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=========================================
Intel® SPMD Program Compiler User's Guide
=========================================
``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 small 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 funcion
calls betwen the two languages, sharing data directly via pointers without
copying or reformating, 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`_
* `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`_
+ `Selecting 32 or 64 Bit Addressing`_
+ `The Preprocessor`_
+ `Debugging`_
* `Parallel Execution Model in ISPC`_
+ `Program Instances and Gangs of Program Instances`_
+ `The SPMD-on-SIMD Execution Model`_
+ `Gang Convergence`_
+ `Data Races Within a Gang`_
+ `Uniform Data In A Gang`_
+ `Uniform Variables and Varying Control Flow`_
* `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`_
* `Struct and Array Types`_
+ `Declarations and Initializers`_
+ `Expressions`_
+ `Control Flow`_
* `Conditional Statements: "if"`_
* `Basic Iteration Statements: "for", "while", and "do"`_
* `"Coherent" Control Flow Statements: "cif" and Friends`_
* `Parallel Iteration Statements: "foreach" and "foreach_tiled"`_
* `Parallel Iteration with "programIndex" and "programCount"`_
* `Functions and Function Calls`_
+ `Function Overloading`_
* `Task Parallel Execution`_
+ `Task Parallelism: "launch" and "sync" Statements`_
+ `Task Parallelism: Runtime Requirements`_
* `The ISPC Standard Library`_
+ `Math Functions`_
* `Basic Math Functions`_
* `Bit-Level Operations`_
* `Transcendental Functions`_
* `Pseudo-Random Numbers`_
+ `Output Functions`_
+ `Assertions`_
+ `Cross-Program Instance Operations`_
* `Reductions`_
+ `Data Conversions And Storage`_
* `Packed Load and Store Operations`_
* `Converting Between Array-of-Structures and Structure-of-Arrays Layout`_
* `Conversions To and From Half-Precision Floats`_
+ `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`_
+ `Understanding How to Interoperate With the Application's Data`_
* `Related Languages`_
* `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 1.1 release of ``ispc`` features first-class support for pointers in
the language. Adding this functionality led to a number of syntactic
changes to the language. These should generally require only
straightforward modification of existing 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 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.
* 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.
* 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.
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 correpsonding
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.
For a simple program like this one, the performance difference versus a
regular scalar C/C++ implementation of the same computation is not likely
to be compelling. For more complex programs that do more substantial
amounts of computation, doing that computation in parallel across the
machine's SIMD lanes can have a substantial performance benefit.
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++ 2010\* 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 walkthrough 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
optimizaion, ``-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.
By default, the ``ispc`` compiler generates code for the 64-bit x86-64
architecture (i.e. ``--arch=x86-64`.) To compile to a 32-bit x86 target,
supply ``--arch=x86`` on the command line:
::
ispc foo.ispc -o foo.obj --arch=x86
No other architectures are currently supported.
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 a number 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 between the SSE2, SSE4, and AVX instruction
sets. (As general context, SSE2 was first introduced in processors that
shipped in 2001, SSE4 was introduced in 2007, and processors with AVX
were introduced in 2010. Consult your CPU's manual for specifics on which
vector instruction set it supports.)
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, use ``--target=sse2``. (As with the other options in this
section, see the output of ``ispc --help`` for a full list of supported
targets.)
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 decision 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.)
Three preprocessor symbols are automatically defined before the
preprocessor runs. First, ``ISPC`` is defined, so that it can be detected
that the ``ispc`` compiler is running over the program. Next, a symbol
indicating the target instruction set is defined. With an SSE2 target,
``ISPC_TARGET_SSE2`` is defined; ``ISPC_TARGET_SSE4`` is defined for SSE4,
and ``ISPC_TARGET_AVX`` for AVX.
To detect which version of the compiler is being used, the
``ISPC_MAJOR_VERSION`` and ``ISPC_MINOR_VERSION`` symbols are available.
For the 1.0 releases of ``ispc`` these symbols were not defined; starting
with ``ispc`` 1.1, they are defined, both having value 1.
For convenience, ``PI`` is defined, having the value 3.1415926535.
Debugging
---------
Support for debugging in ``ispc`` is in progress. 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 and the like
all generally works, though there is occasional unexpected behavior.
