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=========================================
Intel® SPMD Program Compiler User's Guide
=========================================
The Intel® SPMD Program Compiler (``ispc``) is a compiler for writing SPMD
(single program multiple data) programs to run on the CPU. The SPMD
programming approach is widely known to graphics and GPGPU programmers; it
is used for GPU shaders and CUDA\* and OpenCL\* kernels, for example. The
main idea behind SPMD is that one writes programs as if they were operating
on a single data element (a pixel for a pixel shader, for example), but
then the underlying hardware and runtime system executes multiple
invocations of the program in parallel with different inputs (the values
for different pixels, for example).
The main goals behind ``ispc`` are to:
* Build a variant of the C programming language that delivers good
performance to performance-oriented programmers who want to run SPMD
programs on CPUs.
* Provide a thin abstraction layer between the programmer and the
hardware--in particular, to follow the lesson from C for serial programs
of having an execution and data model where the programmer can cleanly
reason about the mapping of their source program to compiled assembly
language and the underlying hardware.
* Harness the computational power of the Single Program, Multiple Data (SIMD) vector
units without the extremely low-programmer-productivity activity of directly
writing intrinsics.
* Explore opportunities from close-coupling between C/C++ application code
and SPMD ``ispc`` code running on the same processor--lightweight function
calls between the two languages, sharing data directly via pointers without
copying or reformatting, etc.
**We are very interested in your feedback and comments about ispc and
in hearing your experiences using the system. We are especially interested
in hearing if you try using ispc but see results that are not as you
were expecting or hoping for.** We encourage you to send a note with your
experiences or comments to the `ispc-users`_ mailing list or to file bug or
feature requests with the ``ispc`` `bug tracker`_. (Thanks!)
.. _ispc-users: http://groups.google.com/group/ispc-users
.. _bug tracker: https://github.com/ispc/ispc/issues?state=open
Contents:
* `Recent Changes to ISPC`_
+ `Updating ISPC Programs For Changes In ISPC 1.1`_
+ `Updating ISPC Programs For Changes In ISPC 1.2`_
+ `Updating ISPC Programs For Changes In ISPC 1.3`_
+ `Updating ISPC Programs For Changes In ISPC 1.5.0`_
+ `Updating ISPC Programs For Changes In ISPC 1.6.0`_
+ `Updating ISPC Programs For Changes In ISPC 1.7.0`_
+ `Updating ISPC Programs For Changes In ISPC 1.8.2`_
+ `Updating ISPC Programs For Changes In ISPC 1.9.0`_
+ `Updating ISPC Programs For Changes In ISPC 1.9.1`_
* `Getting Started with ISPC`_
+ `Installing ISPC`_
+ `Compiling and Running a Simple ISPC Program`_
* `Using The ISPC Compiler`_
+ `Basic Command-line Options`_
+ `Selecting The Compilation Target`_
+ `Generating Generic C++ Output`_
+ `Compiling For The Intel® Xeon Phi™ Architecture (codename Knights Corner)`_
+ `Compiling For The Intel® Xeon Phi™ Architecture (codename Knights Landing)`_
+ `Selecting 32 or 64 Bit Addressing`_
+ `The Preprocessor`_
+ `Debugging`_
* `The ISPC Parallel Execution Model`_
+ `Basic Concepts: Program Instances and Gangs of Program Instances`_
+ `Control Flow Within A Gang`_
* `Control Flow Example: If Statements`_
* `Control Flow Example: Loops`_
* `Gang Convergence Guarantees`_
+ `Uniform Data`_
* `Uniform Control Flow`_
* `Uniform Variables and Varying Control Flow`_
+ `Data Races Within a Gang`_
+ `Tasking Model`_
* `The ISPC Language`_
+ `Relationship To The C Programming Language`_
+ `Lexical Structure`_
+ `Types`_
* `Basic Types and Type Qualifiers`_
* `"uniform" and "varying" Qualifiers`_
* `Defining New Names For Types`_
* `Pointer Types`_
* `Function Pointer Types`_
* `Reference Types`_
* `Enumeration Types`_
* `Short Vector Types`_
* `Array Types`_
* `Struct Types`_
+ `Operators Overloading`_
* `Structure of Array Types`_
+ `Declarations and Initializers`_
+ `Expressions`_
* `Dynamic Memory Allocation`_
+ `Control Flow`_
* `Conditional Statements: "if"`_
* `Conditional Statements: "switch"`_
* `Iteration Statements`_
+ `Basic Iteration Statements: "for", "while", and "do"`_
+ `Iteration over active program instances: "foreach_active"`_
+ `Iteration over unique elements: "foreach_unique"`_
+ `Parallel Iteration Statements: "foreach" and "foreach_tiled"`_
+ `Parallel Iteration with "programIndex" and "programCount"`_
* `Unstructured Control Flow: "goto"`_
* `"Coherent" Control Flow Statements: "cif" and Friends`_
* `Functions and Function Calls`_
+ `Function Overloading`_
* `Re-establishing The Execution Mask`_
* `Task Parallel Execution`_
+ `Task Parallelism: "launch" and "sync" Statements`_
+ `Task Parallelism: Runtime Requirements`_
* `The ISPC Standard Library`_
+ `Basic Operations On Data`_
* `Logical and Selection Operations`_
* `Bit Operations`_
+ `Math Functions`_
* `Basic Math Functions`_
* `Transcendental Functions`_
* `Pseudo-Random Numbers`_
* `Random Numbers`_
+ `Output Functions`_
+ `Assertions`_
+ `Cross-Program Instance Operations`_
* `Reductions`_
+ `Data Movement`_
* `Setting and Copying Values In Memory`_
* `Packed Load and Store Operations`_
+ `Data Conversions`_
* `Converting Between Array-of-Structures and Structure-of-Arrays Layout`_
* `Conversions To and From Half-Precision Floats`_
* `Converting to sRGB8`_
+ `Systems Programming Support`_
* `Atomic Operations and Memory Fences`_
* `Prefetches`_
* `System Information`_
* `Interoperability with the Application`_
+ `Interoperability Overview`_
+ `Data Layout`_
+ `Data Alignment and Aliasing`_
+ `Restructuring Existing Programs to Use ISPC`_
* `Experimental support for PTX`_
+ `Overview`_
+ `Compiling For The NVIDIA Kepler GPU`_
+ `Hints`_
+ `Limitations & known issues`_
* `Disclaimer and Legal Information`_
* `Optimization Notice`_
Recent Changes to ISPC
======================
See the file `ReleaseNotes.txt`_ in the ``ispc`` distribution for a list
of recent changes to the compiler.
.. _ReleaseNotes.txt: https://raw.github.com/ispc/ispc/master/docs/ReleaseNotes.txt
Updating ISPC Programs For Changes In ISPC 1.1
----------------------------------------------
The major changes introduced in the 1.1 release of ``ispc`` are first-class
support for pointers in the language and new parallel loop constructs.
Adding this functionality required a number of syntactic changes to the
language. These changes should generally lead to straightforward minor
modifications of existing ``ispc`` programs.
These are the relevant changes to the language:
* The syntax for reference types has been changed to match C++'s syntax for
references and the ``reference`` keyword has been removed. (A diagnostic
message is issued if ``reference`` is used.)
+ Declarations like ``reference float foo`` should be changed to ``float &foo``.
+ Any array parameters in function declaration with a ``reference``
qualifier should just have ``reference`` removed: ``void foo(reference
float bar[])`` can just be ``void foo(float bar[])``.
* It is now a compile-time error to assign an entire array to another
array.
* A number of standard library routines have been updated to take
pointer-typed parameters, rather than references or arrays an index
offsets, as appropriate. For example, the ``atomic_add_global()``
function previously took a reference to the variable to be updated
atomically but now takes a pointer. In a similar fashion,
``packed_store_active()`` takes a pointer to a ``uniform unsigned int``
as its first parameter rather than taking a ``uniform unsigned int[]`` as
its first parameter and a ``uniform int`` offset as its second parameter.
* It is no longer legal to pass a varying lvalue to a function that takes a
reference parameter; references can only be to uniform lvalue types. In
this case, the function should be rewritten to take a varying pointer
parameter.
* There are new iteration constructs for looping over computation domains,
``foreach`` and ``foreach_tiled``. In addition to being syntactically
cleaner than regular ``for`` loops, these can provide performance
benefits in many cases when iterating over data and mapping it to program
instances. See the Section `Parallel Iteration Statements: "foreach" and
"foreach_tiled"`_ for more information about these.
Updating ISPC Programs For Changes In ISPC 1.2
----------------------------------------------
The following changes were made to the language syntax and semantics for
the ``ispc`` 1.2 release:
* Syntax for the "launch" keyword has been cleaned up; it's now no longer
necessary to bracket the launched function call with angle brackets. (In
other words, now use ``launch foo();``, rather than ``launch < foo() >;``.)
* When using pointers, the pointed-to data type is now "uniform" by
default. Use the varying keyword to specify varying pointed-to types
when needed. (i.e. ``float *ptr`` is a varying pointer to uniform float
data, whereas previously it was a varying pointer to varying float
values.) Use ``varying float *`` to specify a varying pointer to varying
float data, and so forth.
* The details of "uniform" and "varying" and how they interact with struct
types have been cleaned up. Now, when a struct type is declared, if the
struct elements don't have explicit "uniform" or "varying" qualifiers,
they are said to have "unbound" variability. When a struct type is
instantiated, any unbound variability elements inherit the variability of
the parent struct type. See `Struct Types`_ for more details.
* ``ispc`` has a new language feature that makes it much easier to use the
efficient "(array of) structure of arrays" (AoSoA, or SoA) memory layout
of data. A new ``soa<n>`` qualifier can be applied to structure types to
specify an n-wide SoA version of the corresponding type. Array indexing
and pointer operations with arrays SoA types automatically handles the
two-stage indexing calculation to access the data. See `Structure of
Array Types`_ for more details.
Updating ISPC Programs For Changes In ISPC 1.3
----------------------------------------------
This release adds a number of new iteration constructs, which in turn use
new reserved words: ``unmasked``, ``foreach_unique``, ``foreach_active``,
and ``in``. Any program that happens to have a variable or function with
one of these names must be modified to rename that symbol.
Updating ISPC Programs For Changes In ISPC 1.5.0
------------------------------------------------
This release adds support for double precision floating point constants.
Double precision floating point constants are floating point number with
``d`` suffix and optional exponent part. Here are some examples: 3.14d,
31.4d-1, 1.d, 1.0d, 1d-2. Note that floating point number without suffix is
treated as single precision constant.
Updating ISPC Programs For Changes In ISPC 1.6.0
------------------------------------------------
This release adds support for `Operators Overloading`_, so a word ``operator``
becomes a keyword and it potentially creates a conflict with existing user
function. Also a new library function packed_store_active2() was introduced,
which also may create a conflict with existing user functions.
Updating ISPC Programs For Changes In ISPC 1.7.0
------------------------------------------------
This release contains several changes that may affect compatibility with
older versions:
* The algorithm for selecting overloaded functions was extended to cover more
types of overloading, and handling of reference types was fixed. At the same
time the old scheme, which blindly used the function with "the best score"
summed for all arguments, was switched to the C++ approach, which requires
"the best score" for each argument. If the best function doesn't exist, a
warning is issued in this version. It will be turned into an error in the
next version. A simple example: Suppose we have two functions: max(int, int)
and max(unsigned int, unsigned int). The new rules lead to an error when
calling max(int, unsigned int), as the best choice is ambiguous.
* Implicit cast of pointer to const type to void* was disallowed. Use explicit
cast if needed.
* A bug which prevented "const" qualifiers from appearing in emitted .h files
was fixed. Consequently, "const" qualifiers now properly appearing in emitted
.h files may cause compile errors in pre-existing codes.
* get_ProgramCount() was moved from stdlib to examples/util/util.isph file. You
need to include this file to be able to use this function.
Updating ISPC Programs For Changes In ISPC 1.8.2
------------------------------------------------
The release doesn't contain language changes, which may affect compatibility with
older versions. Though you may want be aware of the following:
* Mangling of uniform types was changed to not include varying width, so now you
may use uniform structures and pointers to uniform types as return types in
export functions in multi-target compilation.
Updating ISPC Programs For Changes In ISPC 1.9.0
------------------------------------------------
The release doesn't contains language changes, which may affect compatibility with
older versions. It introduces new AVX512 target: avx512knl-i32x16.
Updating ISPC Programs For Changes In ISPC 1.9.1
------------------------------------------------
The release doesn't contains language changes, which may affect compatibility with
older versions. It introduces new AVX512 target: avx512skx-i32x16.
Getting Started with ISPC
=========================
Installing ISPC
---------------
The `ispc downloads web page`_ has prebuilt executables for Windows\*,
Linux\* and Mac OS\* available for download. Alternatively, you can
download the source code from that page and build it yourself; see see the
`ispc wiki`_ for instructions about building ``ispc`` from source.
.. _ispc downloads web page: downloads.html
.. _ispc wiki: http://github.com/ispc/ispc/wiki
Once you have an executable for your system, copy it into a directory
that's in your ``PATH``. Congratulations--you've now installed ``ispc``.
Compiling and Running a Simple ISPC Program
-------------------------------------------
The directory ``examples/simple`` in the ``ispc`` distribution includes a
simple example of how to use ``ispc`` with a short C++ program. See the
file ``simple.ispc`` in that directory (also reproduced here.)
::
export void simple(uniform float vin[], uniform float vout[],
uniform int count) {
foreach (index = 0 ... count) {
float v = vin[index];
if (v < 3.)
v = v * v;
else
v = sqrt(v);
vout[index] = v;
}
}
This program loops over an array of values in ``vin`` and computes an
output value for each one. For each value in ``vin``, if its value is less
than three, the output is the value squared, otherwise it's the square root
of the value.
The first thing to notice in this program is the presence of the ``export``
keyword in the function definition; this indicates that the function should
be made available to be called from application code. The ``uniform``
qualifiers on the parameters to ``simple`` indicate that the corresponding
variables are non-vector quantities--this concept is discussed in detail in the
`"uniform" and "varying" Qualifiers`_ section.
Each iteration of the ``foreach`` loop works on a number of input values in
parallel--depending on the compilation target chosen, it may be 4, 8, or
even 16 elements of the ``vin`` array, processed efficiently with the CPU's
SIMD hardware. Here, the variable ``index`` takes all values from 0 to
``count-1``. After the load from the array to the variable ``v``, the
program can then proceed, doing computation and control flow based on the
values loaded. The result from the running program instances is written to
the ``vout`` array before the next iteration of the ``foreach`` loop runs.
On Linux\* and Mac OS\*, the makefile in that directory compiles this program.
For Windows\*, open the ``examples/examples.sln`` file in Microsoft Visual
C++ 2012\* to build this (and the other) examples. In either case,
build it now! We'll walk through the details of the compilation steps in
the following section, `Using The ISPC Compiler`_.) In addition to
compiling the ``ispc`` program, in this case the ``ispc`` compiler also
generates a small header file, ``simple.h``. This header file includes the
declaration for the C-callable function that the above ``ispc`` program is
compiled to. The relevant parts of this file are:
::
#ifdef __cplusplus
extern "C" {
#endif // __cplusplus
extern void simple(float vin[], float vout[], int32_t count);
#ifdef __cplusplus
}
#endif // __cplusplus
It's not mandatory to ``#include`` the generated header file in your C/C++
code (you can alternatively use a manually-written ``extern`` declaration
of the ``ispc`` functions you use), but it's a helpful check to ensure that
the function signatures are as expected on both sides.
Here is the main program, ``simple.cpp``, which calls the ``ispc`` function
above.
::
#include <stdio.h>
#include "simple.h"
int main() {
float vin[16], vout[16];
for (int i = 0; i < 16; ++i)
vin[i] = i;
simple(vin, vout, 16);
for (int i = 0; i < 16; ++i)
printf("%d: simple(%f) = %f\n", i, vin[i], vout[i]);
}
Note that the call to the ``ispc`` function in the middle of ``main()`` is
a regular function call. (And it has the same overhead as a C/C++ function
call, for that matter.)
When the executable ``simple`` runs, it generates the expected output:
::
0: simple(0.000000) = 0.000000
1: simple(1.000000) = 1.000000
2: simple(2.000000) = 4.000000
3: simple(3.000000) = 1.732051
...
For a slightly more complex example of using ``ispc``, see the `Mandelbrot
set example`_ page on the ``ispc`` website for a walk-through of an ``ispc``
implementation of that algorithm. After reading through that example, you
may want to examine the source code of the various examples in the
``examples/`` directory of the ``ispc`` distribution.
.. _Mandelbrot set example: http://ispc.github.com/example.html
Using The ISPC Compiler
=======================
To go from a ``ispc`` source file to an object file that can be linked
with application code, enter the following command
::
ispc foo.ispc -o foo.o
(On Windows, you may want to specify ``foo.obj`` as the output filename.)
Basic Command-line Options
--------------------------
The ``ispc`` executable can be run with ``--help`` to print a list of
accepted command-line arguments. By default, the compiler compiles the
provided program (and issues warnings and errors), but doesn't
generate any output.
If the ``-o`` flag is given, it will generate an output file (a native
object file by default).
::
ispc foo.ispc -o foo.obj
To generate a text assembly file, pass ``--emit-asm``:
::
ispc foo.ispc -o foo.asm --emit-asm
To generate LLVM bitcode, use the ``--emit-llvm`` flag.
Optimizations are on by default; they can be turned off with ``-O0``:
::
ispc foo.ispc -o foo.obj -O0
On Mac\* and Linux\*, there is basic support for generating debugging
symbols; this is enabled with the ``-g`` command-line flag. Using ``-g``
causes optimizations to be disabled; to compile with debugging symbols and
optimization, ``-O1`` should be provided as well as the ``-g`` flag.
The ``-h`` flag can also be used to direct ``ispc`` to generate a C/C++
header file that includes C/C++ declarations of the C-callable ``ispc``
functions and the types passed to it.
The ``-D`` option can be used to specify definitions to be passed along to
the pre-processor, which runs over the program input before it's compiled.
For example, including ``-DTEST=1`` defines the pre-processor symbol
``TEST`` to have the value ``1`` when the program is compiled.
The compiler issues a number of performance warnings for code constructs
that compile to relatively inefficient code. These warnings can be
silenced with the ``--wno-perf`` flag (or by using ``--woff``, which turns
off all compiler warnings.) Furthermore, ``--werror`` can be provided to
direct the compiler to treat any warnings as errors.
Position-independent code (for use in shared libraries) is generated if the
``--pic`` command-line argument is provided.
Selecting The Compilation Target
--------------------------------
There are three options that affect the compilation target: ``--arch``,
which sets the target architecture, ``--cpu``, which sets the target CPU,
and ``--target``, which sets the target instruction set.
If none of these options is specified, ``ispc`` generates code for the
architecture of the system the compiler is running on (i.e. 64-bit x86-64
(``--arch=x86-64``) on x86 systems and ARM NEON on ARM systems.
To compile to a 32-bit x86 target, for example, supply ``--arch=x86`` on
the command line:
::
ispc foo.ispc -o foo.obj --arch=x86
Currently-supported architectures are ``x86-64``, ``x86``, and ``arm``.
The target CPU determines both the default instruction set used as well as
which CPU architecture the code is tuned for. ``ispc --help`` provides a
list of all of the supported CPUs. By default, the CPU type of the system
on which you're running ``ispc`` is used to determine the target CPU.
::
ispc foo.ispc -o foo.obj --cpu=corei7-avx
Finally, ``--target`` selects the target instruction set. The target
string is of the form ``[ISA]-i[mask size]x[gang size]``. For example,
``--target=avx2-i32x16`` specifies a target with the AVX2 instruction set,
a mask size of 32 bits, and a gang size of 16.
The following target ISAs are supported:
============ =========================================================
Target Description
------------ ---------------------------------------------------------
avx, avx1 AVX (2010-2011 era Intel CPUs)
avx1.1 AVX 1.1 (2012 era "Ivybridge" Intel CPUs)
avx2 AVX 2 target (2013- Intel "Haswell" CPUs)
avx512knl AVX 512 target (Xeon Phi chips codename Knights Landing)
avx512skx AVX 512 target (future Xeon CPUs)
neon ARM NEON
sse2 SSE2 (early 2000s era x86 CPUs)
sse4 SSE4 (generally 2008-2010 Intel CPUs)
============ =========================================================
Consult your CPU's manual for specifics on which vector instruction set it
supports.
The mask size may be 8, 16, or 32 bits, though not all combinations of ISAs
and mask sizes are supported. For best performance, the best general
approach is to choose a mask size equal to the size of the most common
datatype in your programs. For example, if most of your computation is on
32-bit floating-point values, an ``i32`` target is appropriate. However,
if you're mostly doing computation on 8-bit images, ``i8`` is a better choice.
See `Basic Concepts: Program Instances and Gangs of Program Instances`_ for
more discussion of the "gang size" and its implications for program
execution.