Another option for debugging (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.
Parallel Execution Model in ISPC
================================
invariant: will never execute with mask "all off" (at least not observably)
make the notion of a uniform pc + a mask a clear component
define what we mean by control flow coherence here
handwave to point forward to the language reference in the following
section
mention task parallelism here, basically that there are no guarantees about
ordering between tasks, no way to synchronize among them, but remidn that
we sync before returning from functions
Though ``ispc`` has C-based syntax, it is inherently a language for
parallel computation. Understanding the details of ``ispc``'s parallel
execution model is critical for writing efficient and correct programs in
``ispc``.
``ispc`` supports both task parallelism to parallelize across multiple
cores and SPMD parallelism to parallelize across the SIMD vector lanes on a
single core. This section focuses on SPMD parallelism. See the sections
`Task Parallelism: "launch" and "sync" Statements`_ and `Task Parallelism:
Runtime Requirements`_ for discussion of task parallelism in ``ispc``.
Program Instances and Gangs of Program Instances
------------------------------------------------
The SPMD-on-SIMD Execution Model
--------------------------------
In the SPMD model as implemented in ``ispc``, you programs that compute a
set of outputs based on a set of inputs. You must write these
programs so that it is safe to run multiple instances of them in
parallel--i.e. given a program an a set of inputs, the programs shouldn't
have any assumptions about the order in which they will be run over the
inputs, whether one program instances will have completed before another
runs. [#]_
.. [#] This is essentially the same requirement that languages like CUDA\*
and OpenCL\* place on the programmer.
Given this guarantee, the ``ispc`` compiler can safely execute multiple
program instances in parallel, across the SIMD lanes of a single CPU. In
many cases, this execution approach can achieve higher overall performance
than if the program instances had been run serially.
Upon entry to a ``ispc`` function, the execution model switches from
the application's serial model to SPMD. Conceptually, a number of
``ispc`` program instances will start running in parallel. This
parallelism doesn't involve launching hardware threads. Rather, one
program instance is mapped to each of the SIMD lanes of the CPU's vector
unit (Intel® SSE or Intel® AVX).
If a ``ispc`` program is written to do a the following computation:
::
float x = ..., y = ...;
return x+y;
and if the ``ispc`` program is running four-wide on a CPU that supports the
Intel® SSE instructions, then four program instances are running in
parallel, each adding a pair of scalar values. However, these four program
instances store their individual scalar values for ``x`` and ``y`` in the
lanes of an Intel® SSE vector register, so the addition operation for all
four program instances can be done in parallel with a single ``addps``
instruction.
Program execution is more complicated in the presence of control flow. The
details are handled by the ``ispc`` compiler, but you may find it helpful
to understand what is going on in order to be a more effective ``ispc``
programmer. In particular, the mapping of SPMD to SIMD lanes can lead to
reductions in this SIMD efficiency as different program instances want to
perform different computations. For example, consider a simple ``if``
statement:
::
float x = ..., y = ...;
if (x < y) {
...
} else {
...
}
In general, the test ``x<y`` has a different result for different running
SPMD program instances. 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. ``ispc`` processes this case by
generating code that executes for both cases and masking the results, such
that the "true" code doesn't have any side effects for the program
instances that want to run the "false" code, and vice versa. Thus, the
correct reusult is computed for all of the program instances in the end,
though with some overhead relative to a scalar implementation where code
for only one of the two cases needs to run.
``for``, ``while``, and ``do`` statements are similar. Their loops must
run until all of the running SPMD program instances are ready to exit the
loop. Thus in an extreme case of a loop like:
::
// assume limit has the values (1,1,1,1000) for the
// current running program instances
int limit = ...;
for (int i = 0; i < limit; ++i) {
...
}
The loop body needs to execute 1000 times, since one of the SPMD
program instances has a value of 1000 for ``limit``. For the other three
running program instances, the right result will still be computed, as the
code run the additional 999 times won't have any side effects for them. However,
the result will have poor SIMD utilization as the majority of the loop
iterations don't benefit three out of the four currently running program
instances. Thus, finding ways to structure the computation
so that the currently running program instances have similar desired
control flow paths leads to better overall efficiency.