Running ``ispc --help`` and looking at the output for the ``--target``
option gives the most up-to-date documentation about which targets your
compiler binary supports.
The naming scheme for compilation targets changed in August 2013; the
following table shows the relationship between names in the old scheme and
in the new scheme:
============= ===========
Target Former Name
------------- -----------
avx1-i32x8 avx, avx1
avx1-i32x16 avx-x2
avx1.1-i32x8 avx1.1
avx1.1-i32x16 avx1.1-x2
avx2-i32x8 avx2
avx2-i32x16 avx2-x2
neon-8 n/a
neon-16 n/a
neon-32 n/a
sse2-i32x4 sse2
sse2-i32x8 sse2-x2
sse4-i32x4 sse4
sse4-i32x8 sse4-x2
sse4-i8x16 n/a
sse4-i16x8 n/a
============= ===========
By default, the target instruction set is chosen based on the most capable
one supported by the system on which you're running ``ispc``. You can
override this choice with the ``--target`` flag; for example, to select
Intel® SSE2 with a 32-bit mask and 4 program instances in a gang, use
``--target=sse2-i32x4``. (As with the other options in this section, see
the output of ``ispc --help`` for a full list of supported targets.)
Generating Generic C++ Output
-----------------------------
In addition to generating object files or assembly output for specific
targets like NEON, SSE2, SSE4, and AVX, ``ispc`` provides an option to generate
"generic" C++ output. This
As an example, consider the following simple ``ispc`` program:
::
int foo(int i, int j) {
return (i < 0) ? 0 : i + j;
}
If this program is compiled with the following command:
::
ispc foo.ispc --emit-c++ --target=generic-4 -o foo.cpp
Then ``foo()`` is compiled to the following C++ code (after various
automatically-generated boilerplate code):
::
__vec4_i32 foo(__vec4_i32 i_llvm_cbe, __vec4_i32 j_llvm_cbe,
__vec4_i1 __mask_llvm_cbe) {
return (__select((__signed_less_than(i_llvm_cbe,
__vec4_i32 (0u, 0u, 0u, 0u))),
__vec4_i32 (0u, 0u, 0u, 0u),
(__add(i_llvm_cbe, j_llvm_cbe))));
}
Note that the original computation has been expressed in terms of a number
of vector types (e.g. ``__vec4_i32`` for a 4-wide vector of 32-bit integers
and ``__vec4_i1`` for a 4-wide vector of boolean values) and in terms of
vector operations on these types like ``__add()`` and ``__select()``).
You are then free to provide your own implementations of these types and
functions. For example, you might want to target a specific vector ISA, or
you might want to instrument these functions for performance measurements.
There is an example implementation of 4-wide variants of the required
functions, suitable for use with the ``generic-4`` target in the file
``examples/intrinsics/sse4.h``, and there is an example straightforward C
implementation of the 16-wide variants for the ``generic-16`` target in the
file ``examples/intrinsics/generic-16.h``. There is not yet comprehensive
documentation of these types and the functions that must be provided for
them when the C++ target is used, but a review of those two files should
provide the basic context.
If you are using C++ source emission, you may also find the
``--c++-include-file=<filename>`` command line argument useful; it adds an
``#include`` statement with the given filename at the top of the emitted
C++ file; this can be used to easily include specific implementations of
the vector types and functions.
Compiling For The Intel® Xeon Phi™ Architecture (codename Knights Corner)
--------------------------------------------------------------------------
``ispc`` has beta-level support for compiling for the many-core Intel®
Xeon Phi™ architecture (formerly, "Many Integrated Cores" / MIC, codename
Knights Corner).
This support is based on the "generic" C++ output, described in the previous
section.
To compile for Xeon Phi™, first generate intermediate C++ code:
::
ispc foo.ispc --emit-c++ --target=generic-16 -o foo.cpp \
--c++-include-file=knc.h
The ``ispc`` distribution now includes a header file,
``examples/intrinsics/knc.h``, which maps from the generic C++ output
to the corresponding intrinsic operations supported by Intel Xeon Phi™.
Thus, to generate an object file, use the Intel C++ Compiler (``icpc``) compile
the C++ code generated by ``ispc``, setting the ``#include`` search
path so that it can find the ``examples/intrinsics/knc.h`` header file
in the ``ispc`` distribution.
::
icpc -mmic -Iexamples/intrinsics/ foo.cpp -o foo.o
With the current beta implementation, complex ``ispc`` programs are able to
run on Xeon Phi™, though there are a number of known limitations:
* The ``examples/intrinsics/knc.h`` header file isn't complete yet; for
example, vector operations with ``int8`` and ``int16`` types aren't yet
implemented. Programs that operate on ``varying`` ``int32``, ``float``,
and ``double`` data-types (and ``uniform`` variables of any data type,
and arrays and structures of these types), should operate correctly.
* If you use the ``launch`` functionality to launch tasks across cores,
note that the pthreads task system implemented in
``examples/tasksys.cpp`` offers several implemenetations for Xeon Phi™.
You will need to experiment to understand which one is most
appropriate for your workload.
* The compiler currently emits unaligned memory accesses in many cases
where the memory address is actually aligned. This may unnecessarily
impact performance.
* When requesting that ICPC generate code with strict floating point
precision compliance (using ICPC option ``-fp-model strict``) or
accurate reporting of floating point exceptions (using ICPC option
``-fp-model except``) the compiler will generate code that uses the
x87 unit rather than Xeon Phi™'s vector unit. For similar reasons, the
options ``–ansi`` and ``–fmath-errno`` may result in calls to math
functions that are implemented in x87 rather than using vector instructions.
This will have a significant performance impact. See the ICPC manual for
details on these compiler options.
All of these issues are currently actively being addressed and will be
fixed in future releases.
If you do use the current version of ``ispc`` on Intel Xeon Phi™,
please let us know of any bugs or unexpected results. (Also, any
interesting results!).
Compiling For The Intel® Xeon Phi™ Architecture (codename Knights Landing)
---------------------------------------------------------------------------
``ispc`` starting from v1.9.0 has support for compiling for the second
generation of Intel® Xeon Phi™ architecture (codename Knights Landing).
Two compilation paths are supported - generic (similar to KNC support) and
native.
To compile using generic path, follow KNC instructions, but use knl.h, instead
of knc.h and use -xMIC-AVX512 for ICPC instead of -mmic.
To compile using native path, just set --target=avx512knl-i32x16.
Going forward, generic path will be deprecated, so using native target is
preferable way to get AVX512 support.
Selecting 32 or 64 Bit Addressing
---------------------------------
By default, ``ispc`` uses 32-bit arithmetic for performing addressing
calculations, even when using a 64-bit compilation target like x86-64.
This implementation approach can provide substantial performance benefits
by reducing the cost of addressing calculations. (Note that pointers
themselves are still maintained as 64-bit quantities for 64-bit targets.)
If you need to be able to address more than 4GB of memory from your
``ispc`` programs, the ``--addressing=64`` command-line argument can be
provided to cause the compiler to generate 64-bit arithmetic for addressing
calculations. Note that it is safe to mix object files where some were
compiled with the default ``--addressing=32`` and others were compiled with
``--addressing=64``.
The Preprocessor
----------------
``ispc`` automatically runs the C preprocessor on your input program before
compiling it. Thus, you can use ``#ifdef``, ``#define``, and so forth in
your ispc programs. (This functionality can be disabled with the ``--nocpp``
command-line argument.)
A number of preprocessor symbols are automatically defined before the
preprocessor runs:
.. list-table:: Predefined Preprocessor symbols and their values
* - Symbol name
- Value
- Use
* - ISPC
- 1
- Detecting that the ``ispc`` compiler is processing the file
* - ISPC_TARGET_{NEON_8, NEON_16, NEON_32, SSE2, SSE4, AVX, AVX11, AVX2, AVX512KNL, AVX512SKX, GENERIC}
- 1
- One of these will be set, depending on the compilation target.
* - ISPC_POINTER_SIZE
- 32 or 64
- Number of bits used to represent a pointer for the target architecture.
* - ISPC_MAJOR_VERSION
- 1
- Major version of the ``ispc`` compiler/language
* - ISPC_MINOR_VERSION
- 3
- Minor version of the ``ispc`` compiler/language
* - PI
- 3.1415926535
- Mathematics
Debugging
---------
On Linux\* and Mac OS\*, the ``-g`` command-line flag can be supplied to
the compiler, which causes it to generate debugging symbols. Running
``ispc`` programs in the debugger, setting breakpoints, printing out
variables is just the same as debugging C/C++ programs. Similarly, you can
directly step up and down the call stack between ``ispc`` code and C/C++
code.
One limitation of the current debugging support is that the debugger
provides a window into an entire gang's worth of program instances, rather
than just a single program instance. (These concepts will be introduced
shortly, in `Basic Concepts: Program Instances and Gangs of Program
Instances`). Thus, when a ``varying`` variable is printed, the values for
each of the program instances are displayed. Along similar lines, the path
the debugger follows through program source code passes each statement that
any program instance wants to execute (see `Control Flow Within A Gang`_
for more details on control flow in ``ispc``.)
While debugging, a variable, ``__mask``, is available to provide the
current program execution mask at the current point in the program
Another option for debugging (and the only current option on Windows\*) is
to use the ``print`` statement for ``printf()`` style debugging. (See
`Output Functions`_ for more information.) You can also use the ability to
call back to application code at particular points in the program, passing
a set of variable values to be logged or otherwise analyzed from there.
The ISPC Parallel Execution Model
=================================
Though ``ispc`` is a C-based language, it is inherently a language for
parallel computation. Understanding the details of ``ispc``'s parallel
execution model that are introduced in this section is critical for writing
efficient and correct programs in ``ispc``.
``ispc`` supports two types of parallelism: task parallelism to parallelize
across multiple processor cores and SPMD parallelism to parallelize across
the SIMD vector lanes on a single core. Most of this section focuses on
SPMD parallelism, but see `Tasking Model`_ at the end of this section for
discussion of task parallelism in ``ispc``.
This section will use some snippets of ``ispc`` code to illustrate various
concepts. Given ``ispc``'s relationship to C, these should be
understandable on their own, but you may want to refer to the `The ISPC
Language`_ section for details on language syntax.
Basic Concepts: Program Instances and Gangs of Program Instances
----------------------------------------------------------------
Upon entry to a ``ispc`` function called from C/C++ code, the execution
model switches from the application's serial model to ``ispc``'s execution
model. Conceptually, a number of ``ispc`` *program instances* start
running concurrently. The group of running program instances is a
called a *gang* (harkening to "gang scheduling", since ``ispc`` provides
certain guarantees about the control flow coherence of program instances
running in a gang, detailed in `Gang Convergence Guarantees`_.) An
``ispc`` program instance is thus similar to a CUDA* "thread" or an OpenCL*
"work-item", and an ``ispc`` gang is similar to a CUDA* "warp".
An ``ispc`` program expresses the computation performed by a gang of
program instances, using an "implicit parallel" model, where the ``ispc``
program generally describes the behavior of a single program instance, even
though a gang of them is actually executing together. This implicit model
is the same that is used for shaders in programmable graphics pipelines,
OpenCL* kernels, and CUDA*. For example, consider the following ``ispc``
function:
::
float func(float a, float b) {
return a + b / 2.;
}
In C, this function describes a simple computation on two individual
floating-point values. In ``ispc``, this function describes the
computation to be performed by each program instance in a gang. Each
program instance has distinct values for the variables ``a`` and ``b``, and
thus each program instance generally computes a different result when
executing this function.
The gang of program instances starts executing in the same hardware thread
and context as the application code that called the ``ispc`` function; no
thread creation or context switching is done under the covers by ``ispc``.
Rather, the set of program instances is mapped to the SIMD lanes of the
current processor, leading to excellent utilization of hardware SIMD units
and high performance.
The number of program instances in a gang is relatively small; in practice,
it's no more than 2-4x the native SIMD width of the hardware it is
executing on. (Thus, four or eight program instances in a gang on a CPU
using the the 4-wide SSE instruction set, and eight or sixteen on a CPU
using 8-wide AVX.)
Control Flow Within A Gang
--------------------------
Almost all the standard control-flow constructs are supported by ``ispc``;
program instances are free to follow different program execution paths than
other ones in their gang. For example, consider a simple ``if`` statement
in ``ispc`` code:
::
float x = ..., y = ...;
if (x < y) {
// true statements
}
else {
// false statements
}
In general, the test ``x < y`` may have different result for different
program instances in the gang: some of the currently running program
instances want to execute the statements for the "true" case and some want
to execute the statements for the "false" case.
Complex control flow in ``ispc`` programs generally works as expected,
computing the same results for each program instance in a gang as would
have been computed if the equivalent code ran serially in C to compute each
program instance's result individually. However, here we will more
precisely define the execution model for control flow in order to be able
to precisely define the language's behavior in specific situations.
We will specify the notion of a *program counter* and how it is updated to
step through the program, and an *execution mask* that indicates which
program instances want to execute the instruction at the current program
counter. The program counter is shared by all of the
program instances in the gang; it points to a single instruction to be
executed next. The execution mask is a per-program-instance boolean value
that indicates whether or not side effects from the current instruction
should effect each program instance. Thus, for example, if a statement
were to be executed with an "all off" mask, there should be no observable
side-effects.
Upon entry to an ``ispc`` function called by the application, the execution
mask is "all on" and the program counter points at the first statement in
the function. The following two statements describe the required behavior
of the program counter and the execution mask over the course of execution
of an ``ispc`` function.
1. The program counter will have a sequence of values corresponding to a
conservative execution path through the function, wherein if *any*
program instance wants to execute a statement, the program counter will
pass through that statement.
2. At each statement the program counter passes through, the execution
mask will be set such that its value for a particular program instance is
"on" if and only if the program instance wants to execute that statement.
Note that these definitions provide the compiler some latitude; for example,
the program counter is allowed to pass through a series of statements with the
execution mask "all off" because doing so has no observable side-effects.
Elsewhere, we will speak informally of the *control flow coherence* of a
program; this notion describes the degree to which the program instances in
the gang want to follow the same control flow path through a function (or,
conversely, whether most statements are executed with a "mostly on"
execution mask or a "mostly off" execution mask.) In general, control flow
divergence leads to reductions in SIMD efficiency (and thus performance) as
different program instances want to perform different computations.
Control Flow Example: If Statements
-----------------------------------
As a concrete example of the interplay between program counter and
execution mask, one way that an ``if`` statement like the one in the
previous section can be represented is shown by the following pseudo-code
compiler output:
::
float x = ..., y = ...;
bool test = (x < y);
mask originalMask = get_current_mask();
set_mask(originalMask & test);
if (any_mask_entries_are_enabled()) {
// true statements
}
set_mask(originalMask & ~test);
if (any_mask_entries_are_enabled()) {
// false statements
}
set_mask(originalMask);
In other words, the program counter steps through the statements for both
the "true" case and the "false" case, with the execution mask set so that
no side-effects from the true statements affect the program instances that
want to run the false statements, and vice versa. However, a block of
statements does not execute if the mask is "all off" upon entry to that
block. The execution mask is then restored to the value it had before the
``if`` statement.
Control Flow Example: Loops
---------------------------
``for``, ``while``, and ``do`` statements are handled in an analogous
fashion. The program counter continues to run additional iterations of the
loop until all of the program instances are ready to exit the loop.
Therefore, if we have a loop like the following:
::
int limit = ...;
for (int i = 0; i < limit; ++i) {
...
}
where ``limit`` has the value 1 for all of the program instances but one,
and has value 1000 for the other one, the program counter will step through
the loop body 1000 times. The first time, the execution mask will be all
on (assuming it is all on going into the ``for`` loop), and the remaining
999 times, the mask will be off except for the program instance with a
``limit`` value of 1000. (This would be a loop with poor control flow
coherence!)
A ``continue`` statement in a loop may be handled either by disabling the
execution mask for the program instances that execute the ``continue`` and
then continuing to step the program counter through the rest of the loop,
or by jumping to the loop step statement, if all program instances are
disabled after the ``continue`` has executed. ``break`` statements are
handled in a similar fashion.
Gang Convergence Guarantees
---------------------------
The ``ispc`` execution model provides an important guarantee about the
behavior of the program counter and execution mask: the execution of
program instances is *maximally converged*. Maximal convergence means that
if two program instances follow the same control path, they are guaranteed
to execute each program statement concurrently. If two program instances
follow diverging control paths, it is guaranteed that they will reconverge
as soon as possible in the function (if they do later reconverge). [#]_
.. [#] This is another significant difference between the ``ispc``
execution model and the one implemented by OpenCL* and CUDA*, which
doesn't provide this guarantee.
Maximal convergence means that in the presence of divergent control flow
such as the following:
::
if (test) {
// true
}
else {
// false
}
It is guaranteed that all program instances that were running before the
``if`` test will also be running after the end of the ``else`` block.
(This guarantee stems from the notion of having a single program counter
for the gang of program instances, rather than the concept of a unique
program counter for each program instance.)
Another implication of this property is that it would be illegal for the
``ispc`` implementation to execute a function with an 8-wide gang by
running it two times, with a 4-wide gang representing half of the original
8-wide gang each time.
It also follows that given the following program:
::
if (programIndex == 0) {
while (true) // infinite loop
;
}
print("hello, world\n");
the program will loop infinitely and the ``print`` statement will never be
executed. (A different execution model that allowed gang divergence might
execute the ``print`` statement since not all program instances were caught
in the infinite loop in the example above.)
The way that "varying" function pointers are handled in ``ispc`` is also
affected by this guarantee: if a function pointer is ``varying``, then it
has a possibly-different value for all running program instances. Given a
call to a varying function pointer, ``ispc`` must maintains as much
execution convergence as possible; the assembly code generated finds the
set of unique function pointers over the currently running program
instances and calls each one just once, such that the executing program
instances when it is called are the set of active program instances that
had that function pointer value. The order in which the various function
pointers are called in this case is undefined.
Uniform Data
------------
A variable that is declared with the ``uniform`` qualifier represents a
single value that is shared across the entire gang. (In contrast, the
default variability qualifier for variables in ``ispc``, ``varying``,
represents a variable that has a distinct storage location for each program
instance in the gang.) (Though see the discussion in `Struct Types`_ for
some subtleties related to ``uniform`` and ``varying`` when used with
structures.)
It is an error to try to assign a ``varying`` value to a ``uniform``
variable, though ``uniform`` values can be assigned to ``uniform``
variables. Assignments to ``uniform`` variables are not affected by the
execution mask (there's no unambiguous way that they could be); rather,
they always apply if the program counter pointer passes through a statement
that is a ``uniform`` assignment.
Uniform Control Flow
--------------------
One advantage of declaring variables that are shared across the gang as
``uniform``, when appropriate, is the reduction in storage space required.
A more important benefit is that it can enable the compiler to generate
substantially better code for control flow; when a test condition for a
control flow decision is based on a ``uniform`` quantity, the compiler can
be immediately aware that all of the running program instances will follow
the same path at that point, saving the overhead of needing to deal with
control flow divergence and mask management. (To distinguish the two forms
of control flow, will say that control flow based on ``varying``
expressions is "varying" control flow.)
Consider for example an image filtering operation where the program loops
over pixels adjacent to the given (x,y) coordinates:
::
float box3x3(uniform float image[32][32], int x, int y) {
float sum = 0;
for (int dy = -1; dy <= 1; ++dy)
for (int dx = -1; dx <= 1; ++dx)
sum += image[y+dy][x+dx];
return sum / 9.;
}
In general each program instance in the gang has different values for ``x``
and ``y`` in this function. For the box filtering algorithm here, all of
the program instances will actually want to execute the same number of
iterations of the ``for`` loops, with all of them having the same values
for ``dx`` and ``dy`` each time through. If these loops are instead
implemented with ``dx`` and ``dy`` declared as ``uniform`` variables, then
the ``ispc`` compiler can generate more efficient code for the loops. [#]_
.. [#] In this case, a sufficiently smart compiler could determine that
``dx`` and ``dy`` have the same value for all program instances and thus
generate more optimized code from the start, though this optimization
isn't yet implemented in ``ispc``.
::
for (uniform int dy = -1; dy <= 1; ++dy)
for (uniform int dx = -1; dx <= 1; ++dx)
sum += image[y+dy][x+dx];
In particular, ``ispc`` can avoid the overhead of checking to see if any of
the running program instances wants to do another loop iteration. Instead,
the compiler can generate code where all instances always do the same
iterations.
The analogous benefit comes when using ``if`` statements--if the test in an
``if`` statement is based on a ``uniform`` test, then the result will by
definition be the same for all of the running program instances. Thus, the
code for only one of the two cases needs to execute. ``ispc`` can generate
code that jumps to one of the two, avoiding the overhead of needing to run
the code for both cases.
Uniform Variables and Varying Control Flow
------------------------------------------
Recall that in the presence of varying control flow, both the "true" and
"false" clauses of an ``if`` statement may be executed, with the side
effects of the instructions masked so that they only apply to the program
instances that are supposed to be executing the corresponding clause.