Gang Convergence
----------------
notion of a single shared PC, ...
Unlike languages such as OpenCL\* and CUDA\*, these executing program
instances are guaranteed to be maximally converged--if two program
instances follow the same control path, they are guaranteed to execute each
operation at the same time. In the presence of divergent control flow:
::
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.
There is thus no need for a ``syncthreads``--type construct to synchronize
the executing program instances in cases where program instances would like
to share data or commicate with each other.
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`` maintains as much execution convergence as
possible; the code executed 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
indefined.
Data Races Within a Gang
------------------------
sequence points, this works since writes from first statement will be seen
as having gone to memory by the second
::
int value = ...;
uniform int v[programCount];
v[programIndex] = value;
value = v[(programIndex+1)%programCount];
Although the SPMD model assumes that program instances are independent, you
can write code that has data races across the program instances. For
example, the following code causes all program instances to try to write
different values to the same location:
::
uniform int array[32] = 0;
int index = 0;
array[index] = programIndex;
In this case, the behavior of the program is undefined.
Uniform Data In A Gang
----------------------
When appropriate, declaring variables as ``uniform`` types can allow the
compiler to produce substantially better code. Consider for example an
image filtering operation where the program loops over adjacent pixels:
::
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.;
}
Under the SPMD execution model, a number of program instances are running
this function in parallel (and in general, we will assume that this
function will end up being called with different values for ``x`` and ``y``
for the running program instances.) However, all of the program instances
will 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. [#]_
.. [#] 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 ``ispc`` isn't yet
this clever. Put another way, the ``ispc`` approach is generally that
the programmer shouldn't have to wonder if the compiler was smart or not
in a particular case, thus avoiding performance surprises.
If these are instead implemented with ``dx`` and ``dy`` declared as
``uniform`` variables, then the ``ispc`` compiler can generate more
efficient code for the loops, taking advantage of the fact that these
values are the same for all program instances.
::
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,
``ispc`` can generate code where all instances always do the same
iterations.
A related benefit comes in ``if`` statements--if the test in an ``if``
statement is purely based on ``uniform`` quantities, 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
------------------------------------------
Operations may be executed even if none of the program instances needs to
run them based on their control flow. Consider an ``if``/``else`` test;
the statements in the ``else`` block may be executed even if the test
evaluates to ``true`` for all of the running program instances. In
general, the executed statements are masked, such that they have no side
effects for the program instances that don't want to be running them, so
there is no visible side-effect of executing the ``else`` statements.
There is, however, one case where this part of the execution model can
become apparent.
Consider the cast of modifying the value of a ``uniform`` variable under
varying control flow:
::
extern void foo();
uniform int a;
if (test) { // varying test
++a; // modifying uniform under varying control flow
foo();
}
When possible, ``ispc`` detects that the control flow is varying and issues
an warning if a uniform variable is modified in this case. Here, ``a`` may
be modified in the above code even if *none* of the program instances
evaluated a true value for the test, given the ``ispc`` execution model.
The ISPC Language
=================
``ispc`` is an extended verion 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 is not directly portable to
``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, `Parallel Execution Model in ISPC`_.
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
comapre 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 verion 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 for the following key features as C:
* Expression syntax and basic types
* Syntax for variable declarations
* Control flow structures: if, for, while, do.
* Pointers, including function pointers, ``void *``, and C's array/pointer
duality (arrays are converted to pointers when passed to functions, etc.)
* Structs and arrays
* Recursion
* Separate compilation
* 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 hint that a function should be inlined
* Function overloading by parameter type
* Hexidecimal floating-point constants
``ispc`` also adds a number of new features that aren't in any of C89, C99,
or C++:
* "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`_)
* Short vector types (see `Short Vector Types`_)
* Parallel ``foreach`` and ``foreach_tiled`` iteration constructs (see
`Parallel Iteration Statements: "foreach" and "foreach_tiled"`_)
* Language support for task parallelism (see `Task Parallel Execution`_)
* A rich standard library, though one that is different than C's (see `The
ISPC Standard Library`_.)
There are a number of features of C89 that are not supported in ``ispc``
but are likely to be supported in future releases:
* Short circuiting of logical operations
* There are no types named ``char``, ``short``, or ``long``. However,
there are built-in ``int8``, ``int16``, and ``int64`` types
* Character constants
* String constants and arrays of characters as strings
* ``switch`` and ``goto`` statements
* ``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``
* The ``volatile`` qualifier
The following C89 features are not expected to be supported in any future
``ispc`` release:
* The ``long double`` type
* "K&R" style function declarations
* The C standard library
* The ``register`` storage class for variables
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``, ``export``, ``cdo``, ``cfor``, ``cif``, ``cwhile``, ``false``,
``foreach``, ``foreach_tiled``, ``inline``, ``int8``, ``int16``, ``int32``,
``int64``, ``launch``, ``print``, ``reference``, ``soa``, ``sync``,
``task``, ``true``, ``uniform``, and ``varying``.
Lexical Structure
-----------------
Tokens in ``ispc`` are delimted by white-space and comments. The
white-space characters are the usual set of spaces, tabs, and carriage
returns/line feeds. Comments can be delinated with ``//``, which starts a
comment that continues to the end of the line, or the start of a comment
can be delinated with ``/*`` and the end with ``*/``. Like in 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 or in hexidecimal.
Base 10 constants are given by a sequence of one or more digits from 0 to
9. Hexidecimal constants are denoted by a leading ``0x`` and then one or
more digits from 0-9, a-f, or A-F.
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 hexidecimal
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 hexidecimal 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 unnecessary.)
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``
- carriabe 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 hexidecimal 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_tiled``, ``goto``, ``if``, ``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 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.
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, ``uniform`` variables
lead to a number of performance advantages when they are applicable (see
`Uniform Variables and Varying Control Flow`_, for example.)
``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;
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 n-wide ``float`` values, where "n"
is the gang size, while the second declaration corresonds to 10 ``float``
values.
Defining New Names For Types
----------------------------
The ``typedef`` keyword can be used to name types:
::
typedef Float3 float[3];
``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.
::
float a = 0;
float *pa = &a;
*pa = 1; // now a == 1
Also as in C, arrays are silently converted into pointers:
::
float a[10] = { ... };
float *pa = a; // pointer to first element of a
float *pb = a + 5; // pointer to 5th element of a
As with other basic types, pointers can be both ``uniform`` and
``varying``. By default, they are varying. 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.
::
uniform float f = 0;
uniform float * uniform pf = &f;
*pf = 1;
A subtlety comes in when 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;
float * uniform pa = &a;
*pa = programIndex; // same as (a = programIndex)
Any pointer type can be explicitly typecast to another pointer type (of the
same uniform/varying-ness.)
::
float *pa = ...;
int *pb = (int *)pa; // legal, but beware
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 to 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``.
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 now 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
``ptr`` is a ``varying`` pointer type (in other words, there each program
instance in the gang has its own unique pointer value)
::
uniform float * varying ptr = ...;
float &r = *ptr; // 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 flexibilty and eliminate
this issue, 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 option 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 enuemrations 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 enuemrant 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
Struct and Array Types
----------------------
More complex data structures can be built using ``struct`` and arrays.
::
struct Foo {
float time;
int flags[10];
};
The size of arrays must be a compile-time constant, though functions can be
declared to take "unsized arrays" as parameters.
::
void foo(float array[], int length);
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;
Declarations and Initializers
-----------------------------
Variables are declared and assigned just as in C:
::
float foo = 0, bar[5];
float bat = func(foo);
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 } };
Structures can also be initialized only with element values in braces:
::
struct Color { float r, g, b; };
....
Color d = { 0.5, .75, 1.0 }; // r = 0.5, ...
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 derefernce 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;
Control Flow
------------
``ispc`` supports most of C's control flow constructs, including ``if``,
``for``, ``while``, ``do``. 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.
``ispc`` does not currently support ``switch`` statements or ``goto``.
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.
Basic Iteration Statements: "for", "while", and "do"
----------------------------------------------------
``ispc`` supports ``for``, ``while``, and ``do`` loops, with the same
specification as in C. Like C++, variables can be declared in the ``for``
statment 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.
"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 it can jump to a simpler code path or otherwise save work.
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.
Parallel Iteration Statements: "foreach" and "foreach_tiled"
------------------------------------------------------------
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.