Under this model, we must define the effect of modifying ``uniform``
variables in the context of varying control flow.
In general, modifying ``uniform`` variables under varying control flow
leads to the ``uniform`` variable having a value that depends on whether
any of the program instances in the gang followed a particular execution
path. Consider the following example:
::
float a = ...;
uniform int b = 0;
if (a == 0) {
++b;
// b is 1
}
else {
b = 10;
// b is 10
}
// whether b is 1 or 10 depends on whether any of the values
// of "a" in the executing gang were 0.
Here, if any of the values of ``a`` across the gang was non-zero, then
``b`` will have a value of 10 after the ``if`` statement has executed.
However, if all of the values of ``a`` in the currently-executing program
instances at the start of the ``if`` statement had a value of zero, then
``b`` would have a value of 1.
Data Races Within a Gang
------------------------
In order to be able to write well-formed programs where program instances
depend on values that are written to memory by other program instances
within their gang, it's necessary to have a clear definition of when
side-effects from one program instance become visible to other program
instances running in the same gang.
In the model implemented by ``ispc``, any side effect from one program
instance is visible to other program instances in the gang after the next
sequence point in the program. [#]_
.. [#] This is a significant difference between ``ispc`` and SPMD languages
like OpenCL* and CUDA*, which require barrier synchronization among the
running program instances with functions like ``barrier()`` or
``__syncthreads()``, respectively, to ensure this condition.
Generally, sequence points include the end of a full expression, before a
function is entered in a function call, at function return, and at the end
of initializer expressions. The fact that there is no sequence point
between the increment of ``i`` and the assignment to ``i`` in ``i=i++`` is
why the effect that expression is undefined in C, for example. See, for
example, the `Wikipedia page on sequence points`_ for more information
about sequence points in C and C++.
.. _Wikipedia page on sequence points: http://en.wikipedia.org/wiki/Sequence_point
In the following example, we have declared an array of values ``v``, with
one value for each running program instance. In the below, assume that
``programCount`` gives the gang size, and the ``varying`` integer value
``programIndex`` indexes into the running program instances starting from
zero. (Thus, if 8 program instances are running, the first one of them
will have a value 0, the next one a value of 1, and so forth up to 7.)
::
int x = ...;
uniform int tmp[programCount];
tmp[programIndex] = x;
int neighbor = tmp[(programIndex+1)%programCount];
In this code, the running program instances have written their values of
``x`` into the ``tmp`` array such that the ith element of ``tmp`` is equal
to the value of ``x`` for the ith program instance. Then, the program
instances load the value of ``neighbor`` from ``tmp``, accessing the value
written by their neighboring program instance (wrapping around to the first
one at the end.) This code is well-defined and without data races, since
the writes to and reads from ``tmp`` are separated by a sequence point.
(For this particular application of communicating values from one program
instance to another, there are more efficient built-in functions in the
``ispc`` standard library; see `Cross-Program Instance Operations`_ for
more information.)
It is possible to write code that has data races across the gang of program
instances. For example, if the following function is called with multiple
program instances having the same value of ``index``, then it is undefined
which of them will write their value of ``value`` to ``array[index]``.
::
void assign(uniform int array[], int index, int value) {
array[index] = value;
}
As another example, if the values of the array indices ``i`` and ``j`` have
the same values for some of the program instances, and an assignment like
the following is performed:
::
int i = ..., j = ...;
uniform int array[...] = { ... };
array[i] = array[j];
then the program's behavior is undefined, since there is no sequence point
between the reads and writes to the same location.
While this rule that says that program instances can safely depend on
side-effects from by other program instances in their gang eliminates a
class of synchronization requirements imposed by some other SPMD languages,
it conversely means that it is possible to write ``ispc`` programs that
compute different results when run with different gang sizes.
Tasking Model
-------------
``ispc`` provides an asynchronous function call (i.e. tasking) mechanism
through the ``launch`` keyword. (The syntax is documented in the `Task
Parallelism: "launch" and "sync" Statements`_ section.) A function called
with ``launch`` executes asynchronously from the function that called it;
it may run immediately or it may run concurrently on another processor in
the system, for example. (This model is closely modeled on the model
introduced by Intel® Cilk(tm).)
If a function launches multiple tasks, there are no guarantees about the
order in which the tasks will execute. Furthermore, multiple launched
tasks from a single function may execute concurrently.
A function that has launched tasks may use the ``sync`` keyword to force
synchronization with the launched functions; ``sync`` causes a function to
wait for all of the tasks it has launched to finish before execution
continues after the ``sync``. (Note that ``sync`` only waits for the tasks
launched by the current function, not tasks launched by other functions).
Alternatively, when a function that has launched tasks returns, an implicit
``sync`` waits for all launched tasks to finish before allowing the
function to return to its calling function. This feature is important
since it enables parallel composition: a function can call second function
without needing to be concerned if the second function has launched
asynchronous tasks or not--in either case, when the second function
returns, the first function can trust that all of its computation has
completed.
The ISPC Language
=================
``ispc`` is an extended version of the C programming language, providing a
number of new features that make it easy to write high-performance SPMD
programs for the CPU. Note that between not only the few small syntactic
differences between ``ispc`` and C code but more importantly ``ispc``'s
fundamentally parallel execution model, C code can't just be recompiled to
correctly run in parallel with ``ispc``. However, starting with working C
code and porting it to ``ispc`` can be an efficient way to quickly write
``ispc`` programs.
This section describes the syntax and semantics of the ``ispc`` language.
To understand how to use ``ispc``, you need to understand both the language
syntax and ``ispc``'s parallel execution model, which was described in the
previous section, `The ISPC Parallel Execution Model`_.
Relationship To The C Programming Language
------------------------------------------
This subsection summarizes the differences between ``ispc`` and C; if you
are already familiar with C, you may find it most effective to focus on
this subsection and just focus on the topics in the remainder of section
that introduce new language features. You may also find it helpful to
compare the ``ispc`` and C++ implementations of various algorithms in the
``ispc`` ``examples/`` directory to get a sense of the close relationship
between ``ispc`` and C.
Specifically, C89 is used as the baseline for comparison in this subsection
(this is also the version of C described in the Second Edition of Kernighan
and Ritchie's book). (``ispc`` adopts some features from C99 and from C++,
which will be highlighted in the below.)
``ispc`` has the same syntax and features for the following as is present
in C:
* Expression syntax and basic types
* Syntax for variable declarations
* Control flow structures: ``if``, ``for``, ``while``, ``do``, and ``switch``.
* Pointers, including function pointers, ``void *``, and C's array/pointer
duality (arrays are converted to pointers when passed to functions, etc.)
* Structs and arrays
* Support for recursive function calls
* Support for separate compilation of source files
* "Short-circuit" evaluation of ``||``, ``&&`` and ``? :`` operators
* The preprocessor
``ispc`` adds a number of features from C++ and C99 to this base:
* A boolean type, ``bool``, as well as built-in ``true`` and ``false``
values
* Reference types (e.g. ``const float &foo``)
* Comments delimited by ``//``
* Variables can be declared anywhere in blocks, not just at their start.
* Iteration variables for ``for`` loops can be declared in the ``for``
statement itself (e.g. ``for (int i = 0; ...``)
* The ``inline`` qualifier to indicate that a function should be inlined
* Function overloading by parameter type
* Hexadecimal floating-point constants
* Dynamic memory allocation with ``new`` and ``delete``.
* Limited support for overloaded operators (`Operators Overloading`_).
``ispc`` also adds a number of new features that aren't in C89, C99, or
C++:
* Parallel ``foreach`` and ``foreach_tiled`` iteration constructs (see
`Parallel Iteration Statements: "foreach" and "foreach_tiled"`_)
* The ``foreach_active`` and ``foreach_unique`` iteration constructs, which
provide ways of iterating over subsets of the program instances in the
gang. See `Iteration over active program instances: "foreach_active"`_
and `Iteration over unique elements: "foreach_unique"`_.)
* Language support for task parallelism (see `Task Parallel Execution`_)
* "Coherent" control flow statements that indicate that control flow is
expected to be coherent across the running program instances (see
`"Coherent" Control Flow Statements: "cif" and Friends`_)
* A rich standard library, though one that is different than C's (see `The
ISPC Standard Library`_.)
* Short vector types (see `Short Vector Types`_)
* Syntax to specify integer constants as bit vectors (e.g. ``0b1100`` is 12)
There are a number of features of C89 that are not supported in ``ispc``
but are likely to be supported in future releases:
* There are no types named ``char``, ``short``, or ``long`` (or ``long
double``). However, there are built-in ``int8``, ``int16``, and
``int64`` types
* Character constants
* String constants and arrays of characters as strings
* ``goto`` statements are partially supported (see `Unstructured Control Flow: "goto"`_)
* ``union`` types
* Bitfield members of ``struct`` types
* Variable numbers of arguments to functions
* Literal floating-point constants (even without a ``f`` suffix) are
currently treated as being ``float`` type, not ``double``. To have a double
precision floating point constant use ``d`` suffix.
* The ``volatile`` qualifier
* The ``register`` storage class for variables. (Will be ignored).
The following C89 features are not expected to be supported in any future
``ispc`` release:
* "K&R" style function declarations
* The C standard library
* Octal integer constants
The following reserved words from C89 are also reserved in ``ispc``:
``break``, ``case``, ``const``, ``continue``, ``default``, ``do``,
``double``, ``else``, ``enum``, ``extern``, ``float``, ``for``, ``goto``,
``if``, ``int``, ``NULL``, ``return``, ``signed``, ``sizeof``, ``static``,
``struct``, ``switch``, ``typedef``, ``unsigned``, ``void``, and ``while``.
``ispc`` additionally reserves the following words:
``bool``, ``delete``, ``export``, ``cdo``, ``cfor``, ``cif``, ``cwhile``,
``false``, ``foreach``, ``foreach_active``, ``foreach_tiled``,
``foreach_unique``, ``in``, ``inline``, ``int8``, ``int16``, ``int32``,
``int64``, ``launch``, ``new``, ``print``, ``soa``, ``sync``, ``task``,
``true``, ``uniform``, and ``varying``.
Lexical Structure
-----------------
Tokens in ``ispc`` are delimited by white-space and comments. The
white-space characters are the usual set of spaces, tabs, and carriage
returns/line feeds. Comments can be delineated with ``//``, which starts a
comment that continues to the end of the line, or the start of a comment
can be delineated with ``/*`` at the start and with ``*/`` at the end.
Like C/C++, comments can't be nested.
Identifiers in ``ispc`` are sequences of characters that start with an
underscore or an upper-case or lower-case letter, and then followed by
zero or more letters, numbers, or underscores. Identifiers that start with
two underscores are reserved for use by the compiler.
Integer numeric constants can be specified in base 10, hexadecimal, or
binary. (Octal integer constants aren't supported). Base 10 constants are
given by a sequence of one or more digits from 0 to 9. Hexadecimal
constants are denoted by a leading ``0x`` and then one or more digits from
0-9, a-f, or A-F. Finally, binary constants are denoted by a leading
``0b`` and then a sequence of 1s and 0s.
Here are three ways of specifying the integer value "15":
::
int fifteen_decimal = 15;
int fifteen_hex = 0xf;
int fifteen_binary = 0b1111;
A number of suffixes can be provided with integer numeric constants.
First, "u" denotes that the constant is unsigned, and "ll" denotes a 64-bit
integer constant (while "l" denotes a 32-bit integer constant). It is also
possible to denote units of 1024, 1024*1024, or 1024*1024*1024 with the
SI-inspired suffixes "k", "M", and "G" respectively:
::
int two_kb = 2k; // 2048
int two_megs = 2M; // 2 * 1024 * 1024
int one_gig = 1G; // 1024 * 1024 * 1024
Floating-point constants can be specified in one of three ways. First,
they may be a sequence of zero or more digits from 0 to 9, followed by a
period, followed by zero or more digits from 0 to 9. (There must be at
least one digit before or after the period).
The second option is scientific notation, where a base value is specified
as the first form of a floating-point constant but is then followed by an
"e" or "E", then a plus sign or a minus sign, and then an exponent.
Finally, floating-point constants may be specified as hexadecimal
constants; this form can ensure a perfectly bit-accurate representation of
a particular floating-point number. These are specified with an "0x"
prefix, followed by a zero or a one, a period, and then the remainder of
the mantissa in hexadecimal form, with digits from 0-9, a-f, or A-F. The
start of the exponent is denoted by a "p", which is then followed by an
optional plus or minus sign and then digits from 0 to 9. For example:
::
float two = 0x1p+1; // 2.0
float pi = 0x1.921fb54442d18p+1; // 3.1415926535...
float neg = -0x1.ffep+11; // -4095.
Floating-point constants can optionally have a "f" or "F" suffix (``ispc``
currently treats all floating-point constants as having 32-bit precision,
making this suffix not currently have an effect.)
String constants in ``ispc`` are denoted by an opening double quote ``"``
followed by any character other than a newline, up to a closing double
quote. Within the string, a number of special escape sequences can be used
to specify special characters. These sequences all start with an initial
``\`` and are listed below:
.. list-table:: Escape sequences in strings
* - ``\\``
- backslash: ``\``
* - ``\"``
- double quotation mark: ``"``
* - ``\'``
- single quotation mark: ``'``
* - ``\a``
- bell (alert)
* - ``\b``
- backspace character
* - ``\f``
- formfeed character
* - ``\n``
- newline
* - ``\r``
- carriage return
* - ``\t``
- horizontal tab
* - ``\v``
- vertical tab
* - ``\`` followed by one or more digits from 0-8
- ASCII character in octal notation
* - ``\x``, followed by one or more digits from 0-9, a-f, A-F
- ASCII character in hexadecimal notation
``ispc`` doesn't support a string data type; string constants can be passed
as the first argument to the ``print()`` statement, however. ``ispc`` also
doesn't support character constants.
The following identifiers are reserved as language keywords: ``bool``,
``break``, ``case``, ``cdo``, ``cfor``, ``char``, ``cif``, ``cwhile``,
``const``, ``continue``, ``default``, ``do``, ``double``, ``else``,
``enum``, ``export``, ``extern``, ``false``, ``float``, ``for``,
``foreach``, ``foreach_active``, ``foreach_tiled``, ``foreach_unique``,
``goto``, ``if``, ``in``, ``inline``, ``int``, ``int8``, ``int16``,
``int32``, ``int64``, ``launch``, ``NULL``, ``print``, ``return``,
``signed``, ``sizeof``, ``soa``, ``static``, ``struct``, ``switch``,
``sync``, ``task``, ``true``, ``typedef``, ``uniform``, ``union``,
``unsigned``, ``varying``, ``void``, ``volatile``, ``while``.
``ispc`` defines the following operators and punctuation:
.. list-table:: Operators
* - Symbols
- Use
* - ``=``
- Assignment
* - ``+``, ``-``, \*, ``/``, ``%``
- Arithmetic operators
* - ``&``, ``|``, ``^``, ``!``, ``~``, ``&&``, ``||``, ``<<``, ``>>``
- Logical and bitwise operators
* - ``++``, ``--``
- Pre/post increment/decrement
* - ``<``, ``<=``, ``>``, ``>=``, ``==``, ``!=``
- Relational operators
* - ``*=``, ``/=``, ``+=``, ``-=``, ``<<=``, ``>>=``, ``&=``, ``|=``
- Compound assignment operators
* - ``?``, ``:``
- Selection operators
* - ``;``
- Statement separator
* - ``,``
- Expression separator
* - ``.``
- Member access
A number of tokens are used for grouping in ``ispc``:
.. list-table:: Grouping Tokens
* - ``(``, ``)``
- Parenthesization of expressions, function calls, delimiting specifiers
for control flow constructs.
* - ``[``, ``]``
- Array and short-vector indexing
* - ``{``, ``}``
- Compound statements
Types
-----
Basic Types and Type Qualifiers
-------------------------------
``ispc`` is a statically-typed language. It supports a variety of core
basic types:
* ``void``: "empty" type representing no value.
* ``bool``: boolean value; may be assigned ``true``, ``false``, or the
value of a boolean expression.
* ``int8``: 8-bit signed integer.
* ``unsigned int8``: 8-bit unsigned integer.
* ``int16``: 16-bit signed integer.
* ``unsigned int16``: 16-bit unsigned integer.
* ``int``: 32-bit signed integer; may also be specified as ``int32``.
* ``unsigned int``: 32-bit unsigned integer; may also be specified as
``unsigned int32``.
* ``float``: 32-bit floating point value
* ``int64``: 64-bit signed integer.
* ``unsigned int64``: 64-bit unsigned integer.
* ``double``: 64-bit double-precision floating point value.
There are also a few built-in types related to pointers and memory:
* ``size_t``: the maximum size of any object (structure or array)
* ``ptrdiff_t``: an integer type large enough to represent the difference
between two pointers
* ``intptr_t``: signed integer type that is large enough to represent
a pointer value
* ``uintptr_t``: unsigned integer type large enough to represent a pointer
Implicit type conversion between values of different types is done
automatically by the ``ispc`` compiler. Thus, a value of ``float`` type
can be assigned to a variable of ``int`` type directly. In binary
arithmetic expressions with mixed types, types are promoted to the "more
general" of the two types, with the following precedence:
::
double > uint64 > int64 > float > uint32 > int32 >
uint16 > int16 > uint8 > int8 > bool
In other words, adding an ``int64`` to a ``double`` causes the ``int64`` to
be converted to a ``double``, the addition to be performed, and a
``double`` value to be returned. If a different conversion behavior is
desired, then explicit type-casts can be used, where the destination type
is provided in parenthesis around the expression:
::
double foo = 1. / 3.;
int bar = (float)bar + (float)bar; // 32-bit float addition
If a ``bool`` is converted to an integer numeric type (``int``, ``int64``,
etc.), then the result is the value one if the ``bool`` has the value
``true`` and has the value zero otherwise.
Variables can be declared with the ``const`` qualifier, which prohibits
their modification.
::
const float PI = 3.1415926535;
As in C, the ``extern`` qualifier can be used to declare a function or
global variable defined in another source file, and the ``static``
qualifier can be used to define a variable or function that is only visible
in the current scope. The values of ``static`` variables declared in
functions are preserved across function calls.
"uniform" and "varying" Qualifiers
----------------------------------
If a variable has a ``uniform`` qualifier, then there is only a single
instance of that variable shared by all program instances in a gang. (In
other words, it necessarily has the same value across all of the program
instances.) In addition to requiring less storage than varying values,
``uniform`` variables lead to a number of performance advantages when they
are applicable (see `Uniform Control Flow`_, for example.) Varying
variables may be qualified with ``varying``, though doing so has no effect,
as ``varying`` is the default.
``uniform`` variables can be modified as the program executes, but only in
ways that preserve the property that they have a single value for the
entire gang. Thus, it's legal to add two uniform variables together and
assign the result to a uniform variable, but assigning a non-``uniform``
(i.e., ``varying``) value to a ``uniform`` variable is a compile-time
error.
``uniform`` variables implicitly type-convert to varying types as required:
::
uniform int x = ...;
int y = ...;
int z = x * y; // x is converted to varying for the multiply
Arrays themselves aren't uniform or varying, but the elements that they
store are:
::
float foo[10];
uniform float bar[10];
The first declaration corresponds to 10 gang-wide ``float`` values in
memory, while the second declaration corresponds to 10 ``float`` values.
Defining New Names For Types
----------------------------
The ``typedef`` keyword can be used to name types:
::
typedef int64 BigInt;
typedef float Float3[3];
Following C's syntax, the code above defines ``BigInt`` to have ``int64``
type and ``Float3`` to have ``float[3]`` type.
Also as in C, ``typedef`` doesn't create a new type: it just provides an
alternative name for an existing type. Thus, in the above example, it is
legal to pass a value with ``float[3]`` type to a function that has been
declared to take a ``Float3`` parameter.
Pointer Types
-------------
It is possible to have pointers to data in memory; pointer arithmetic,
changing values in memory with pointers, and so forth is supported as in C.
As with other basic types, pointers can be both ``uniform`` and
``varying``.
** Like other types in ``ispc``, pointers are ``varying`` by default, if an
explicit ``uniform`` qualifier isn't provided. However, the default
variability of the pointed-to type is uniform. ** This rule will be
illustrated and explained in examples below.
For example, the ``ptr`` variable in the code below is a varying pointer to
``uniform float`` values. Each program instance has a separate pointer
value and the assignment to ``*ptr`` generally represents a scatter to
memory.
::
uniform float a[] = ...;
int index = ...;
float * ptr = &a[index];
*ptr = 1;
A ``uniform`` pointer can be declared with an appropriately-placed
qualifier:
::
float f = 0;
varying float * uniform pf = &f; // uniform pointer to a varying float
*pf = 1;
The placement of the ``uniform`` qualifier to declare a ``uniform`` pointer
may be initially surprising, but it matches the form of how, for example, a
pointer that is itself ``const`` (as opposed to pointing to a ``const``
type) is declared in C. (Reading the declaration from right to left gives
its meaning: a uniform pointer to a float that is varying.)