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 iteraton, 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.
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.
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.
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``.
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.
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 methods to try to find a match.
If a single match of a given type is found, it is used; if multiple matches
of a given type are found, an error is issued.
* All parameter types match exactly.
* All parameter types match exactly, where any reference-type
parameters are considered equivalent to their underlying type.
* Parameters match with only type conversions that don't risk losing any
information (for example, converting an ``int16`` value to an ``int32``
parameter value.)
* Parameters match with only promotions from ``uniform`` to ``varying``
types.
* Parameters match using arbitrary type conversion, without changing
variability from ``uniform`` to ``varying`` (e.g., ``int`` to ``float``,
``float`` to ``int``.)
* Parameters match using arbitrary type conversion, including also changing
variability from ``uniform`` to ``varying`` as needed.
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. (See the ``examples/mandelbrot_tasks`` example to see it used in
a small example.)
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 definitions, there are two ways to write code that launches
tasks, using the ``launch`` construct. 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) >;
Note the ``launch`` keyword and the brackets around the function call.
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] = ...
}
Program execution continues asynchronously after a ``launch`` statement in
a function; thus, a function shouldn't access values being generated by the
tasks it has launched within the function without synchronization. If
results are needed before function return, a function can use a ``sync``
statement to wait for all launched tasks to finish:
::
launch[100] < func2(a) >;
sync;
// now safe to use computed values in a[]...
Alternatively, any function that launches tasks has an automatically-added
``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.
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.
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 implmenting 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 count);
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`` functon, 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 aize 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 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 thie 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 ``count`` is the number of instances of this function to
enqueue for asynchronous execution. (In other words, ``count`` corresponds
to the value ``n`` in a multiple-task launch statement like ``launch[n]``.)
The signature of the provided function pointer ``f`` is
::
void (*TaskFuncPtr)(void *data, int threadIndex, int threadCount,
int taskIndex, int taskCount)
When this function pointer is called by one of the hardware threads managed
bythe 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 number of tasks launched in the
``launch`` statement that caused the call to ``ISPCLaunch()`` and each of
the calls to this function should be given a unique value of ``taskIndex``
between zero and ``taskCount``, 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.)
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
``icc`` 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)
Bit-Level 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);
}
It, it 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.
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)
Arctangent functions are also available:
::
float atan(float x)
float atan2(float x, float y)
uniform float atan(uniform float x)
uniform float atan2(uniform float x, uniform float y)
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, float * uniform s, 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)
Some 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, int * uniform pw2)
uniform float frexp(uniform float x,
uniform int * uniform pw2)
Pseudo-Random Numbers
---------------------
A simple random number generator is provided. State for the RNG
is maintained in an instance of the ``RNGState`` structure, which is seeded
with ``seed_rng()``.
::
struct RNGState;
unsigned int random(RNGState * uniform state)
float frandom(RNGState * uniform state)
void seed_rng(RNGState * uniform state, uniform int seed)
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 garabge 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 true 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 true 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
---------------------------------
Usually, ``ispc`` code expresses independent programs performing
computation on separate data elements. There are, however, a number of
cases 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.
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 SIMD 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 ``offset`` has the value (1, 2, 3, 4, 5,
6, 7, 8) in each of the 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
``programCount`` (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)
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 ``programCount-1``.
::
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 ``2*programCount-1`` 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 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 few routines that 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,
and ``all()`` returns ``true`` if it true for all of them.
::
uniform bool any(bool v)
uniform bool all(bool v)
You can also compute a variety of reductions across the program instances.
For example, the values in each of the SIMD lanes ``x`` are added together
by ``reduce_add()``. If this function is called under control flow, it
only adds the values for the currently active program instances.
::
uniform float reduce_add(float x)
uniform int reduce_add(int x)
uniform unsigned int reduce_add(unsigned int x)
You can also use functions to compute the minimum and maximum value of the
given value across all of the currently-executing vector lanes.