A subtlety comes in in cases like the where a uniform pointer points to a
varying datatype. In this case, each program instance accesses a distinct
location in memory (because the underlying varying datatype is itself laid
out with a separate location in memory for each program instance.)
::
float a;
varying float * uniform pa = &a;
*pa = programIndex; // same as (a = programIndex)
Also as in C, arrays are silently converted into pointers:
::
float a[10] = { ... };
varying float * uniform pa = a; // pointer to first element of a
varying float * uniform pb = a + 5; // pointer to 5th element of a
Any pointer type can be explicitly typecast to another pointer type, as
long as the source type isn't a ``varying`` pointer when the destination
type is a ``uniform`` pointer.
::
float *pa = ...;
int *pb = (int *)pa; // legal, but beware
Like other types, ``uniform`` pointers can be typecast to be ``varying``
pointers, however.
Any pointer type can be assigned to a ``void`` pointer without a type cast:
::
float foo(void *);
int *bar = ...;
foo(bar);
There is a special ``NULL`` value that corresponds to a NULL pointer. As a
special case, the integer value zero can be implicitly converted to a NULL
pointer and pointers are implicitly converted to boolean values in
conditional expressions.
::
void foo(float *ptr) {
if (ptr != 0) { // or, (ptr != NULL), or just (ptr)
...
It is legal to explicitly type-cast a pointer type to an integer type and
back from an integer type to a pointer type. Note that this conversion
isn't performed implicitly, for example for function calls.
Function Pointer Types
----------------------
Pointers to functions can also be taken and used as in C and C++.
The syntax for declaring function pointer types is the same as in those
languages; it's generally easiest to use a ``typedef`` to help:
::
int inc(int v) { return v+1; }
int dec(int v) { return v-1; }
typedef int (*FPType)(int);
FPType fptr = inc; // vs. int (*fptr)(int) = inc;
Given a function pointer, the function it points to can be called:
::
int x = fptr(1);
It's not necessary to take the address of a function to assign it to a
function pointer or to dereference it to call the function.
As with pointers to data in ``ispc``, function pointers can be either
``uniform`` or ``varying``. A call through a ``uniform`` causes all of the
running program instances in the gang to call into the target function; the
implications of a call through a ``varying`` function pointer are discussed
in the section `Gang Convergence Guarantees`_.
Reference Types
---------------
``ispc`` also provides reference types (like C++ references) that can be
used for passing values to functions by reference, allowing functions can
return multiple results or modify existing variables.
::
void increment(float &f) {
++f;
}
As in C++, once a reference is bound to a variable, it can't be rebound
to a different variable:
::
float a = ..., b = ...;
float &r = a; // makes r refer to a
r = b; // assigns b to a, doesn't make r refer to b
An important limitation with references in ``ispc`` is that references
can't be bound to varying lvalues; doing so causes a compile-time error to
be issued. This situation is illustrated in the following code, where
``vptr`` is a ``varying`` pointer type (in other words, there each program
instance in the gang has its own unique pointer value)
::
uniform float * uniform uptr = ...;
float &ra = *uptr; // ok
uniform float * varying vptr = ...;
float &rb = *vptr; // ERROR: *ptr is a varying lvalue type
(The rationale for this limitation is that references must be represented
as either a uniform pointer or a varying pointer internally. While
choosing a varying pointer would provide maximum flexibility and eliminate
this restriction, it would reduce performance in the common case where a
uniform pointer is all that's needed. As a work-around, a varying pointer
can be used in cases where a varying lvalue reference would be desired.)
Enumeration Types
-----------------
It is possible to define user-defined enumeration types in ``ispc`` with
the ``enum`` keyword, which is followed by an optional enumeration type name
and then a brace-delimited list of enumerators with optional values:
::
enum Color { RED, GREEN, BLUE };
enum Flags {
UNINITIALIZED = 0,
INITIALIZED = 2,
CACHED = 4
};
Each ``enum`` declaration defines a new type; an attempt to implicitly
convert between enumerations of different types gives a compile-time error,
but enumerations of different types can be explicitly cast to one other.
::
Color c = (Color)CACHED;
Enumerators are implicitly converted to integer types, however, so they can
be directly passed to routines that take integer parameters and can be used
in expressions including integers, for example. However, the integer
result of such an expression must be explicitly cast back to the enumerant
type if it to be assigned to a variable with the enumerant type.
::
Color c = RED;
int nextColor = c+1;
c = (Color)nextColor;
In this particular case, the explicit cast could be avoided using an
increment operator.
::
Color c = RED;
++c; // c == GREEN now
Short Vector Types
------------------
``ispc`` supports a parameterized type to define short vectors. These
short vectors can only be used with basic types like ``float`` and ``int``;
they can't be applied to arrays or structures. Note: ``ispc`` does *not*
use these short vectors to facilitate program vectorization; they are
purely a syntactic convenience. Using them or writing the corresponding
code without them shouldn't lead to any noticeable performance differences
between the two approaches.
Syntax similar to C++ templates is used to declare these types:
::
float<3> foo; // vector of three floats
double<6> bar;
The length of these vectors can be arbitrarily long, though the expected
usage model is relatively short vectors.
You can use ``typedef`` to create types that don't carry around
the brackets around the vector length:
::
typedef float<3> float3;
``ispc`` doesn't support templates in general. In particular,
not only must the vector length be a compile-time constant, but it's
also not possible to write functions that are parameterized by vector
length.
::
uniform int i = foo();
// ERROR: length must be compile-time constant
float<i> vec;
// ERROR: can't write functions parameterized by vector length
float<N> func(float<N> val);
Arithmetic on these short vector types works as one would expect; the
operation is applied component-wise to the values in the vector. Here is a
short example:
::
float<3> func(float<3> a, float<3> b) {
a += b; // add individual elements of a and b
a *= 2.; // multiply all elements of a by 2
bool<3> test = a < b; // component-wise comparison
return test ? a : b; // return each minimum component
}
As shown by the above code, scalar types automatically convert to
corresponding vector types when used in vector expressions. In this
example, the constant ``2.`` above is converted to a three-vector of 2s for
the multiply in the second line of the function implementation.
Type conversion between other short vector types also works as one would
expect, though the two vector types must have the same length:
::
float<3> foo = ...;
int<3> bar = foo; // ok, cast elements to ints
int<4> bat = foo; // ERROR: different vector lengths
float<4> bing = foo; // ERROR: different vector lengths
For convenience, short vectors can be initialized with a list of individual
element values:
::
float x = ..., y = ..., z = ...;
float<3> pos = { x, y, z };
There are two mechanisms to access the individual elements of these short
vector data types. The first is with the array indexing operator:
::
float<4> foo;
for (uniform int i = 0; i < 4; ++i)
foo[i] = i;
``ispc`` also provides a specialized mechanism for naming and accessing
the first few elements of short vectors based on an overloading of
the structure member access operator. The syntax is similar to that used
in HLSL, for example.
::
float<3> position;
position.x = ...;
position.y = ...;
position.z = ...;
More specifically, the first element of any short vector type can be
accessed with ``.x`` or ``.r``, the second with ``.y`` or ``.g``, the third
with ``.z`` or ``.b``, and the fourth with ``.w`` or ``.a``. Just like
using the array indexing operator with an index that is greater than the
vector size, accessing an element that is beyond the vector's size is
undefined behavior and may cause your program to crash.
It is also possible to construct new short vectors from other short vector
values using this syntax, extended for "swizzling". For example,
::
float<3> position = ...;
float<3> new_pos = position.zyx; // reverse order of components
float<2> pos_2d = position.xy;
Though a single element can be assigned to, as in the examples above, it is
not currently possible to use swizzles on the left-hand side of assignment
expressions:
::
int8<2> foo = ...;
int8<2> bar = ...;
foo.yz = bar; // Error: can't assign to left-hand side of expression
Array Types
-----------
Arrays of any type can be declared just as in C and C++:
::
float a[10];
uniform int * varying b[20];
Multidimensional arrays can be specified as arrays of arrays; the following
declares an array of 5 arrays of 15 floats.
::
float a[5][15];
The size of arrays must be a compile-time constant, though array size can
be determined from array initializer lists; see the following section,
`Declarations and Initializers`_, for details. One exception to this is
that functions can be declared to take "unsized arrays" as parameters:
::
void foo(float array[], int length);
Finally, the name of an array will be automatically implicitly converted to
a uniform pointer to the array type if needed:
::
int a[10];
int * uniform ap = a;
Struct Types
------------
Aggregate data structures can be built using ``struct``.
::
struct Foo {
float time;
int flags[10];
};
As in C++, after a ``struct`` is declared, an instance can be created using
the ``struct``'s name:
::
Foo f;
Alternatively, ``struct`` can be used before the structure name:
::
struct Foo f;
Members in a structure declaration may each have ``uniform`` or ``varying``
qualifiers, or may have no rate qualifier, in which case their variability
is initially "unbound".
::
struct Bar {
uniform int a;
varying int b;
int c;
};
In the declaration above, the variability of ``c`` is unbound. The
variability of struct members that are unbound is resolved when a struct is
defined; if the ``struct`` is ``uniform``, then unbound members are
``uniform``, and if the ``struct`` is ``varying``, then unbound members are
varying.
::
Bar vb;
uniform Bar ub;
Here, ``b`` is a ``varying Bar`` (since ``varying`` is the default
variability). If ``Bar`` is defined as above, then ``vb.a`` is still a
``uniform int``, since its varaibility was bound in the original
declaration of the ``Bar`` type. Similarly, ``vb.b`` is ``varying``. The
variability of ``vb.c`` is ``varying``, since ``vb`` is ``varying``.
(Similarly, ``ub.a`` is ``uniform``, ``ub.b`` is ``varying``, and ``ub.c``
is ``uniform``.)
In most cases, it's worthwhile to declare ``struct`` members with unbound
variability so that all have the same variability for both ``uniform`` and
``varying`` structs. In particular, if a ``struct`` has a member with
bound ``uniform`` type, it's not possible to index into an array of the
struct type with a ``varying`` index. Consider the following example:
::
struct Foo { uniform int a; };
uniform Foo f[...] = ...;
int index = ...;
Foo fv = f[index]; // ERROR
Here, the ``Foo`` type has a member with bound ``uniform`` variability.
Because ``index`` has a different value for each program instance in the
above code, the value of ``f[index]`` needs to be able to store a different
value of ``Foo::a`` for each program instance. However, a ``varying Foo``
still has only a single ``a`` member, since ``a`` was declared with
``uniform`` variability in the declaration of ``Foo``. Therefore, the
indexing operation in the last line results in an error.
Operators Overloading
---------------------
ISPC has limited support for overloaded operators for ``struct`` types. Only
binary operators are supported currently, namely they are: ``*, /, %, +, -, >>
and <<``. Operators overloading support is similar to the one in C++ language.
To overload an operator for ``struct S``, you need to declare and implement a
function using keyword ``operator``, which accepts two parameters of type
``struct S`` or ``struct S&`` and returns either of these types. For example:
::
struct S { float re, im;};
struct S operator*(struct S a, struct S b) {
struct S result;
result.re = a.re * b.re - a.im * b.im;
result.im = a.re * b.im + a.im * b.re;
return result;
}
void foo(struct S a, struct S b) {
struct S mul = a*b;
print("a.re: %\na.im: %\n", a.re, a.im);
print("b.re: %\nb.im: %\n", b.re, b.im);
print("mul.re: %\nmul.im: %\n", mul.re, mul.im);
}
Structure of Array Types
------------------------
If data can be laid out in memory so that the executing program instances
access it via loads and stores of contiguous sections of memory, overall
performance can be improved noticably. One way to improve this memory
access coherence is to lay out structures in "structure of arrays" (SOA)
format in memory; the benefits from SOA layout are discussed in more detail
in the `Use "Structure of Arrays" Layout When Possible`_ section in the
ispc Performance Guide.
.. _Use "Structure of Arrays" Layout When Possible: perfguide.html#use-structure-of-arrays-layout-when-possible
``ispc`` provides two key language-level capabilities for laying out and
accessing data in SOA format:
* An ``soa`` keyword that transforms a regular ``struct`` into an SOA version
of the struct.
* Array indexing syntax for SOA arrays that transparently handles SOA
indexing.
As an example, consider a simple struct declaration:
::
struct Point { float x, y, z; };
With the ``soa`` rate qualifier, an array of SOA variants of this structure
can be declared:
::
soa<8> Point pts[...];
The in-memory layout of the ``Point`` instances has had the SOA transformation
applied, such that there are 8 ``x`` values in memory followed by 8 ``y``
values, and so forth. Here is the effective declaration of ``soa<8>
Point``:
::
struct { uniform float x[8], y[8], z[8]; };
Given an array of SOA data, array indexing (and pointer arithmetic) is done
so that the appropriate values from the SOA array are accessed. For
example, given:
::
soa<8> Point pts[...];
uniform float x = pts[10].x;
The generated code effectively accesses the second 8-wide SOA structure and
then loads the third ``x`` value from it. In general, one can write the
same code to access arrays of SOA elements as one would write to access
them in AOS layout.
Note that it directly follows from SOA layout that the layout of a single
element of the array isn't contiguous in memory--``pts[1].x`` and
``pts[1].y`` are separated by 7 ``float`` values in the above example.
There are a few limitations to the current implementation of SOA types in
``ispc``; these may be relaxed in future releases:
* It's illegal to typecast to ``soa`` data to ``void`` pointers.
* Reference types are illegal in SOA structures
* All members of SOA structures must have no rate qualifiers--specifically,
it's illegal to have an explicitly-qualified ``uniform`` or ``varying``
member of a structure that has ``soa`` applied to it.
Declarations and Initializers
-----------------------------
Variables are declared and assigned just as in C:
::
float foo = 0, bar[5];
float bat = func(foo);
More complex declarations are also possible:
::
void (*fptr_array[16])(int, int);
Here, ``fptr_array`` is an array of 16 pointers to functions that have
``void`` return type and take two ``int`` parameters.
If a variable is declared without an initializer expression, then its value
is undefined until a value is assigned to it. Reading an undefined
variable is undefined behavior.
Any variable that is declared at file scope (i.e. outside a function) is a
global variable. If a global variable is qualified with the ``static``
keyword, then its only visible within the compilation unit in which it was
defined. As in C/C++, a variable with a ``static`` qualifier inside a
functions maintains its value across function invocations.
As in C++, variables don't need to be declared at the start of a basic
block:
::
int foo = ...;
if (foo < 2) { ... }
int bar = ...;
Variables can also be declared in ``for`` statement initializers:
::
for (int i = 0; ...)
Arrays can be initialized with individual element values in braces:
::
int bar[2][4] = { { 1, 2, 3, 4 }, { 5, 6, 7, 8 } };
An array with an initializer expression can be declared with some or all of
its dimensions unspecified. In this case, the "shape" of the initializer
expression is used to determine the array dimensions:
::
// This corresponds to bar[2][4], due to the initializer expression
int bar[][] = { { 1, 2, 3, 4 }, { 5, 6, 7, 8 } };
Structures can also be initialized by providing element values in braces:
::
struct Color { float r, g, b; };
....
Color d = { 0.5, .75, 1.0 }; // r = 0.5, ...
Arrays of structures and arrays inside structures can be initialized with
the expected syntax:
::
struct Foo { int x; float bar[3]; };
Foo fa[2] = { { 1, { 2, 3, 4 } }, { 10, { 20, 30, 40 } } };
// now, fa[1].bar[2] == 30, and so forth
Expressions
-----------
All of the operators from C that you'd expect for writing expressions are
present. Rather than enumerating all of them, here is a short summary of
the range of them available in action.
::
unsigned int i = 0x1234feed;
unsigned int j = (i << 3) ^ ~(i - 3);
i += j / 6;
float f = 1.234e+23;
float g = j * f / (2.f * i);
double h = (g < 2) ? f : g/5;
Structure member access and array indexing also work as in C.
::
struct Foo { float f[5]; int i; };
Foo foo = { { 1,2,3,4,5 }, 2 };
return foo.f[4] - foo.i;
The address-of operator, pointer dereference operator, and pointer member
operator also work as expected.
::
struct Foo { float a, b, c; };
Foo f;
Foo * uniform fp = &f;
(*fp).a = 0;
fp->b = 1;
As in C and C++, evaluation of the ``||`` and ``&&`` logical operators as
well as the selection operator ``? :`` is "short-circuited"; the right hand
side won't be evaluated if the value from the left-hand side determines the
logical operator's value. For example, in the following code,
``array[index]`` won't be evaluated for values of ``index`` that are
greater than or equal to ``NUM_ITEMS``.
::
if (index < NUM_ITEMS && array[index] > 0) {
// ...
}
Short-circuiting may impose some overhead in the generated code; for cases
where short-circuiting is undesirable due to performance impact, see
the section `Logical and Selection Operations`_, which introduces helper
functions in the standard library that provide these operations without
short-circuiting.
Dynamic Memory Allocation
-------------------------
``ispc`` programs can dynamically allocate (and free) memory, using syntax
based on C++'s ``new`` and ``delete`` operators:
::
int count = ...;
int *ptr = new int[count];
// use ptr...
delete[] ptr;
In the above code, each program instance allocates its own ``count`` sized
array of ``uniform int`` values, uses that memory, and then deallocates
that memory. Uses of ``new`` and ``delete`` in ``ispc`` programs are
implemented as calls to C library's aligned memory allocation routines,
which are platform dependent (``posix_memalign()`` and ``free()`` on Linux
and Mac and ``_aligned_malloc()`` and ``_aligned_free()`` on Windows). So it's
advised to pair ISPC's ``new`` and ``delete`` with each other, but not with
C/C++ memory management functions.
Note that the rules for ``uniform`` and ``varying`` for ``new`` are
analogous to the corresponding rules for pointers (as described in
`Pointer Types`_). Specifically, if a specific rate qualifier isn't
provided with the ``new`` expression, then the default is that a "varying"
``new`` is performed, where each program instance performs a unique
allocation. The allocated type, in turn, is by default ``uniform``.
After a pointer has been deleted, it is illegal to access the memory it
points to. However, that deletion happens on a per-program-instance basis.
In other words, consider the following code:
::
int *ptr = new int[count];
// use ptr
if (count > 1000)
delete[] ptr;
// ...
Here, the program instances where ``count`` is greater than 1000 have
deleted the dynamically allocated memory pointed to by ``ptr``, but the
other program instances have not. As such, it's illegal for the former set
of program instances to access ``*ptr``, but it's perfectly fine for the
latter set to continue to use the memory ``ptr`` points to. Note that it
is illegal to delete a pointer value returned by ``new`` more than one
time.
Sometimes, it's useful to be able to do a single allocation for the entire
gang of program instances. A ``new`` statement can be qualified with
``uniform`` to indicate a single memory allocation:
::
float * uniform ptr = uniform new float[10];
While a regular call to ``new`` returns a ``varying`` pointer (i.e. a
distinct pointer to separately-allocated memory for each program instance),
a ``uniform new`` performs a single allocation and returns a ``uniform``
pointer. Recall that with a ``uniform`` ``new``, the default variability
of the allocated type is ``varying``, so the above code is allocating an
array of ten ``varying float`` values.
When using ``uniform new``, it's important to be aware of a subtlety; if
the returned pointer is stored in a varying pointer variable (as may be
appropriate and useful for the particular program being written), then the
varying pointer may inadvertently be passed to a subsequent ``delete``
statement, which is an error: effectively
::
varying float * ptr = uniform new float[10];
// use ptr...
delete ptr; // ERROR: varying pointer is deleted
In this case, ``ptr`` will be deleted multiple times, once for each
executing program instance, which is an error (unless it happens that only
a single program instance is active in the above code.)
When using ``new`` statements, it's important to make an appropriate choice
of ``uniform`` or ``varying``, for both the ``new`` operator itself as well
as the type of data being allocated, based on the program's needs.
Consider the following four memory allocations:
::
uniform float * uniform p1 = uniform new uniform float[10];
float * uniform p2 = uniform new float[10];
float * p3 = new float[10];
varying float * p4 = new varying float[10];
Assuming that a ``float`` is 4 bytes in memory and if the gang size is 8
program instances, then the first allocation represents a single allocation
of 10 ``uniform float`` values (40 bytes), the second is a single
allocation of 10 ``varying float`` values (8*4*10 = 320 bytes), the third
is 8 allocations of 10 ``uniform float`` values (8 allocations of 40 bytes
each), and the last performs 8 allocations of 320 bytes each.
Note in particular that varying allocations of varying data types are rarely
desirable in practice. In that case, each program instance is performing a
separate allocation of ``varying float`` memory. In this case, it's likely
that the program instances will only access a single element of each
``varying float``, which is wasteful. (This in turn is partially why the
allocated type is uniform by default with both pointers and ``new``
statements.)
Although ``ispc`` doesn't support constructors or destructors like C++, it
is possible to provide initializer values with ``new`` statements:
::
struct Point { float x, y, z; };
Point *pptr = new Point(10, 20, 30);
Here for example, the "x" element of the returned ``Point`` is initialized
to have the value 10 and so forth. In general, the rules for how
initializer values provided in ``new`` statements are used to initialize
complex data types follow the same rules as initializers for variables
described in `Declarations and Initializers`_.
Control Flow
------------
``ispc`` supports most of C's control flow constructs, including ``if``,
``switch``, ``for``, ``while``, ``do``. It has limited support for
``goto``, detailed below. It also supports variants of C's control flow
constructs that provide hints about the expected runtime coherence of the
control flow at that statement. It also provides parallel looping
constructs, ``foreach`` and ``foreach_tiled``, all of which will be
detailed in this section.
Conditional Statements: "if"
----------------------------
The ``if`` statement behaves precisely as in C; the code in the "true"
block only executes if the condition evaluates to ``true``, and if an
optional ``else`` clause is provided, the code in the "else" block only
executes if the condition is false.
::
float x = ..., y = ...;
if (x < 0.)
y = -y;
else
x *= 2.;
Conditional Statements: "switch"
--------------------------------
The ``switch`` conditional statement is also available, again with the same
behavior as in C; the expression used in the ``switch`` must be of integer
type (but it can be uniform or varying). As in C, if there is no ``break``
statement at the end of the code for a given case, execution "falls
through" to the following case. These features are demonstrated in the
code below.
::
int x = ...;
switch (x) {
case 0:
case 1:
foo(x);
/* fall through */
case 5:
x = 0;
break;
default:
x *= x;
}
Iteration Statements
--------------------
In addition to the standard iteration statements ``for``, ``while``, and
``do``, inherited from C/C++, ``ispc`` provides a number of additional
specialized ways to iterate over data.
Basic Iteration Statements: "for", "while", and "do"
----------------------------------------------------
``ispc`` supports ``for``, ``while``, and ``do`` loops, with the same
specification as in C. As in C++, variables can be declared in the ``for``
statement itself:
::
for (uniform int i = 0; i < 10; ++i) {
// loop body
}
// i is now no longer in scope
You can use ``break`` and ``continue`` statements in ``for``, ``while``,
and ``do`` loops; ``break`` breaks out of the current enclosing loop, while
``continue`` has the effect of skipping the remainder of the loop body and
jumping to the loop step.
Note that all of these looping constructs have the effect of executing
independently for each of the program instances in a gang; for example, if
one of them executes a ``continue`` statement, other program instances
executing code in the loop body that didn't execute the ``continue`` will
be unaffected by it.
Iteration over active program instances: "foreach_active"
---------------------------------------------------------
The ``foreach_active`` construct specifies a loop that serializes over the
active program instances: the loop body executes once for each active
program instance, and with only that program instance executing.
As an example of the use of this construct, consider an application where
each program instance independently computes an offset into a shared array
that is being updated:
::
uniform float array[...] = { ... };
int index = ...;
++array[index];
If more than one active program instance computes the same value for
``index``, the above code has undefined behavior (see the section `Data
Races Within a Gang`_ for details.) The increment of ``array[index]``
could instead be written inside a ``foreach_active`` statement:
::
foreach_active (i) {
++array[index];
}
The variable name provided in parenthesis after the ``foreach_active``
keyword (here, ``index``), causes a ``const uniform int64`` local variable
of that name to be declared, where the variable takes the ``programIndex``
value of the program instance executing at each loop iteration.
In the code above, because only one program instance is executing at a time
when the loop body executes, the update to ``array`` is well-defined.
Note that for this particular example, the "local atomic" operations in
the standard library could be used instead to safely update ``array``.
However, local atomics functions aren't always available or appropriate for
more complex cases.)
``continue`` statements may be used inside ``foreach_active`` loops, though
``break`` and ``return`` are prohibited. The order in which the active
program instances are processed in the loop is not defined.
See the `Using "foreach_active" Effectively`_ Section in the ``ispc``
Performance Guide for more details about ``foreach_active``.
.. _Using "foreach_active" Effectively: perfguide.html#using-foreach-active-effectively
Iteration over unique elements: "foreach_unique"
------------------------------------------------
It can be useful to iterate over the elements of a varying variable,
processing the subsets of them that have the same value together. For
example, consider a varying variable ``x`` that has the values ``{1, 2, 2,
1, 1, 0, 0, 0}``, where the program is running on a target with a gang size
of 8 program instances. Here, ``x`` has three unique values across the
program instances: ``0``, ``1``, and ``2``.
The ``foreach_unique`` looping construct allows us to iterate over these
unique values. In the code below, the ``foreach_unique`` loop body
executes once for each of the three unique values, with execution mask set
to match the program instances where the varying value matches the current
unique value being processed.
::
int x = ...; // assume {1, 2, 2, 1, 1, 0, 0, 0}
foreach_unique (val in x) {
extern void func(uniform int v);
func(val);
}
In the above, ``func()`` will be called three times, once with value 0,
once with value 1, and once with value 2. When it is called for value 0,
only the last three program instances will be executing, and so forth. The
order in which the loop executes for the unique values isn't defined.
The varying expression that provides the values to be iterated over is only
evaluated once, and it must be of an atomic type (``float``, ``int``,
etc.), an ``enum`` type, or a pointer type. The iteration variable ``val``
is a variable of ``const uniform`` type of the iteration type; it can't be
modified within the loop. Finally, ``break`` and ``return`` statements are
illegal within the loop body, but ``continue`` statements are allowed.
Parallel Iteration Statements: "foreach" and "foreach_tiled"
------------------------------------------------------------
The ``foreach`` and ``foreach_tiled`` constructs specify loops over a
possibly multi-dimensional domain of integer ranges. Their role goes
beyond "syntactic sugar"; they provide one of the two key ways of
expressing parallel computation in ``ispc``.
In general, a ``foreach`` or ``foreach_tiled`` statement takes one or more
dimension specifiers separated by commas, where each dimension is specified
by ``identifier = start ... end``, where ``start`` is a signed integer
value less than or equal to ``end``, specifying iteration over all integer
values from ``start`` up to and including ``end-1``. An arbitrary number
of iteration dimensions may be specified, with each one spanning a
different range of values. Within the ``foreach`` loop, the given
identifiers are available as ``const varying int32`` variables. The
execution mask starts out "all on" at the start of each ``foreach`` loop
iteration, but may be changed by control flow constructs within the loop.
It is illegal to have a ``break`` statement or a ``return`` statement
within a ``foreach`` loop; a compile-time error will be issued in this
case. (It is legal to have a ``break`` in a regular ``for`` loop that's
nested inside a ``foreach`` loop.) ``continue`` statements are legal in
``foreach`` loops; they have the same effect as in regular ``for`` loops:
a program instances that executes a ``continue`` statement effectively
skips over the rest of the loop body for the current iteration.
It is also currently illegal to have nested ``foreach`` statements; this
limitation will be removed in a future release of ``ispc``.
As a specific example, consider the following ``foreach`` statement:
::
foreach (j = 0 ... height, i = 0 ... width) {
// loop body--process data element (i,j)
}
It specifies a loop over a 2D domain, where the ``j`` variable goes from 0
to ``height-1`` and ``i`` goes from 0 to ``width-1``. Within the loop, the
variables ``i`` and ``j`` are available and initialized accordingly.
``foreach`` loops actually cause the given iteration domain to be
automatically mapped to the program instances in the gang, so that all of
the data can be processed, in gang-sized chunks. As a specific example,
consider a simple ``foreach`` loop like the following, on a target where
the gang size is 8:
::
foreach (i = 0 ... 16) {
// perform computation on element i
}
One possible valid execution path of this loop would be for the program
counter the step through the statements of this loop just ``16/8==2``
times; the first time through, with the ``varying int32`` variable ``i``
having the values (0,1,2,3,4,5,6,7) over the program instances, and the
second time through, having the values (8,9,10,11,12,13,14,15), thus
mapping the available program instances to all of the data by the end of
the loop's execution.
In general, however, you shouldn't make any assumptions about the order in
which elements of the iteration domain will be processed by a ``foreach``
loop. For example, the following code exhibits undefined behavior:
::
uniform float a[10][100];
foreach (i = 0 ... 10, j = 0 ... 100) {
if (i == 0)
a[i][j] = j;
else
// Error: can't assume that a[i-1][j] has been set yet
a[i][j] = a[i-1][j];
The ``foreach`` statement generally subdivides the iteration domain by
selecting sets of contiguous elements in the inner-most dimension of the
iteration domain. This decomposition approach generally leads to coherent
memory reads and writes, but may lead to worse control flow coherence than
other decompositions.
Therefore, ``foreach_tiled`` decomposes the iteration domain in a way that
tries to map locations in the domain to program instances in a way that is
compact across all of the dimensions. For example, on a target with an
8-wide gang size, the following ``foreach_tiled`` statement might process
the iteration domain in chunks of 2 elements in ``j`` and 4 elements in
``i`` each time. (The trade-offs between these two constructs are
discussed in more detail in the `ispc Performance Guide`_.)
.. _ispc Performance Guide: perfguide.html#improving-control-flow-coherence-with-foreach-tiled
::
foreach_tiled (j = 0 ... height, i = 0 ... width) {
// loop body--process data element (i,j)
}
Parallel Iteration with "programIndex" and "programCount"
---------------------------------------------------------
In addition to ``foreach`` and ``foreach_tiled``, ``ispc`` provides a
lower-level mechanism for mapping SPMD program instances to data to operate
on via the built-in ``programIndex`` and ``programCount`` variables.
``programIndex`` gives the index of the SIMD-lane being used for running
each program instance. (In other words, it's a varying integer value that
has value zero for the first program instance, and so forth.) The
``programCount`` builtin gives the total number of instances in the gang.
Together, these can be used to uniquely map executing program instances to
input data. [#]_
.. [#] ``programIndex`` is analogous to ``get_global_id()`` in OpenCL* and
``threadIdx`` in CUDA*.
As a specific example, consider an ``ispc`` function that needs to perform
some computation on an array of data.
::
for (uniform int i = 0; i < count; i += programCount) {
float d = data[i + programIndex];
float r = ....
result[i + programIndex] = r;
}
Here, we've written a loop that explicitly loops over the data in chunks of
``programCount`` elements. In each loop iteration, the running program
instances effectively collude amongst themselves using ``programIndex`` to
determine which elements to work on in a way that ensures that all of the
data elements will be processed. In this particular case, a ``foreach``
loop would be preferable, as ``foreach`` naturally handles the case where
``programCount`` doesn't evenly divide the number of elements to be
processed, while the loop above assumes that case implicitly.
Unstructured Control Flow: "goto"
---------------------------------
``goto`` statements are allowed in ``ispc`` programs under limited
circumstances; specifically, only when the compiler can determine that if
any program instance executes a ``goto`` statement, then all of the program
instances will be running at that statement, such that all will follow the
``goto``.
Put another way: it's illegal for there to be "varying" control flow
statements in scopes that enclose a ``goto`` statement. An error is issued
if a ``goto`` is used in this situation.
The syntax for adding labels to ``ispc`` programs and jumping to them with
``goto`` is the same as in C. The following code shows a ``goto`` based
equivalent of a ``for`` loop where the induction variable ``i`` goes from
zero to ten.
::
uniform int i = 0;
check:
if (i > 10)
goto done;
// loop body
++i;
goto check;
done:
// ...
"Coherent" Control Flow Statements: "cif" and Friends
-----------------------------------------------------
``ispc`` provides variants of all of the standard control flow constructs
that allow you to supply a hint that control flow is expected to be
coherent at a particular point in the program's execution. These
mechanisms provide the compiler a hint that it's worth emitting extra code
to check to see if the control flow is in fact coherent at run-time, in
which case a simpler code path can often be executed.
The first of these statements is ``cif``, indicating an ``if`` statement
that is expected to be coherent. The usage of ``cif`` in code is just the
same as ``if``:
::
cif (x < y) {
...
} else {
...
}
``cif`` provides a hint to the compiler that you expect that most of the
executing SPMD programs will all have the same result for the ``if``
condition.
Along similar lines, ``cfor``, ``cdo``, and ``cwhile`` check to see if all
program instances are running at the start of each loop iteration; if so,
they can run a specialized code path that has been optimized for the "all
on" execution mask case.
Functions and Function Calls
----------------------------
Like C, functions must be declared in ``ispc`` before they are called,
though a forward declaration can be used before the actual function
definition. Also like C, arrays are passed to functions by reference.
Recursive function calls are legal:
::
int gcd(int a, int b) {
if (a == 0)
return b;
else
return gcd(b%a, a);
}
Functions can be declared with a number of qualifiers that affect their
visibility and capabilities. As in C/C++, functions have global visibility
by default. If a function is declared with a ``static`` qualifier, then it
is only visible in the file in which it was declared.
::
static void lerp(float t, float a, float b) {
return (1.-t)*a + t*b;
}
Any function that can be launched with the ``launch`` construct in ``ispc``
must have a ``task`` qualifier; see `Task Parallelism: "launch" and "sync"
Statements`_ for more discussion of launching tasks in ``ispc``.
A function can also be given the ``unmasked`` qualifier; this qualifier
indicates that all program instances should be made active at the start of
the function execution (or, equivalently, that the current execution mask
shouldn't be passed to the function from the function call site.) If it is
known that a function will always be called when all program instances are
executing, adding this qualifier can slightly improve performance. See the
Section `Re-establishing The Execution Mask`_ for more discussion of
``unmasked`` program code.
Functions that are intended to be called from C/C++ application code must
have the ``export`` qualifier. This causes them to have regular C linkage
and to have their declarations included in header files, if the ``ispc``
compiler is directed to generated a C/C++ header file for the file it
compiled.
::
export uniform float inc(uniform float v) {
return v+1;
}
Finally, any function defined with an ``inline`` qualifier will always be
inlined by ``ispc``; ``inline`` is not a hint, but forces inlining. The
compiler will opportunistically inline short functions depending on their
complexity, but any function that should always be inlined should have the
``inline`` qualifier.
Function Overloading
--------------------
Functions can be overloaded by parameter type. Given multiple definitions
of a function, ``ispc`` uses the following model to choose the best function:
each conversion of two types has its cost. ``ispc`` tries to find conversion
with the smallest cost. When ``ispc`` can't find any conversion it means that
this function is not suitable. Then ``ispc`` sums costs for all arguments and
chooses the function with the smallest final cost. If the chosen function
has some arguments which costs are bigger than their costs in other function
this treats as ambiguous.
Costs of type conversions placed from small to big:
1. Parameter types match exactly.
2. Function parameter type is reference and parameters match when any reference-type parameter are considered equivalent to their underlying type.
3. Function parameter type is const-reference and parameters match when any reference-type parameter are considered equivalent to their underlying type ignoring const attributes.
4. Parameters match exactly, except constant attributes. [NO CONSTANT ATTRIBUTES LATER]
5. Parameters match exactly, except reference attributes. [NO REFERENCES ATTRIBUTES LATER]
6. Parameters match with only type conversions that don't risk losing any information (for example, converting an int16 value to an int32 parameter value.)
7. Parameters match with only promotions from uniform to varying types.
8. Parameters match using arbitrary type conversion, without changing variability from uniform to varying (e.g., int to float, float to int.)
9. Parameters match with widening and promotions from uniform to varying types. (combination of "6" and "7")
10. Parameters match using arbitrary type conversion, including also changing variability from uniform to varying.
* If function parameter type is reference and neither "2" nor "3" aren't suitable, function is not suitable
* If "10" isn't suitable, function is not suitable
Re-establishing The Execution Mask
----------------------------------
As discussed in `Functions and Function Calls`_, a function that is
declared with an ``unmasked`` qualifier starts execution with all program
instances running, regardless of the execution mask at the site of the
function call. A block of statements can also be enclosed with
``unmasked`` to have the same effect within a function:
::
int a = ..., b = ...;
if (a < b) {
// only program instances where a < b are executing here
unmasked {
// now all program instances are executing
}
// and again only the a < b instances
}
``unmasked`` can be useful in cases where the programmer wants to "change
the axis of parallelism" or use nested parallelism, as shown in the
following code:
::
uniform WorkItem items[...] = ...;
foreach (itemNum = 0 ... numItems) {
// do computation on items[itemNum] to determine if it needs
// further processing...
if (/* itemNum needs processing */) {
foreach_active (i) {
unmasked {
uniform int uItemNum = extract(itemNum, i);
// apply entire gang of program instances to uItemNum
}
}
}
}
The general idea is that we are first using SPMD parallelism to determine
which of the items requires further processing, checking a gang's worth of
them concurrently inside the ``foreach`` loop. Assuming that only a subset
of them needs further processing, would be wasteful to do this work within
the ``foreach`` loop in the same program instance that made the initial
determination of whether more work as needed; in this case, all of the
program instances corresponding to items that didn't need further
processing would be inactive, with corresponding unused computational
capability in the system.
In the above code, this issue is avoided by working on each of the items
requiring more processing in turn with ``foreach_active`` and then using
``unmasked`` to re-establish execution of all of the program instances.
The entire gang can in turn be applied to the computation to be done for
each ``items[itemNum]``.
The ``unmasked`` statement should be used with care; it can lead to a
number of surprising cases of undefined program behavior. For example,
consider the following code:
::
void func(float);
float a = ...;
float b;
if (a < 0) {
b = 0;
unmasked {
if (b == 0)
func(a);
}
}
The variable ``a`` is initialized to some value and ``b`` is declared but
not initialized, and thus has an undefined value. Within the ``if`` test,
we have assigned zero to ``b``, though only for the program instances
currently executing--i.e. those where ``a < 0``. After re-establishing the
executing mask with ``unmasked``, we then compare ``b`` to zero--this
comparison is well-defined (and "true") for the program instances where ``a
< 0``, but it is undefined for any program instances where that isn't the
case, since the value of ``b`` is undefined for those program instances.
Similar surprising cases can arise when writing to ``varying`` variables
within ``unmasked`` code.
As a general rule, code within an ``unmasked`` block, or a function with
the ``unmasked`` qualifier should use great care when accessing ``varying``
variables that were declared in an outer scope.
Task Parallel Execution
-----------------------
In addition to the facilities for using SPMD for parallelism across the
SIMD lanes of one processing core, ``ispc`` also provides facilities for
parallel execution across multiple cores though an asynchronous function
call mechanism via the ``launch`` keyword. A function called with
``launch`` executes as an asynchronous task, often on another core in the
system.
Task Parallelism: "launch" and "sync" Statements
------------------------------------------------
One option for combining task-parallelism with ``ispc`` is to just use
regular task parallelism in the C/C++ application code (be it through
Intel® Cilk(tm), Intel® Thread Building Blocks or another task system), and
for tasks to use ``ispc`` for SPMD parallelism across the vector lanes as
appropriate. Alternatively, ``ispc`` also has support for launching tasks
from ``ispc`` code. The approach is similar to Intel® Cilk's task launch
feature. (Check the ``examples/mandelbrot_tasks`` example to see how it is used.)
Any function that is launched as a task must be declared with the
``task`` qualifier:
::
task void func(uniform float a[], uniform int index) {
...
a[index] = ....
}
Tasks must return ``void``; a compile time error is issued if a
non-``void`` task is defined.
Given a task declaration, a task can be launched with ``launch``:
::
uniform float a[...] = ...;
launch func(a, 1);
Program execution continues asynchronously after a ``launch`` statement in
a function; thus, a function shouldn't access values written by a task it
has launched within the function without synchronization. A function can
use a ``sync`` statement to wait for all launched tasks to finish:
::
launch func(a, 1);
sync;
// now safe to use computed values in a[]...
Alternatively, any function that launches tasks has an automatically-added
implicit ``sync`` statement before it returns, so that functions that call
a function that launches tasks don't have to worry about outstanding
asynchronous computation from that function.
The task generated by a ``launch`` statement is a single gang's worth of
work. The same program instances are respectively active and inactive at
the start of the task as were active and inactive when their ``launch``
statement executed. To make all program instances in the launched gang be
active, the ``unmasked`` construct can be used (see `Re-establishing The
Execution Mask`_.)
There are two ways to write code that launches a group multiple tasks.
First, one task can be launched at a time, with parameters passed to the
task to help it determine what part of the overall computation it's
responsible for:
::
for (uniform int i = 0; i < 100; ++i)
launch func(a, i);
This code launches 100 tasks, each of which presumably does some
computation that is keyed off of given the value ``i``. In general, one
should launch many more tasks than there are processors in the system to
ensure good load-balancing, but not so many that the overhead of scheduling
and running tasks dominates the computation.
Alternatively, a number of tasks may be launched from a single ``launch``
statement. We might instead write the above example with a single
``launch`` like this:
::
launch[100] func2(a);
Where an integer value (not necessarily a compile-time constant) is
provided to the ``launch`` keyword in square brackets; this number of tasks
will be enqueued to be run asynchronously. Within each of the tasks, two
special built-in variables are available--``taskIndex``, and ``taskCount``.