::
uniform float reduce_min(float a)
uniform int32 reduce_min(int32 a)
uniform unsigned int32 reduce_min(unsigned int32 a)
uniform double reduce_min(double a)
uniform int64 reduce_min(int64 a)
uniform unsigned int64 reduce_min(unsigned int64 a)
uniform float reduce_max(float a)
uniform int32 reduce_max(int32 a)
uniform unsigned int32 reduce_max(unsigned int32 a)
uniform double reduce_max(double a)
uniform int64 reduce_max(int64 a)
uniform unsigned int64 reduce_max(unsigned int64 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(float v)
uniform bool reduce_equal(int64 v)
uniform bool reduce_equal(unsigned int64 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.
::
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(float v, uniform float * 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(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 preceeding 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 = 0; 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)
Data Conversions And Storage
----------------------------
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. 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_load_active(uniform int * uniform base,
int * uniform val)
uniform int packed_load_active(uniform unsigned int * uniform base,
unsigned int * uniform val)
uniform int packed_store_active(uniform int * uniform base,
int val)
uniform int packed_store_active(uniform unsigned int * uniform base,
unsigned int val)
As an example of how these functions can be used, the following code shows
the use of ``packed_store_active()``. The program instances that are
executing each compute some value ``x``; we'd like to record the program
index values of the program instances for which ``x`` is less than zero, if
any. In following the code, the ``programIndex`` value for each program
instance is written into the ``ids`` array only if ``x < 0`` for that
program instance. The total number of values written into ``ids`` is
returned from ``packed_store_active()``.
::
uniform int ids[100];
uniform int offset = 0;
float x = ...;
if (x < 0)
offset += packed_store_active(&ids[offset], programIndex);
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 `Understanding How to Interoperate With the
Application's Data`_ 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 ``3*programCount`` 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[], float * uniform v0,
float * uniform v1, float * uniform v2)
void aos_to_soa3(uniform int32 a[], int32 * uniform v0,
int32 * uniform v1, 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 ``4*programCount`` values from the given array,
starting at the given offset.
::
void aos_to_soa4(uniform float a[], float * uniform v0, float * uniform v1,
float * uniform v2, float * uniform v3)
void aos_to_soa4(uniform int32 a[], int32 * uniform v0, int32 * uniform v1,
int32 * uniform v2, 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 the 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)
Systems Programming Support
---------------------------
Atomic Operations and Memory Fences
-----------------------------------
The usual range of atomic memory operations are provided in ``ispc``, with
a few variants to handle both uniform and varying types. As a first
example, consider the 32-bit integer atomic add routine:
::
int32 atomic_add_global(uniform int32 * uniform ptr, int32 delta)
The semantics are the expected ones for an atomic add function: the pointer
points to a single location in memory (the same one for all program
instances), and fore each executing program instance, the "val" has that
program instance's value "delta" added to it atomically, and the old value
of "val" is returned from the function. (Thus, 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.)
One thing to note is that that the type of the value being added to here 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 of ``val`` 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.
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. (The ``atomic_swap_global()``
function can be used with ``float`` and ``double`` types as well.)
::
int32 atomic_add_global(uniform int32 * uniform ptr, int32 value)
int32 atomic_subtract_global(uniform int32 * uniform ptr, int32 value)
int32 atomic_min_global(uniform int32 * uniform ptr, int32 value)
int32 atomic_max_global(uniform int32 * uniform ptr, int32 value)
int32 atomic_and_global(uniform int32 * uniform ptr, int32 value)
int32 atomic_or_global(uniform int32 * uniform ptr, int32 value)
int32 atomic_xor_global(uniform int32 * uniform ptr, int32 value)
int32 atomic_swap_global(uniform int32 * uniform ptr, int32 value)
There are also variants of these functions 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_global(uniform int32 * uniform ptr,
uniform int32 value)
uniform int32 atomic_subtract_global(uniform int32 * uniform ptr,
uniform int32 value)
uniform int32 atomic_min_global(uniform int32 * uniform ptr,
uniform int32 value)
uniform int32 atomic_max_global(uniform int32 * uniform ptr,
uniform int32 value)
uniform int32 atomic_and_global(uniform int32 * uniform ptr,
uniform int32 value)
uniform int32 atomic_or_global(uniform int32 * uniform ptr,
uniform int32 value)
uniform int32 atomic_xor_global(uniform int32 * uniform ptr,
uniform int32 value)
uniform int32 atomic_swap_global(uniform int32 * uniform ptr,
uniform int32 newval)
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_global(uniform int32 * varying ptr, int32 value)
int32 atomic_subtract_global(uniform int32 * varying ptr, int32 value)
int32 atomic_min_global(uniform int32 * varying ptr, int32 value)
int32 atomic_max_global(uniform int32 * varying ptr, int32 value)
int32 atomic_and_global(uniform int32 * varying ptr, int32 value)
int32 atomic_or_global(uniform int32 * varying ptr, int32 value)
int32 atomic_xor_global(uniform int32 * varying ptr, int32 value)
int32 atomic_swap_global(uniform int32 * varying ptr, int32 value)
There are also an atomic swap and "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`` and ``double`` variants as well.)
::
int32 atomic_swap_global(uniform int32 * uniform ptr, int32 newvalue)
uniform int32 atomic_swap_global(uniform int32 * uniform ptr,
uniform int32 newvalue)
int32 atomic_compare_exchange_global(uniform int32 * uniform ptr,
int32 compare, int32 newval)
uniform int32 atomic_compare_exchange_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();
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
------------------
A routine is available to find the number of CPU cores available in the
system:
::
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.
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
}
}
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 {
uniform int count;
uniform float pos[3];
};
If the ``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`` prohibits any varying types from being used in
parameters to functions with the ``export`` qualifier. (``ispc`` also
prohibits passing structures that themselves have varying types as members,
etc.) Thus, all datatypes that is shared with the application must have
the ``uniform`` qualifier applied to them. (See `Understanding How to
Interoperate With the Application's Data`_ for more discussion of how to
load vectors of SoA or AoSoA data from the application.)
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 {
uniform float * uniform foo, * uniform bar;
};
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 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 if 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 betwen 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/perf.html
Understanding How to Interoperate With the Application's Data
-------------------------------------------------------------
One of ``ispc``'s key goals is to be able to interoperate with the
application's data, in whatever layout it is stored in. You don't need to
worry about reformatting of data or the overhead of a driver model that
abstracts the data layout. This section illustrates some of the
alternatives with a simple example of computing the length of a large
number of vectors.
Consider for starters a ``Vector`` data-type, defined in C as:
::
struct Vector { float x, y, z; };
We might have (still in C) an array of ``Vector`` s defined like this:
::
Vector vectors[1024];
This is called an "array of structures" (AoS) layout. To compute the
lengths of these vectors in parallel, you can write ``ispc`` code like
this:
::
export void length(Vector vectors[1024], uniform float len[]) {
foreach (index = 0 ... 1024) {
float x = vectors[index].x;
float y = vectors[index].y;
float z = vectors[index].z;
float l = sqrt(x*x + y*y + z*z);
len[index] = l;
}
}
The problem with this implementation is that the indexing into the array of
structures, ``vectors[index].x`` is relatively expensive. On a target
machine that supports four-wide Intel® SSE, this turns into four loads of
single ``float`` values from non-contiguous memory locations, which are
then packed into a four-wide register corresponding to ``float x``. Once the
values are loaded into the local ``x``, ``y``, and ``z`` variables,
SIMD-efficient computation can proceed; getting to that point is
relatively inefficient.
(As described previously in `Converting Between Array-of-Structures and
Structure-of-Arrays Layout`_, this computation could be written more
efficiently using standard library routines to convert from the AoS layout,
if we were given a flat array of ``float`` values.)
An alternative data layout would be the "structure of arrays" (SoA). In C,
the data would be declared as:
::
float x[1024], y[1024], z[1024];
The ``ispc`` code might be:
::
export void length(uniform float x[1024], uniform float y[1024],
uniform float z[1024], uniform float len[]) {
foreach (index = 0 ... 1024) {
float xx = x[index];
float yy = y[index];
float zz = z[index];
float l = sqrt(xx*xx + yy*yy + zz*zz);
len[index] = l;
}
}
In this example, the loads into ``xx``, ``yy``, and ``zz`` are single
vector loads of an entire gang's worth of values into the corresponding
registers. This processing is more efficient than the multiple scalar
loads that are required with the AoS layout above.