The first, ``taskIndex``, ranges from zero to one minus the number of tasks
provided to ``launch``, and ``taskCount`` equals the number of launched
tasks. Thus, in this example we might use ``taskIndex`` in the
implementation of ``func2`` to determine which array element to process.
::
task void func2(uniform float a[]) {
...
a[taskIndex] = ...
}
Inside functions with the ``task`` qualifier, two additional built-in
variables are provided in addition to ``taskIndex`` and ``taskCount``:
``threadIndex`` and ``threadCount``. ``threadCount`` gives the total
number of hardware threads that have been launched by the task system.
``threadIndex`` provides an index between zero and ``threadCount-1`` that
gives a unique index that corresponds to the hardware thread that is
executing the current task. The ``threadIndex`` can be used for accessing
data that is private to the current thread and thus doesn't require
synchronization to access under parallel execution.
The tasking system also supports multi-dimensional partitioning (currently up
to three dimensions). To launch a 3D grid of tasks, for example with ``N0``,
``N1`` and ``N2`` tasks in x-, y- and z-dimension respectively
::
float data[N2][N1][N0]
task void foo_task()
{
data[taskIndex2][taskIndex1][threadIndex0] = taskIndex;
}
we use the following ``launch`` expressions:
::
launch [N2][N1][N0] foo_task()
or
::
launch [N0,N1,N2] foo_task()
Value of ``taskIndex`` is equal to ``taskIndex0 + taskCount0*(taskIndex1 +
taskCount1*taskIndex2)`` and it ranges from ``0`` to ``taskCount-1``, where
``taskCount = taskCount0*taskCount1*taskCount2``. If ``N1`` or/and ``N2`` are
not specified in the ``launch`` expression, a value of ``1`` is assumed.
Finally, for an one-dimensional grid of tasks, ``taskIndex`` is equivalent to
``taskIndex0`` and ``taskCount`` is equivalent to ``taskCount0``.
Task Parallelism: Runtime Requirements
--------------------------------------
If you use the task launch feature in ``ispc``, you must provide C/C++
implementations of three specific functions that manage launching and
synchronizing parallel tasks; these functions must be linked into your
executable. Although these functions may be implemented in any
language, they must have "C" linkage (i.e. their prototypes must be
declared inside an ``extern "C"`` block if they are defined in C++.)
By using user-supplied versions of these functions, ``ispc`` programs can
easily interoperate with software systems that have existing task systems
for managing parallelism. If you're using ``ispc`` with a system that
isn't otherwise multi-threaded and don't want to write custom
implementations of them, you can use the implementations of these functions
provided in the ``examples/tasksys.cpp`` file in the ``ispc``
distributions.
If you are implementing your own task system, the remainder of this section
discusses the requirements for these calls. You will also likely want to
review the example task systems in ``examples/tasksys.cpp`` for reference.
If you are not implementing your own task system, you can skip reading the
remainder of this section.
Here are the declarations of the three functions that must be provided to
manage tasks in ``ispc``:
::
void *ISPCAlloc(void **handlePtr, int64_t size, int32_t alignment);
void ISPCLaunch(void **handlePtr, void *f, void *data, int count0, int count1, int count2);
void ISPCSync(void *handle);
All three of these functions take an opaque handle (or a pointer to an
opaque handle) as their first parameter. This handle allows the task
system runtime to distinguish between calls to these functions from
different functions in ``ispc`` code. In this way, the task system
implementation can efficiently wait for completion on just the tasks
launched from a single function.
The first time one of ``ISPCLaunch()`` or ``ISPCAlloc()`` is called in an
``ispc`` function, the ``void *`` pointed to by the ``handlePtr`` parameter
will be ``NULL``. The implementations of these function should then
initialize ``*handlePtr`` to a unique handle value of some sort. (For
example, it might allocate a small structure to record which tasks were
launched by the current function.) In subsequent calls to these functions
in the emitted ``ispc`` code, the same value for ``handlePtr`` will be
passed in, such that loading from ``*handlePtr`` will retrieve the value
stored in the first call.
At function exit (or at an explicit ``sync`` statement), a call to
``ISPCSync()`` will be generated if ``*handlePtr`` is non-``NULL``.
Therefore, the handle value is passed directly to ``ISPCSync()``, rather
than a pointer to it, as in the other functions.
The ``ISPCAlloc()`` function is used to allocate small blocks of memory to
store parameters passed to tasks. It should return a pointer to memory
with the given size and alignment. Note that there is no explicit
``ISPCFree()`` call; instead, all memory allocated within an ``ispc``
function should be freed when ``ISPCSync()`` is called.
``ISPCLaunch()`` is called to launch one or more asynchronous
tasks. Each ``launch`` statement in ``ispc`` code causes a call to
``ISPCLaunch()`` to be emitted in the generated code. The three parameters
after the handle pointer to the function are relatively straightforward;
the ``void *f`` parameter holds a pointer to a function to call to run the
work for this task, ``data`` holds a pointer to data to pass to this
function, and ``count0``, ``count1`` and ``count2`` are the number of instances
of this function to enqueue for asynchronous execution. (In other words,
``count0``, ``count1`` and ``count2`` correspond to the value ``n0``, ``n1``
and ``n2`` in a multiple-task launch statement like ``launch[n2][n1][n0]`` or
``launch [n0,n1,n2]`` respectively.)
The signature of the provided function pointer ``f`` is
::
void (*TaskFuncPtr)(void *data, int threadIndex, int threadCount,
int taskIndex, int taskCount,
int taskIndex0, int taskIndex1, int taskIndex2,
int taskCount0, int taskCount1, int taskCount2);
When this function pointer is called by one of the hardware threads managed
by the task system, the ``data`` pointer passed to ``ISPCLaunch()`` should
be passed to it for its first parameter; ``threadCount`` gives the total
number of hardware threads that have been spawned to run tasks and
``threadIndex`` should be an integer index between zero and ``threadCount``
uniquely identifying the hardware thread that is running the task. (These
values can be used to index into thread-local storage.)
The value of ``taskCount`` should be the total number of tasks launched in the
``launch`` statement (it must be equal to ``taskCount0*taskCount1*taskCount2``)
that caused the call to ``ISPCLaunch()`` and each of the calls to this function
should be given a unique value of ``taskIndex``, ``taskIndex0``, ``taskIndex1``
and ``taskIndex2`` between zero and ``taskCount``, ``taskCount0``,
``taskCount1`` and ``taskCount2`` respectively, with ``taskIndex = taskIndex0
+ taskCount0*(taskIndex1 + taskCount1*taskIndex2)``, to distinguish which of
the instances of the set of launched tasks is running.
The ISPC Standard Library
=========================
``ispc`` has a standard library that is automatically available when
compiling ``ispc`` programs. (To disable the standard library, pass the
``--nostdlib`` command-line flag to the compiler.)
Basic Operations On Data
------------------------
Logical and Selection Operations
--------------------------------
Recall from `Expressions`_ that ``ispc`` short-circuits the evaluation of
logical and selection operators: given an expression like ``(index < count
&& array[index] == 0)``, then ``array[index] == 0`` is only evaluated if
``index < count`` is true. This property is useful for writing expressions
like the preceding one, where the second expression may not be safe to
evaluate in some cases.
This short-circuiting can impose overhead in the generated code; additional
operations are required to test the first value and to conditionally jump
over the code that evaluates the second value. The ``ispc`` compiler does
try to mitigate this cost by detecting cases where it is both safe and
inexpensive to evaluate both expressions, and skips short-circuiting in the
generated code in this case (without there being any programmer-visible
change in program behavior.)
For cases where the compiler can't detect this case but the programmer
wants to avoid short-circuiting behavior, the standard library provides a
few helper functions. First, ``and()`` and ``or()`` provide
non-short-circuiting logical AND and OR operations.
::
bool and(bool a, bool b)
bool or(bool a, bool b)
uniform bool and(uniform bool a, uniform bool b)
uniform bool or(uniform bool a, uniform bool b)
And there are three variants of ``select()`` that select between two values
based on a boolean condition. These are the variants of ``select()`` for
the ``int8`` type:
::
int8 select(bool v, int8 a, int8 b)
int8 select(uniform bool v, int8 a, int8 b)
uniform int8 select(uniform bool v, uniform int8 a, uniform int8 b)
There are also variants for ``int16``, ``int32``, ``int64``, ``float``, and
``double`` types.
Bit Operations
--------------
The various variants of ``popcnt()`` return the population count--the
number of bits set in the given value.
::
uniform int popcnt(uniform int v)
int popcnt(int v)
uniform int popcnt(bool v)
A few functions determine how many leading bits in the given value are zero
and how many of the trailing bits are zero; there are also ``unsigned``
variants of these functions and variants that take ``int64`` and ``unsigned
int64`` types.
::
int32 count_leading_zeros(int32 v)
uniform int32 count_leading_zeros(uniform int32 v)
int32 count_trailing_zeros(int32 v)
uniform int32 count_trailing_zeros(uniform int32 v)
Sometimes it's useful to convert a ``bool`` value to an integer using sign
extension so that the integer's bits are all on if the ``bool`` has the
value ``true`` (rather than just having the value one). The
``sign_extend()`` functions provide this functionality:
::
int sign_extend(bool value)
uniform int sign_extend(uniform bool value)
The ``intbits()`` and ``floatbits()`` functions can be used to implement
low-level floating-point bit twiddling. For example, ``intbits()`` returns
an ``unsigned int`` that is a bit-for-bit copy of the given ``float``
value. (Note: it is **not** the same as ``(int)a``, but corresponds to
something like ``*((int *)&a)`` in C.
::
float floatbits(unsigned int a);
uniform float floatbits(uniform unsigned int a);
unsigned int intbits(float a);
uniform unsigned int intbits(uniform float a);
The ``intbits()`` and ``floatbits()`` functions have no cost at runtime;
they just let the compiler know how to interpret the bits of the given
value. They make it possible to efficiently write functions that take
advantage of the low-level bit representation of floating-point values.
For example, the ``abs()`` function in the standard library is implemented
as follows:
::
float abs(float a) {
unsigned int i = intbits(a);
i &= 0x7fffffff;
return floatbits(i);
}
This code directly clears the high order bit to ensure that the given
floating-point value is positive. This compiles down to a single ``andps``
instruction when used with an Intel® SSE target, for example.
Math Functions
--------------
The math functions in the standard library provide a relatively standard
range of mathematical functionality.
A number of different implementations of the transcendental math functions
are available; the math library to use can be selected with the
``--math-lib=`` command line argument. The following values can be provided
for this argument.
* ``default``: ``ispc``'s default built-in math functions. These have
reasonably high precision. (e.g. ``sin`` has a maximum absolute error of
approximately 1.45e-6 over the range -10pi to 10pi.)
* ``fast``: more efficient but lower accuracy versions of the default ``ispc``
implementations.
* ``svml``: use Intel "Short Vector Math Library". Use
``icpc`` to link your final executable so that the appropriate libraries
are linked.
* ``system``: use the system's math library. On many systems, these
functions are more accurate than both of ``ispc``'s implementations.
Using these functions may be quite
inefficient; the system math functions only compute one result at a time
(i.e. they aren't vectorized), so ``ispc`` has to call them once per
active program instance. (This is not the case for the other three
options.)
Basic Math Functions
--------------------
In addition to an absolute value call, ``abs()``, ``signbits()`` extracts
the sign bit of the given value, returning ``0x80000000`` if the sign bit
is on (i.e. the value is negative) and zero if it is off.
::
float abs(float a)
uniform float abs(uniform float a)
unsigned int signbits(float x)
Standard rounding functions are provided. (On machines that support Intel®
SSE or Intel® AVX, these functions all map to variants of the ``roundss`` and
``roundps`` instructions, respectively.)
::
float round(float x)
uniform float round(uniform float x)
float floor(float x)
uniform float floor(uniform float x)
float ceil(float x)
uniform float ceil(uniform float x)
``rcp()`` computes an approximation to ``1/v``. The amount of error is
different on different architectures.
::
float rcp(float v)
uniform float rcp(uniform float v)
A standard set of minimum and maximum functions is available. These
functions also map to corresponding intrinsic functions.
::
float min(float a, float b)
uniform float min(uniform float a, uniform float b)
float max(float a, float b)
uniform float max(uniform float a, uniform float b)
unsigned int min(unsigned int a, unsigned int b)
uniform unsigned int min(uniform unsigned int a,
uniform unsigned int b)
unsigned int max(unsigned int a, unsigned int b)
uniform unsigned int max(uniform unsigned int a,
uniform unsigned int b)
The ``clamp()`` functions clamp the provided value to the given range.
(Their implementations are based on ``min()`` and ``max()`` and are thus
quite efficient.)
::
float clamp(float v, float low, float high)
uniform float clamp(uniform float v, uniform float low,
uniform float high)
unsigned int clamp(unsigned int v, unsigned int low,
unsigned int high)
uniform unsigned int clamp(uniform unsigned int v,
uniform unsigned int low,
uniform unsigned int high)
The ``isnan()`` functions test whether the given value is a floating-point
"not a number" value:
::
bool isnan(float v)
uniform bool isnan(uniform float v)
bool isnan(double v)
uniform bool isnan(uniform double v)
A number of functions are also available for performing operations on 8- and
16-bit quantities; these map to specialized instructions that perform these
operations on targets that support them. ``avg_up()`` computes the average
of the two values, rounding up if their average is halfway between two
integers (i.e., it computes ``(a+b+1)/2``).
::
int8 avg_up(int8 a, int8 b)
unsigned int8 avg_up(unsigned int8 a, unsigned int8 b)
int16 avg_up(int16 a, int16 b)
unsigned int16 avg_up(unsigned int16 a, unsigned int16 b)
``avg_down()`` computes the average of the two values, rounding down (i.e.,
it computes ``(a+b)/2``).
::
int8 avg_down(int8 a, int8 b)
unsigned int8 avg_down(unsigned int8 a, unsigned int8 b)
int16 avg_down(int16 a, int16 b)
unsigned int16 avg_down(unsigned int16 a, unsigned int16 b)
Transcendental Functions
------------------------
The square root of a given value can be computed with ``sqrt()``, which
maps to hardware square root intrinsics when available. An approximate
reciprocal square root, ``1/sqrt(v)`` is computed by ``rsqrt()``. Like
``rcp()``, the error from this call is different on different
architectures.
::
float sqrt(float v)
uniform float sqrt(uniform float v)
float rsqrt(float v)
uniform float rsqrt(uniform float v)
``ispc`` provides a standard variety of calls for trigonometric functions:
::
float sin(float x)
uniform float sin(uniform float x)
float cos(float x)
uniform float cos(uniform float x)
float tan(float x)
uniform float tan(uniform float x)
The corresponding inverse functions are also available:
::
float asin(float x)
uniform float asin(uniform float x)
float acos(float x)
uniform float acos(uniform float x)
float atan(float x)
uniform float atan(uniform float x)
float atan2(float y, float x)
uniform float atan2(uniform float y, uniform float x)
If both sine and cosine are needed, then the ``sincos()`` call computes
both more efficiently than two calls to the respective individual
functions:
::
void sincos(float x, varying float * uniform s, varying float * uniform c)
void sincos(uniform float x, uniform float * uniform s,
uniform float * uniform c)
The usual exponential and logarithmic functions are provided.
::
float exp(float x)
uniform float exp(uniform float x)
float log(float x)
uniform float log(uniform float x)
float pow(float a, float b)
uniform float pow(uniform float a, uniform float b)
A few functions that end up doing low-level manipulation of the
floating-point representation in memory are available. As in the standard
math library, ``ldexp()`` multiplies the value ``x`` by 2^n, and
``frexp()`` directly returns the normalized mantissa and returns the
normalized exponent as a power of two in the ``pw2`` parameter.
::
float ldexp(float x, int n)
uniform float ldexp(uniform float x, uniform int n)
float frexp(float x, varying int * uniform pw2)
uniform float frexp(uniform float x,
uniform int * uniform pw2)
Saturating Arithmetic
---------------------
A saturation (no overflow possible) addition, substraction, multiplication and
division of all integer types are provided by the ``ispc`` standard library.
::
int8 saturating_add(uniform int8 a, uniform int8 b)
int8 saturating_add(varying int8 a, varying int8 b)
unsigned int8 saturating_add(uniform unsigned int8 a, uniform unsigned int8 b)
unsigned int8 saturating_add(varying unsigned int8 a, varying unsigned int8 b)
int8 saturating_sub(uniform int8 a, uniform int8 b)
int8 saturating_sub(varying int8 a, varying int8 b)
unsigned int8 saturating_sub(uniform unsigned int8 a, uniform unsigned int8 b)
unsigned int8 saturating_sub(varying unsigned int8 a, varying unsigned int8 b)
int8 saturating_mul(uniform int8 a, uniform int8 b)
int8 saturating_mul(varying int8 a, varying int8 b)
unsigned int8 saturating_mul(uniform unsigned int8 a, uniform unsigned int8 b)
unsigned int8 saturating_mul(varying unsigned int8 a, varying unsigned int8 b)
int8 saturating_div(uniform int8 a, uniform int8 b)
int8 saturating_div(varying int8 a, varying int8 b)
unsigned int8 saturating_div(uniform unsigned int8 a, uniform unsigned int8 b)
unsigned int8 saturating_div(varying unsigned int8 a,varying unsigned int8 b)
In addition to the ``int8`` variants of saturating arithmetic functions listed
above, there are versions that supports ``int16``, ``int32`` and ``int64``
values as well.
Pseudo-Random Numbers
---------------------
A simple random number generator is provided by the ``ispc`` standard
library. State for the RNG is maintained in an instance of the
``RNGState`` structure, which is seeded with ``seed_rng()``.
::
struct RNGState;
void seed_rng(varying RNGState * uniform state, varying int seed)
void seed_rng(uniform RNGState * uniform state, uniform int seed)
Note that if the same ``varying`` seed value is used for all of the program
instances (e.g. ``RNGState state; seed_rng(&state, 1);``), then all of the
program instances in the gang will see the same sequence of pseudo-random
numbers. If this behavior isn't desred, you may want to add the
``programIndex`` value to the provided seed or otherwise ensure that the
seed has a unique value for each program instance.
After the RNG is seeded, the ``random()`` function can be used to get a
pseudo-random ``unsigned int32`` value and the ``frandom()`` function can
be used to get a pseudo-random ``float`` value.
::
unsigned int32 random(varying RNGState * uniform state)
float frandom(varying RNGState * uniform state)
uniform unsigned int32 random(RNGState * uniform state)
uniform float frandom(uniform RNGState * uniform state)
Random Numbers
--------------
Some recent CPUs (including those based on the Intel(r) Ivy Bridge
micro-architecture), provide support for generating true random numbers. A
few standard library functions make this functionality available:
::
bool rdrand(uniform int32 * uniform ptr)
bool rdrand(varying int32 * uniform ptr)
bool rdrand(uniform int32 * varying ptr)
If the processor doesn't have sufficient entropy to generate a random
number, then this function fails and returns ``false``. Otherwise, if the
processor is successful, the random value is stored in the given pointer
and ``true`` is returned. Therefore, this function should generally be
used as follows, called repeatedly until it is successful:
::
int r;
while (rdrand(&r) == false)
; // empty loop body
In addition to the ``int32`` variants of ``rdrand()`` listed above, there
are versions that return ``int16``, ``float``, and ``int64`` values as
well.
Note that when compiling to targets other than ``avx1.1`` and ``avx2``, the
``rdrand()`` functions always return ``false``.
Output Functions
----------------
``ispc`` has a simple ``print`` statement for printing values during
program execution. In the following short ``ispc`` program, there are
three uses of the ``print`` statement:
::
export void foo(uniform float f[4], uniform int i) {
float x = f[programIndex];
print("i = %, x = %\n", i, x);
if (x < 2) {
++x;
print("added to x = %\n", x);
}
print("last print of x = %\n", x);
}
There are a few things to note. First, the function is called ``print``,
not ``printf`` (unlike C). Second, the formatting string passed to this
function only uses a single percent sign to denote where the corresponding
value should be printed. You don't need to match the types of formatting
operators with the types being passed. However, you can't currently use
the rich data formatting options that ``printf`` provides (e.g. constructs
like ``%.10f``.).
If this function is called with the array of floats (0,1,2,3) passed in for
the ``f`` parameter and the value ``10`` for the ``i`` parameter, it
generates the following output on a four-wide compilation target:
::
i = 10, x = [0.000000,1.000000,2.000000,3.000000]
added to x = [1.000000,2.000000,((2.000000)),((3.000000))]
last print of x = [1.000000,2.000000,2.000000,3.000000]
When a varying variable is printed, the values for program instances that
aren't currently executing are printed inside double parenthesis,
indicating inactive program instances. The elements for inactive program
instances may have garbage values, though in some circumstances it can be
useful to see their values.