A final alternative is "array of structures of arrays" (AoSoA), a hybrid
between these two. A structure is declared that stores a small number of
``x``, ``y``, and ``z`` values in contiguous memory locations:
::
struct Vector16 {
float x[16], y[16], z[16];
};
The ``ispc`` code has an outer loop over ``Vector16`` elements and
then an inner loop that peels off values from the element members:
::
#define N_VEC (1024/16)
export void length(Vector16 v[N_VEC], uniform float len[]) {
foreach (i = 0 ... N_VEC, j = 0 ... 16) {
float x = v[i].x[j];
float y = v[i].y[j];
float z = v[i].z[j];
float l = sqrt(x*x + y*y + z*z);
len[16*i+j] = l;
}
}
}
One advantage of the AoSoA layout is that the memory accesses to load
values are to nearby memory locations, where as with SoA, each of the three
loads above is to locations separated by a few thousand bytes. Thus, AoSoA
can be more cache friendly. For structures with many members, this
difference can lead to a substantial improvement.
With some additional complexity, ``ispc`` can also generate code that
efficiently processes data in AoSoA layout where the inner array length is
less than the machine vector width. For example, consider doing
computation with this AoSoA structure definition on a machine with an
8-wide vector unit (for example, an Intel® AVX target):
::
struct Vector4 {
float x[4], y[4], z[4];
};
The ``ispc`` code to process this loads elements four at a time from
``Vector4`` instances until it has a full ``programCount`` number of
elements to work with and then proceeds with the computation.
::
#define N_VEC (1024/4)
export void length(Vector4 v[N_VEC], uniform float len[]) {
for (uniform int i = 0; i < N_VEC; i += programCount / 4) {
float x, y, z;
for (uniform int j = 0; j < programCount / 4; ++j) {
if (programIndex >= 4 * j &&
programIndex < 4 * (j+1)) {
int index = (programIndex & 0x3);
x = v[i+j].x[index];
y = v[i+j].y[index];
z = v[i+j].z[index];
}
}
float l = sqrt(x*x + y*y + z*z);
len[4*i + programIndex] = l;
}
}
Related Languages
=================
TODO: rsl, C*, IVL
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specifications. Current characterized errata are available on request.
Contact your local Intel sales office or your distributor to obtain the latest
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differentiate features within each processor family, not across different
processor families. See http://www.intel.com/products/processor_number for
details.
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Copyright(C) 2011, Intel Corporation. All rights reserved.
Optimization Notice
===================
Intel compilers, associated libraries and associated development tools may
include or utilize options that optimize for instruction sets that are
available in both Intel and non-Intel microprocessors (for example SIMD
instruction sets), but do not optimize equally for non-Intel
microprocessors. In addition, certain compiler options for Intel
compilers, including some that are not specific to Intel
micro-architecture, are reserved for Intel microprocessors. For a detailed
description of Intel compiler options, including the instruction sets and
specific microprocessors they implicate, please refer to the "Intel
Compiler User and Reference Guides" under "Compiler Options." Many library
routines that are part of Intel compiler products are more highly optimized
for Intel microprocessors than for other microprocessors. While the
compilers and libraries in Intel compiler products offer optimizations for
both Intel and Intel-compatible microprocessors, depending on the options
you select, your code and other factors, you likely will get extra
performance on Intel microprocessors.
Intel compilers, associated libraries and associated development tools may
or may not optimize to the same degree for non-Intel microprocessors for
optimizations that are not unique to Intel microprocessors. These
optimizations include Intel® Streaming SIMD Extensions 2 (Intel® SSE2),
Intel® Streaming SIMD Extensions 3 (Intel® SSE3), and Supplemental
Streaming SIMD Extensions 3 (Intel SSSE3) instruction sets and other
optimizations. Intel does not guarantee the availability, functionality,
or effectiveness of any optimization on microprocessors not manufactured by
Intel. Microprocessor-dependent optimizations in this product are intended
for use with Intel microprocessors.
While Intel believes our compilers and libraries are excellent choices to
assist in obtaining the best performance on Intel and non-Intel
microprocessors, Intel recommends that you evaluate other compilers and
libraries to determine which best meet your requirements. We hope to win
your business by striving to offer the best performance of any compiler or
library; please let us know if you find we do not.
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