Assertions
----------
The ``ispc`` standard library includes a mechanism for adding ``assert()``
statements to ``ispc`` program code. Like ``assert()`` in C, the
``assert()`` function takes a single boolean expression as an argument. If
the expression evaluates to false at runtime, then a diagnostic error
message printed and the ``abort()`` function is called.
When called with a ``varying`` quantity, an assertion triggers if the
expression evaluates to false for any any of the executing program instances
at the point where it is called. Thus, given code like:
::
int x = programIndex - 2; // (-2, -1, 0, ... )
if (x > 0)
assert(x > 0);
The ``assert()`` statement will not trigger, since the condition isn't true
for any of the executing program instances at that point. (If this
``assert()`` statement was outside of this ``if``, then it would of course
trigger.)
To disable all of the assertions in a file that is being compiled (e.g.,
for an optimized release build), use the ``--opt=disable-assertions``
command-line argument.
Cross-Program Instance Operations
---------------------------------
``ispc`` programs are often used to express independently-executing
programs performing computation on separate data elements. (i.e. pure
data-parallelism). However, it's often the case where it's useful for the
program instances to be able to cooperate in computing results. The
cross-lane operations described in this section provide primitives for
communication between the running program instances in the gang.
The ``lanemask()`` function returns an integer that encodes which of the
current SPMD program instances are currently executing. The i'th bit is
set if the i'th program instance lane is currently active.
::
uniform int lanemask()
To broadcast a value from one program instance to all of the others, a
``broadcast()`` function is available. It broadcasts the value of the
``value`` parameter for the program instance given by ``index`` to all of
the running program instances.
::
int8 broadcast(int8 value, uniform int index)
int16 broadcast(int16 value, uniform int index)
int32 broadcast(int32 value, uniform int index)
int64 broadcast(int64 value, uniform int index)
float broadcast(float value, uniform int index)
double broadcast(double value, uniform int index)
The ``rotate()`` function allows each program instance to find the value of
the given value that their neighbor ``offset`` steps away has. For
example, on an 8-wide target, if ``value`` has the value (1, 2, 3, 4, 5,
6, 7, 8) across the gang of running program instances, then ``rotate(value,
-1)`` causes the first program instance to get the value 8, the second
program instance to get the value 1, the third 2, and so forth. The
provided offset value can be positive or negative, and may be greater than
the size of the gang (it is masked to ensure valid offsets).
::
int8 rotate(int8 value, uniform int offset)
int16 rotate(int16 value, uniform int offset)
int32 rotate(int32 value, uniform int offset)
int64 rotate(int64 value, uniform int offset)
float rotate(float value, uniform int offset)
double rotate(double value, uniform int offset)
The ``shift()`` function allows each program instance to find the value of
the given value that their neighbor ``offset`` steps away has. This is similar
to ``rotate()`` with the exception that values are not circularly shifted.
Instead, zeroes are shifted in where appropriate.
::
int8 shift(int8 value, uniform int offset)
int16 shift(int16 value, uniform int offset)
int32 shift(int32 value, uniform int offset)
int64 shift(int64 value, uniform int offset)
float shift(float value, uniform int offset)
double shift(double value, uniform int offset)
Finally, the ``shuffle()`` functions allow two variants of fully general
shuffling of values among the program instances. For the first version,
each program instance's value of permutation gives the program instance
from which to get the value of ``value``. The provided values for
``permutation`` must all be between 0 and the gang size.
::
int8 shuffle(int8 value, int permutation)
int16 shuffle(int16 value, int permutation)
int32 shuffle(int32 value, int permutation)
int64 shuffle(int64 value, int permutation)
float shuffle(float value, int permutation)
double shuffle(double value, int permutation)
The second variant of ``shuffle()`` permutes over the extended vector that
is the concatenation of the two provided values. In other words, a value
of 0 in an element of ``permutation`` corresponds to the first element of
``value0``, the value of two times the gang size, minus one corresponds to
the last element of ``value1``, etc.)
::
int8 shuffle(int8 value0, int8 value1, int permutation)
int16 shuffle(int16 value0, int16 value1, int permutation)
int32 shuffle(int32 value0, int32 value1, int permutation)
int64 shuffle(int64 value0, int64 value1, int permutation)
float shuffle(float value0, float value1, int permutation)
double shuffle(double value0, double value1, int permutation)
Finally, there are primitive operations that extract and set values in the
SIMD lanes. You can implement all of the broadcast, rotate, shift, and shuffle
operations described above in this section from these routines, though in
general, not as efficiently. These routines are useful for implementing
other reductions and cross-lane communication that isn't included in the
above, though. Given a ``varying`` value, ``extract()`` returns the i'th
element of it as a single ``uniform`` value. .
::
uniform int8 extract(int8 x, uniform int i)
uniform int16 extract(int16 x, uniform int i)
uniform int32 extract(int32 x, uniform int i)
uniform int64 extract(int64 x, uniform int i)
uniform float extract(float x, uniform int i)
Similarly, ``insert`` returns a new value
where the ``i`` th element of ``x`` has been replaced with the value ``v``
::
int8 insert(int8 x, uniform int i, uniform int8 v)
int16 insert(int16 x, uniform int i, uniform int16 v)
int32 insert(int32 x, uniform int i, uniform int32 v)
int64 insert(int64 x, uniform int i, uniform int64 v)
float insert(float x, uniform int i, uniform float v)
Reductions
----------
A number of routines are available to evaluate conditions across the
running program instances. For example, ``any()`` returns ``true`` if
the given value ``v`` is ``true`` for any of the SPMD program
instances currently running, ``all()`` returns ``true`` if it true
for all of them, and ``none()`` returns ``true`` if ``v`` is always
``false``.
::
uniform bool any(bool v)
uniform bool all(bool v)
uniform bool none(bool v)
You can also compute a variety of reductions across the program instances.
For example, the values of the given value in each of the active program
instances are added together by the ``reduce_add()`` function.
::
uniform int16 reduce_add(int8 x)
uniform unsigned int16 reduce_add(unsigned int8 x)
uniform int32 reduce_add(int16 x)
uniform unsigned int32 reduce_add(unsigned int16 x)
uniform int64 reduce_add(int32 x)
uniform unsigned int64 reduce_add(unsigned int32 x)
uniform int64 reduce_add(int64 x)
uniform unsigned int64 reduce_add(unsigned int64 x)
uniform float reduce_add(float x)
uniform double reduce_add(double x)
You can also use functions to compute the minimum value of the given value
across all of the currently-executing program instances.
::
uniform int32 reduce_min(int32 a)
uniform unsigned int32 reduce_min(unsigned int32 a)
uniform int64 reduce_min(int64 a)
uniform unsigned int64 reduce_min(unsigned int64 a)
uniform float reduce_min(float a)
uniform double reduce_min(double a)
Equivalent functions are available to comptue the maximum of the given
varying variable over the active program instances.
::
uniform int32 reduce_max(int32 a)
uniform unsigned int32 reduce_max(unsigned int32 a)
uniform int64 reduce_max(int64 a)
uniform unsigned int64 reduce_max(unsigned int64 a)
uniform float reduce_max(float a)
uniform double reduce_max(double a)
Finally, you can check to see if a particular value has the same value in
all of the currently-running program instances:
::
uniform bool reduce_equal(int32 v)
uniform bool reduce_equal(unsigned int32 v)
uniform bool reduce_equal(int64 v)
uniform bool reduce_equal(unsigned int64 v)
uniform bool reduce_equal(float v)
uniform bool reduce_equal(double)
There are also variants of these functions that return the value as a
``uniform`` in the case where the values are all the same. (There is
discussion of an application of this variant to improve memory access
performance in the `Performance Guide`_.
.. _Performance Guide: perfguide.html#understanding-gather-and-scatter
::
uniform bool reduce_equal(int32 v, uniform int32 * uniform sameval)
uniform bool reduce_equal(unsigned int32 v,
uniform unsigned int32 * uniform sameval)
uniform bool reduce_equal(int64 v, uniform int64 * uniform sameval)
uniform bool reduce_equal(unsigned int64 v,
uniform unsigned int64 * uniform sameval)
uniform bool reduce_equal(float v, uniform float * uniform sameval)
uniform bool reduce_equal(double, uniform double * uniform sameval)
If called when none of the program instances are running,
``reduce_equal()`` will return ``false``.
There are also a number of functions to compute "scan"s of values across
the program instances. For example, the ``exclusive_scan_and()`` function
computes, for each program instance, the sum of the given value over all of
the preceding program instances. (The scans currently available in
``ispc`` are all so-called "exclusive" scans, meaning that the value
computed for a given element does not include the value provided for that
element.) In C code, an exclusive add scan over an array might be
implemented as:
::
void scan_add(int *in_array, int *result_array, int count) {
result_array[0] = 0;
for (int i = 1; i < count; ++i)
result_array[i] = result_array[i-1] + in_array[i-1];
}
``ispc`` provides the following scan functions--addition, bitwise-and, and
bitwise-or are available:
::
int32 exclusive_scan_add(int32 v)
unsigned int32 exclusive_scan_add(unsigned int32 v)
float exclusive_scan_add(float v)
int64 exclusive_scan_add(int64 v)
unsigned int64 exclusive_scan_add(unsigned int64 v)
double exclusive_scan_add(double v)
int32 exclusive_scan_and(int32 v)
unsigned int32 exclusive_scan_and(unsigned int32 v)
int64 exclusive_scan_and(int64 v)
unsigned int64 exclusive_scan_and(unsigned int64 v)
int32 exclusive_scan_or(int32 v)
unsigned int32 exclusive_scan_or(unsigned int32 v)
int64 exclusive_scan_or(int64 v)
unsigned int64 exclusive_scan_or(unsigned int64 v)
The use of exclusive scan to generate variable amounts of output from
program instances into a compact output buffer is `discussed in the FAQ`_.
.. _discussed in the FAQ: faq.html#how-can-a-gang-of-program-instances-generate-variable-amounts-of-output-efficiently
Data Movement
-------------
Setting and Copying Values In Memory
------------------------------------
There are a few functions for copying blocks of memory and initializing
values in memory. Along the lines of the equivalently-named routines in
the C Standard libary, ``memcpy`` copies a given number of bytes starting
from a source location in memory to a destination locaiton, where the two
regions of memory are guaranteed by the caller to be non-overlapping.
Alternatively, ``memmove`` can be used to copy data if the buffers may
overlap.
::
void memcpy(void * uniform dst, void * uniform src, uniform int32 count)
void memmove(void * uniform dst, void * uniform src, uniform int32 count)
void memcpy(void * varying dst, void * varying src, int32 count)
void memmove(void * varying dst, void * varying src, int32 count)
Note that there are variants of these functions that take both ``uniform``
and ``varying`` pointers. Also note that ``sizeof(float)`` and
``sizeof(uniform float)`` return different values, so programmers should
take care when calculating ``count``.
To initialize values in memory, the ``memset`` routine can be used. (It
also behaves like the function of the same name in the C Standard Library.)
It sets the given number of bytes of memory starting at the given location
to the value provided.
::
void memset(void * uniform ptr, uniform int8 val, uniform int32 count)
void memset(void * varying ptr, int8 val, int32 count)
There are also variants of all of these functions that take 64-bit values
for the number of bytes of memory to operate on:
::
void memcpy64(void * uniform dst, void * uniform src, uniform int64 count)
void memcpy64(void * varying dst, void * varying src, int64 count)
void memmove64(void * uniform dst, void * uniform src, uniform int64 count)
void memmove64(void * varying dst, void * varying src, int64 count)
void memset64(void * uniform ptr, uniform int8 val, uniform int64 count)
void memset64(void * varying ptr, int8 val, int64 count)
Packed Load and Store Operations
--------------------------------
The standard library also offers routines for writing out and reading in
values from linear memory locations for the active program instances. The
``packed_load_active()`` functions load consecutive values starting at the
given location, loading one consecutive value for each currently-executing
program instance and storing it into that program instance's ``val``
variable. They return the total number of values loaded.
::
uniform int packed_load_active(uniform int * uniform base,
varying int * uniform val)
uniform int packed_load_active(uniform unsigned int * uniform base,
varying unsigned int * uniform val)
Similarly, the ``packed_store_active()`` functions store the ``val`` values
for each program instances that executed the ``packed_store_active()``
call, storing the results consecutively starting at the given location.
They return the total number of values stored.
::
uniform int packed_store_active(uniform int * uniform base,
int val)
uniform int packed_store_active(uniform unsigned int * uniform base,
unsigned int val)
There are also ``packed_store_active2()`` functions with exactly the same
signatures and the same semantic except that they may write one extra
element to the output array (but still returning the same value as
``packed_store_active()``). These functions suggest different branch free
implementation on most of supported targets, which usually (but not always)
performs better than ``packed_store_active()``. It's advised to test function
performance on user's scenarios on particular target hardware before using it.
As an example of how these functions can be used, the following code shows
the use of ``packed_store_active()``.
::
uniform int negative_indices(uniform float a[], uniform int length,
uniform int indices[]) {
uniform int numNeg = 0;
foreach (i = 0 ... length) {
if (a[i] < 0.)
numNeg += packed_store_active(&indices[numNeg], i);
}
return numNeg;
}
The function takes an array of floating point values ``a``, with length
given by the ``length`` parameter. This function also takes an output
array, ``indices``, which is assumed to be at least as long as ``length``.
It then loops over all of the elements of ``a`` and, for each element that
is less than zero, stores that element's offset into the ``indices`` array.
It returns the total number of negative values. For example, given an
input array ``a[8] = { 10, -20, 30, -40, -50, -60, 70, 80 }``, it returns a count
of four negative values, and initializes the first four elements of
``indices[]`` to the values ``{ 1, 3, 4, 5 }`` corresponding to the array
indices where ``a[i]`` was less than zero.
Data Conversions
----------------
Converting Between Array-of-Structures and Structure-of-Arrays Layout
---------------------------------------------------------------------
Applications often lay data out in memory in "array of structures" form.
Though convenient in C/C++ code, this layout can make ``ispc`` programs
less efficient than they would be if the data was laid out in "structure of
arrays" form. (See the section `Use "Structure of Arrays" Layout When
Possible`_ in the performance guide for extended discussion of this topic.)
The standard library does provide a few functions that efficiently convert
between these two formats, for cases where it's not possible to change the
application to use "structure of arrays layout". Consider an array of 3D
(x,y,z) position data laid out in a C array like:
::
// C++ code
float pos[] = { x0, y0, z0, x1, y1, z1, x2, ... };
In an ``ispc`` program, we might want to load a set of (x,y,z) values and
do a computation based on them. The natural expression of this:
::
extern uniform float pos[];
uniform int base = ...;
float x = pos[base + 3 * programIndex]; // x = { x0 x1 x2 ... }
float y = pos[base + 1 + 3 * programIndex]; // y = { y0 y1 y2 ... }
float z = pos[base + 2 + 3 * programIndex]; // z = { z0 z1 z2 ... }
leads to irregular memory accesses and reduced performance. Alternatively,
the ``aos_to_soa3()`` standard library function could be used:
::
extern uniform float pos[];
uniform int base = ...;
float x, y, z;
aos_to_soa3(&pos[base], x, y, z);
This routine loads three times the gang size values from the given array
starting at the given offset, returning three ``varying`` results. There
are both ``int32`` and ``float`` variants of this function:
::
void aos_to_soa3(uniform float a[], varying float * uniform v0,
varying float * uniform v1, varying float * uniform v2)
void aos_to_soa3(uniform int32 a[], varying int32 * uniform v0,
varying int32 * uniform v1, varying int32 * uniform v2)
After computation is done, corresponding functions convert back from the
SoA values in ``ispc`` ``varying`` variables and write the values back to
the given array, starting at the given offset.
::
extern uniform float pos[];
uniform int base = ...;
float x, y, z;
aos_to_soa3(&pos[base], x, y, z);
// do computation with x, y, z
soa_to_aos3(x, y, z, &pos[base]);
::
void soa_to_aos3(float v0, float v1, float v2, uniform float a[])
void soa_to_aos3(int32 v0, int32 v1, int32 v2, uniform int32 a[])
There are also variants of these functions that convert 4-wide values
between AoS and SoA layouts. In other words, ``aos_to_soa4()`` converts
AoS data in memory laid out like ``r0 g0 b0 a0 r1 g1 b1 a1 ...`` to four
``varying`` variables with values ``r0 r1...``, ``g0 g1...``, ``b0 b1...``,
and ``a0 a1...``, reading a total of four times the gang size values from
the given array, starting at the given offset.
::
void aos_to_soa4(uniform float a[], varying float * uniform v0,
varying float * uniform v1, varying float * uniform v2,
varying float * uniform v3)
void aos_to_soa4(uniform int32 a[], varying int32 * uniform v0,
varying int32 * uniform v1, varying int32 * uniform v2,
varying int32 * uniform v3)
void soa_to_aos4(float v0, float v1, float v2, float v3, uniform float a[])
void soa_to_aos4(int32 v0, int32 v1, int32 v2, int32 v3, uniform int32 a[])
Conversions To and From Half-Precision Floats
---------------------------------------------
There are functions to convert to and from the IEEE 16-bit floating-point
format. Note that there is no ``half`` data-type, and it isn't possible
to do floating-point math directly with ``half`` types in ``ispc``; these
functions facilitate converting to and from half-format data in memory.
To use them, half-format data should be loaded into an ``int16`` and the
``half_to_float()`` function used to convert it to a 32-bit floating point
value. To store a value to memory in half format, the ``float_to_half()``
function returns the 16 bits that are the closest match to the given
``float``, in half format.
::
float half_to_float(unsigned int16 h)
uniform float half_to_float(uniform unsigned int16 h)
int16 float_to_half(float f)
uniform int16 float_to_half(uniform float f)
There are also faster versions of these functions that don't worry about
handling floating point infinity, "not a number" and denormalized numbers
correctly. These are faster than the above functions, but are less
precise.
::
float half_to_float_fast(unsigned int16 h)
uniform float half_to_float_fast(uniform unsigned int16 h)
int16 float_to_half_fast(float f)
uniform int16 float_to_half_fast(uniform float f)
Converting to sRGB8
-------------------
The sRGB color space is used in many applications in graphics and imaging;
see the `Wikipedia page on sRGB`_ for more information. The ``ispc``
standard library provides two functions for converting floating-point color
values to 8-bit values in the sRGB space.
.. _Wikipedia page on sRGB: http://en.wikipedia.org/wiki/SRGB
::
int float_to_srgb8(float v)
uniform int float_to_srgb8(uniform float v)
Systems Programming Support
---------------------------
Atomic Operations and Memory Fences
-----------------------------------
The standard set of atomic memory operations are provided by the standard
library, including variants to handle both uniform and varying
types as well as "local" and "global" atomics.
Local atomics provide atomic behavior across the program instances in a
gang, but not across multiple gangs or memory operations in different
hardware threads. To see why they are needed, consider a histogram
calculation where each program instance in the gang computes which bucket a
value lies in and then increments a corresponding counter. If the code is
written like this:
::
uniform int count[N_BUCKETS] = ...;
float value = ...;
int bucket = clamp(value / N_BUCKETS, 0, N_BUCKETS);
++count[bucket]; // ERROR: undefined behavior if collisions
then the program's behavior is undefined: whenever multiple program
instances have values that map to the same value of ``bucket``, then the
effect of the increment is undefined. (See the discussion in the `Data
Races Within a Gang`_ section; in the case here, there isn't a sequence
point between one program instance updating ``count[bucket]`` and the other
program instance reading its value.)
The ``atomic_add_local()`` function can be used in this case; as a local
atomic it is atomic across the gang of program instances, such that the
expected result is computed.
::
...
int bucket = clamp(value / N_BUCKETS, 0, N_BUCKETS);
atomic_add_local(&count[bucket], 1);
It uses this variant of the 32-bit integer atomic add routine:
::
int32 atomic_add_local(uniform int32 * uniform ptr, int32 delta)
The semantics of this routine are typical for an atomic add function: the
pointer here points to a single location in memory (the same one for all
program instances), and for each executing program instance, the value
stored in the location that ``ptr`` points to has that program instance's
value "delta" added to it atomically, and the old value at that location is
returned from the function.
One thing to note is that the type of the value being added to is a
``uniform`` integer, while the increment amount and the return value are
``varying``. In other words, the semantics of this call are that each
running program instance individually issues the atomic operation with its
own ``delta`` value and gets the previous value back in return. The
atomics for the running program instances may be issued in arbitrary order;
it's not guaranteed that they will be issued in ``programIndex`` order, for
example.
Global atomics are more powerful than local atomics; they are atomic across
both the program instances in the gang as well as atomic across different
gangs and different hardware threads. For example, for the global variant
of the atomic used above,
::
int32 atomic_add_global(uniform int32 * uniform ptr, int32 delta)
if multiple processors simultaneously issue atomic adds to the same memory
location, the adds will be serialized by the hardware so that the correct
result is computed in the end.
Here are the declarations of the ``int32`` variants of these functions.
There are also ``int64`` equivalents as well as variants that take
``unsigned`` ``int32`` and ``int64`` values.
::
int32 atomic_add_{local,global}(uniform int32 * uniform ptr, int32 value)
int32 atomic_subtract_{local,global}(uniform int32 * uniform ptr, int32 value)
int32 atomic_min_{local,global}(uniform int32 * uniform ptr, int32 value)
int32 atomic_max_{local,global}(uniform int32 * uniform ptr, int32 value)
int32 atomic_and_{local,global}(uniform int32 * uniform ptr, int32 value)
int32 atomic_or_{local,global}(uniform int32 * uniform ptr, int32 value)
int32 atomic_xor_{local,global}(uniform int32 * uniform ptr, int32 value)
int32 atomic_swap_{local,global}(uniform int32 * uniform ptr, int32 value)
Support for ``float`` and ``double`` types is also available. For local
atomics, all but the logical operations are available. (There are
corresponding ``double`` variants of these, not listed here.)
::
float atomic_add_local(uniform float * uniform ptr, float value)
float atomic_subtract_local(uniform float * uniform ptr, float value)
float atomic_min_local(uniform float * uniform ptr, float value)
float atomic_max_local(uniform float * uniform ptr, float value)
float atomic_swap_local(uniform float * uniform ptr, float value)
For global atomics, only atomic swap is available for these types:
::
float atomic_swap_global(uniform float * uniform ptr, float value)
double atomic_swap_global(uniform double * uniform ptr, double value)
Finally, "swap" (but none of these other atomics) is available for pointer
types:
::
void *atomic_swap_{local,global}(void * * uniform ptr, void * value)
There are also variants of the atomic that take ``uniform`` values for the
operand and return a ``uniform`` result. These correspond to a single
atomic operation being performed for the entire gang of program instances,
rather than one per program instance.
::
uniform int32 atomic_add_{local,global}(uniform int32 * uniform ptr,
uniform int32 value)
uniform int32 atomic_subtract_{local,global}(uniform int32 * uniform ptr,
uniform int32 value)
uniform int32 atomic_min_{local,global}(uniform int32 * uniform ptr,
uniform int32 value)
uniform int32 atomic_max_{local,global}(uniform int32 * uniform ptr,
uniform int32 value)
uniform int32 atomic_and_{local,global}(uniform int32 * uniform ptr,
uniform int32 value)
uniform int32 atomic_or_{local,global}(uniform int32 * uniform ptr,
uniform int32 value)
uniform int32 atomic_xor_{local,global}(uniform int32 * uniform ptr,
uniform int32 value)
uniform int32 atomic_swap_{local,global}(uniform int32 * uniform ptr,
uniform int32 newval)
And similarly for pointers:
::
uniform void *atomic_swap_{local,global}(void * * uniform ptr,
void *newval)
Be careful that you use the atomic function that you mean to; consider the
following code:
::
extern uniform int32 counter;
int32 myCounter = atomic_add_global(&counter, 1);
One might write code like this with the intent that each running program
instance increments the counter by one and gets the old value of the
counter (for example, to store results into unique locations in an array).
However, the above code calls the second variant of
``atomic_add_global()``, which takes a ``uniform int`` value to add to the
counter and only performs one atomic operation. The counter will be
increased by just one, and all program instances will receive the same
value back (thanks to the ``uniform int32`` return value being silently
converted to a ``varying int32``.) Writing the code this way, for example,
will cause the desired atomic add function to be called.
::
extern uniform int32 counter;
int32 myCounter = atomic_add_global(&counter, (varying int32)1);
There is a third variant of each of these atomic functions that takes a
``varying`` pointer; this allows each program instance to issue an atomic
operation to a possibly-different location in memory. (Of course, the
proper result is still returned if some or all of them happen to point to
the same location in memory!)
::
int32 atomic_add_{local,global}(uniform int32 * varying ptr, int32 value)
int32 atomic_subtract_{local,global}(uniform int32 * varying ptr, int32 value)
int32 atomic_min_{local,global}(uniform int32 * varying ptr, int32 value)
int32 atomic_max_{local,global}(uniform int32 * varying ptr, int32 value)
int32 atomic_and_{local,global}(uniform int32 * varying ptr, int32 value)
int32 atomic_or_{local,global}(uniform int32 * varying ptr, int32 value)
int32 atomic_xor_{local,global}(uniform int32 * varying ptr, int32 value)
int32 atomic_swap_{local,global}(uniform int32 * varying ptr, int32 value)
And:
::
void *atomic_swap_{local,global}(void * * ptr, void *value)
There are also atomic "compare and exchange" functions. Compare and
exchange atomically compares the value in "val" to "compare"--if they
match, it assigns "newval" to "val". In either case, the old value of
"val" is returned. (As with the other atomic operations, there are also
``unsigned`` and 64-bit variants of this function. Furthermore, there are
``float``, ``double``, and ``void *`` variants as well.)
::
int32 atomic_compare_exchange_{local,global}(uniform int32 * uniform ptr,
int32 compare, int32 newval)
uniform int32 atomic_compare_exchange_{local,global}(uniform int32 * uniform ptr,
uniform int32 compare, uniform int32 newval)
``ispc`` also has a standard library routine that inserts a memory barrier
into the code; it ensures that all memory reads and writes prior to be
barrier complete before any reads or writes after the barrier are issued.
See the `Linux kernel documentation on memory barriers`_ for an excellent
writeup on the need for and the use of memory barriers in multi-threaded
code.
.. _Linux kernel documentation on memory barriers: http://www.kernel.org/doc/Documentation/memory-barriers.txt
::
void memory_barrier();
Note that this barrier is *not* needed for coordinating reads and writes
among the program instances in a gang; it's only needed for coordinating
between multiple hardware threads running on different cores. See the
section `Data Races Within a Gang`_ for the guarantees provided about
memory read/write ordering across a gang.
Prefetches
----------
The standard library has a variety of functions to prefetch data into the
processor's cache. While modern CPUs have automatic prefetchers that do a
reasonable job of prefetching data to the cache before its needed, high
performance applications may find it helpful to prefetch data before it's
needed.
For example, this code shows how to prefetch data to the processor's L1
cache while iterating over the items in an array.
::
uniform int32 array[...];
for (uniform int i = 0; i < count; ++i) {
// do computation with array[i]
prefetch_l1(&array[i+32]);
}
The standard library has routines to prefetch to the L1, L2, and L3
caches. It also has a variant, ``prefetch_nt()``, that indicates that the
value being prefetched isn't expected to be used more than once (so should
be high priority to be evicted from the cache). Furthermore, it has
versions of these functions that take both ``uniform`` and ``varying``
pointer types.
::
void prefetch_{l1,l2,l3,nt}(void * uniform ptr)
void prefetch_{l1,l2,l3,nt}(void * varying ptr)
System Information
------------------
The value of a high-precision hardware clock counter is returned by the
``clock()`` routine; its value increments by one each processor cycle.
Thus, taking the difference between the values returned by ``clock()`` at
different points in program execution gives the number of cycles between
those points in the program.
::
uniform int64 clock()
Note that ``clock()`` flushes the processor pipeline. It has an overhead
of a hundred or so cycles, so for very fine-grained measurements, it may be
worthwhile to measure the cost of calling ``clock()`` and subtracting that
value from reported results.
A routine is also available to find the number of CPU cores available in
the system:
::
uniform int num_cores()
This value can be useful for adapting the granularity of parallel task
decomposition depending on the number of processors in the system.
Interoperability with the Application
=====================================
One of ``ispc``'s key goals is to make it easy to interoperate between the
C/C++ application code and parallel code written in ``ispc``. This
section describes the details of how this works and describes a number of
the pitfalls.
Interoperability Overview
-------------------------
As described in `Compiling and Running a Simple ISPC Program`_ it's
relatively straightforward to call ``ispc`` code from C/C++. First, any
``ispc`` functions to be called should be defined with the ``export``
keyword:
::
export void foo(uniform float a[]) {
...
}
This function corresponds to the following C-callable function:
::
void foo(float a[]);
(Recall from the `"uniform" and "varying" Qualifiers`_ section
that ``uniform`` types correspond to a single instances of the
corresponding type in C/C++.)
In addition to variables passed from the application to ``ispc`` in the
function call, you can also share global variables between the application
and ``ispc``. To do so, just declare the global variable as usual (in
either ``ispc`` or application code), and add an ``extern`` declaration on
the other side.
For example, given this ``ispc`` code:
::
// ispc code
uniform float foo;
extern uniform float bar[10];
And this C++ code:
::
// C++ code
extern "C" {
extern float foo;
float bar[10];
}
Both the ``foo`` and ``bar`` global variables can be accessed on each
side. Note that the ``extern "C"`` declaration is necessary from C++,
since ``ispc`` uses C linkage for functions and globals.
``ispc`` code can also call back to C/C++. On the ``ispc`` side, any
application functions to be called must be declared with the ``extern "C"``
qualifier.
::
extern "C" void foo(uniform float f, uniform float g);
Unlike in C++, ``extern "C"`` doesn't take braces to delineate
multiple functions to be declared; thus, multiple C functions to be called
from ``ispc`` must be declared as follows:
::
extern "C" void foo(uniform float f, uniform float g);
extern "C" uniform int bar(uniform int a);
It is illegal to overload functions declared with ``extern "C"`` linkage;
``ispc`` issues an error in this case.
**Only a single function call is made back to C++ for the entire gang of
running program instances**. Furthermore, function calls back to C/C++ are not
made if none of the program instances want to make the call. For example,
given code like:
::
uniform float foo = ...;
float x = ...;
if (x != 0)
foo = appFunc(foo);
``appFunc()`` will only be called if one or more of the running program
instances evaluates ``true`` for ``x != 0``. If the application code would
like to determine which of the running program instances want to make the
call, a mask representing the active SIMD lanes can be passed to the
function.
::
extern "C" float appFunc(uniform float x,
uniform int activeLanes);
If the function is then called as:
::
...
x = appFunc(x, lanemask());
The ``activeLanes`` parameter will have the value one in the 0th bit if the
first program instance is running at this point in the code, one in the
first bit for the second instance, and so forth. (The ``lanemask()``
function is documented in `Cross-Program Instance Operations`_.)
Application code can thus be written as:
::
float appFunc(float x, int activeLanes) {
for (int i = 0; i < programCount; ++i)
if ((activeLanes & (1 << i)) != 0) {
// do computation for i'th SIMD lane
}
}
In some cases, it can be desirable to generate a single call for each
executing program instance, rather than one call for a gang. For example,
the code below shows how one might call an existing math library routine
that takes a scalar parameter.
::
extern "C" uniform double erf(uniform double);
double v = ...;
double result;
foreach_active (instance) {
uniform double r = erf(extract(v, instance));
result = insert(result, instance, r);
}
This code calls ``erf()`` once for each active program instance, passing it
the program instance's value of ``v`` and storing the result in the
instance's ``result`` value.
Data Layout
-----------
In general, ``ispc`` tries to ensure that ``struct`` types and other
complex datatypes are laid out in the same way in memory as they are in
C/C++. Matching structure layout is important for easy interoperability
between C/C++ code and ``ispc`` code.
The main complexity in sharing data between ``ispc`` and C/C++ often comes
from reconciling data structures between ``ispc`` code and application
code; it can be useful to declare the shared structures in ``ispc`` code
and then examine the generated header file (which will have the C/C++
equivalents of them.) For example, given a structure in ``ispc``:
::
// ispc code
struct Node {
int count;
float pos[3];
};
If a ``uniform Node`` structure is used in the parameters to an ``export``
ed function, then the header file generated by the ``ispc`` compiler will
have a declaration like:
::
// C/C++ code
struct Node {
int count;
float pos[3];
};
Because ``varying`` types have size that depends on the size of the gang of
program instances, ``ispc`` has restrictrictions on using varying types in
parameters to functions with the ``export`` qualifier. ``ispc `` prohibits
parameters to exported functions to have varying type unless the parameter is
of pointer type. (That is, ``varying float`` isn't allowed, but ``varying float * uniform``
(uniform pointer to varying float) is permitted.) Care must be taken
by the programmer to ensure that the data being accessed through any
pointers to varying data has the correct organization.
Similarly, ``struct`` types shared with the application can also have
embedded pointers.
::
// C code
struct Foo {
float *foo, *bar;
};
On the ``ispc`` side, the corresponding ``struct`` declaration is:
::
// ispc
struct Foo {
float * uniform foo, * uniform bar;
};
If a pointer to a varying ``struct`` type appears in an exported function,
the generated header file will have a definition like (for 8-wide SIMD):
::
// C/C++ code
struct Node {
int count[8];
float pos[3][8];
};
In the case of multiple target compilation, ``ispc`` will generate multiple
header files and a "general" header file with definitions for multiple sizes.
Any pointers to varyings in exported functions will be rewritten as ``void *``.
At runtime, the ``ispc`` dispatch mechanism will cast these pointers to the appropriate
types. Programmers can
provide C/C++ code with a mechanism to determine the gang width used
at runtime by ``ispc`` by creating an exported function that simply
returns the value of ``programCount``. An example of such a function
is provided in the file ``examples/util/util.isph`` included in the ``ispc``
distribution.
There is one subtlety related to data layout to be aware of: ``ispc``
stores ``uniform`` short-vector types in memory with their first element at
the machine's natural vector alignment (i.e. 16 bytes for a target that is
using Intel® SSE, and so forth.) This implies that these types will have
different layout on different compilation targets. As such, applications
should in general avoid accessing ``uniform`` short vector types from C/C++
application code if possible.
Data Alignment and Aliasing
---------------------------
There are two important constraints that must be adhered to when
passing pointers from the application to ``ispc`` programs.
The first is that it is required that it be valid to read memory at the
first element of any array that is passed to ``ispc``. In practice, this
should just happen naturally, but it does mean that it is illegal to pass a
``NULL`` pointer as a parameter to a ``ispc`` function called from the
application.
The second constraint is that pointers and references in ``ispc`` programs
must not alias. The ``ispc`` compiler assumes that different pointers
can't end up pointing to the same memory location, either due to having the
same initial value, or through array indexing in the program as it
executed.
This aliasing constraint also applies to ``reference`` parameters to
functions. Given a function like:
::
void func(int &a, int &b) {
a = 0;
if (b == 0) { ... }
}
Then the same variable must not be passed to ``func()``. This is
another case of aliasing, and if the caller calls the function as ``func(x,
x)``, it's not guaranteed that the ``if`` test will evaluate to true, due
to the compiler's requirement of no aliasing.
(In the future, ``ispc`` will have a mechanism to indicate that pointers
may alias.)
Restructuring Existing Programs to Use ISPC
-------------------------------------------
``ispc`` is designed to enable you to incorporate
SPMD parallelism into existing code with minimal modification; features
like the ability to share memory and data structures between C/C++ and
``ispc`` code and the ability to directly call back and forth between
``ispc`` and C/C++ are motivated by this. These features also make it
easy to incrementally transform a program to use ``ispc``; the most
computationally-intensive localized parts of the computation can be
transformed into ``ispc`` code while the remainder of the system is left
as is.
For a given section of code to be transitioned to run in ``ispc``, the
next question is how to parallelize the computation. Generally, there will
be obvious loops inside which a large amount of computation is done ("for
each ray", "for each pixel", etc.) Mapping these to the SPMD computational
style is often effective.
Carefully choose how to do the exact mapping of computation to SPMD program
instances. This choice can impact the mix of gather/scatter memory access
versus coherent memory access, for example. (See more on this topic in the
`ispc Performance Tuning Guide`_.) This decision can also impact the
coherence of control flow across the running SPMD program instances, which
can also have a significant effect on performance; in general, creating
groups of work that will tend to do similar computation across the SPMD
program instances improves performance.
.. _ispc Performance Tuning Guide: http://ispc.github.com/perfguide.html
Experimental support for PTX
============================
``ispc`` provides experimental support for PTX code generation which currently
targets NVIDIA GPUs with compute capability >3.5 [Kepler GPUs with support for
dynamic parallelism]. Due to its nature, the PTX backend currently impose
several restrictions on the ``ispc`` program, which will be described below.
Overview
--------
SPMD programming in ``ispc`` is similar to a warp-synchronous CUDA programming.
Namely, program instances in a gang are equivalent of CUDA threads in a single
warp. Hence, to run efficiently on a GPU ``ispc`` program must use tasking
functionality via ``launch`` keyword to ensure multiple number of warps are
executed concurrently on the GPU.
``export`` functions are equipped with a CUDA C wrapper which schedules a
single warp--a thread-block with a total of 32 threads. In contract to CPU
programming, this exported function, either directly or otherwise, should
utilize ``launch`` keyword to schedule work on a GPU.
At the PTX level, ``launch`` keyword is mapped to CUDA Dynamic Parallelism and
it schedules a grid of thread-blocks each 4 warps-wide (128 threads). As a
result, ``ispc`` has a tasking-granularity of 4 tasks with PTX target; this
restriction will be eliminated in future.
When passing pointers to an ``export`` function, it is important that they
remain legal when are accessed from GPU. Prior to CUDA 6.0, such a pointer were
holding an address that is only accessible from the GPU. With the release of
CUDA 6.0, it is possible to pass a pointer to a unified memory allocated with
``cudaMallocManaged``. Examples provides rudimentary wrapper functions that
call CUDA API for managed memory allocations, allowing the programmers to avoid
explicit memory copies.
Compiling For The NVIDIA Kepler GPU
-----------------------------------
Compilation for NVIDIA Kepler GPU is a several step procedure.
First, we need to generate a LLVM assembly from ``ispc`` source file (``ispc``
generates LLVM assembly instead of bitcode when ``nvptx`` target is chosen):
::
$ISPC_HOME/ispc foo.ispc --emit-llvm --target=nvptx -o foo.ll
This LLVM assembly can immediately be compiled into PTX with the help of
``ptxgen`` tool; this tool uses ``libNVVM`` which is a part of a CUDA Toolkit.
::
$ISPC_HOME/ptxtools/ptxgen --use_fast_math foo.ll -o foo.ptx
.. If ``ispc`` is compiled with LLVM >3.2, the resulting bitcode must first be
.. decompiled with the ``llvm-dis`` from LLVM 3.2 distribution; this "trick" is
.. required to generate an IR compatible with libNVVM:
.. ::
..
.. $LLVM32/bin/llvm-dis foo.bc -o foo.ll
.. $ISPC_HOME/ptxtools/ptxgen --use_fast_math foo.ll -o foo.ptx
This PTX is ready for execution on a GPU, for example via CUDA
Driver API. Alternatively, we also provide a simple ``ptxcc`` tool, which
compiles the resulting PTX code into an object file:
::
$ISPC_HOME/ptxtools/ptxcc foo.ptx -o foo_cu.o -Xnvcc="--maxrregcount=64
-Xptxas=-v"
This object file can be linked with the main program via ``nvcc``:
::
nvcc foo_cu.o foo_main.o -o foo
Hints
-----
- ``uniform`` arrays in a function scope are statically allocated in
``__shared__`` memory, with all ensuing consequences. For example, if more
than avaiable shared memory per SMX is allocated, a link- or runtime-error will occur
- If ``uniform`` arrays of large size are desired, we recommend to use
``uniform new uniform T[size]`` for their allocation, ideally outside the
tasking function (see ``deferred/kernels.ispc`` in the deferred shading example)
Examples that produces executables for CPU, XeonPhi and Kepler GPU display
several tuning approaches that can benefit GPU performance.
``ispc`` may also generate performance warning, that if followed, may improve
GPU application performance.
Limitations & known issues
--------------------------
Due to its experimental form, PTX code generation is known to impose several
limitation on the ``ispc`` program which are documented in the following list:
- Must use ``ispc`` tasking functionality to run efficiently on GPU
- Must use ``new/delete`` and/or ``ispc_malloc``/``ispc_free``/``ispc_memset``/``ispc_memcpy`` to allocate/free/set/copy memory that is visible to GPU
- ``export`` functions must have ``void`` return type.
- ``task``/``export`` functions do not accept varying data-types
- ``new``/``delete`` currently only works with ``uniform`` data-types
- ``aossoa``/``soaaos`` is not yet supported
- ``sizeof(varying)`` is not yet unsupported
- Function pointers do not work yet (may or may not generate compilation fail)
- ``memset``/``memcpy``/``memmove`` is not yet supported
- ``uniform`` arrays in global scope are mapped to global memory
- ``varying`` arrays in global scope are not yet supported
- ``uniform`` arrays in local scope are mapped to shared memory
- ``varying`` arrays in local scope are mapped to local memory
- ``const uniform/varying`` arrays are mapped to local memory
- ``const static uniform`` arrays are mapped to constant memory
- ``const static varying`` arrays are mapped to global memory
- ``static`` data types in local scope are not allowed; compilation will fail
- Best performance is obtained with libNVVM (LLVM PTX backend can also be used but it requires libdevice.compute_35.10.bc that comes with libNVVM)
Likely there are more... which, together with some of the above-mentioned
issues, will be fixed in due time.
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