Initial support for ARM NEON on Cortex-A9 and A15 CPUs. All but ~10 tests
pass, and all examples compile and run correctly. Most of the examples
show a ~2x speedup on a single A15 core versus scalar code.
Current open issues/TODOs
- Code quality looks decent, but hasn't been carefully examined. Known
issues/opportunities for improvement include:
- fp32 vector divide is done as a series of scalar divides rather than
a vector divide (which I believe exists, but I may be mistaken.)
This is particularly harmful to examples/rt, which only runs ~1.5x
faster with ispc, likely due to long chains of scalar divides.
- The compiler isn't generating a vmin.f32 for e.g. the final scalar
min in reduce_min(); instead it's generating a compare and then a
select instruction (and similarly elsewhere).
- There are some additional FIXMEs in builtins/target-neon.ll that
include both a few pieces of missing functionality (e.g. rounding
doubles) as well as places that deserve attention for possible
code quality improvements.
- Currently only the "cortex-a9" and "cortex-15" CPU targets are
supported; LLVM supports many other ARM CPUs and ispc should provide
access to all of the ones that have NEON support (and aren't too
obscure.)
- ~5 of the reduce-* tests hit an assertion inside LLVM (unfortunately
only when the compiler runs on an ARM host, though).
- The Windows build hasn't been tested (though I've tried to update
ispc.vcxproj appropriately). It may just work, but will more likely
have various small issues.)
- Anything related to 64-bit ARM has seen no attention.
They're all based off a common examples/common.mk file, so that individual
makefiles are quite simple now.
The common.mk file also provides targets to build the examples using C++
output with the generic-16h or sse4.h files. These targets don't run by
default, but do run if 'make all' is run.
These make it easier to iterate over arbitrary amounts of data
elements; specifically, they automatically handle the "ragged
extra bits" that come up when the number of elements to be
processed isn't evenly divided by programCount.
TODO: documentation
Pointers can be either uniform or varying, and behave correspondingly.
e.g.: "uniform float * varying" is a varying pointer to uniform float
data in memory, and "float * uniform" is a uniform pointer to varying
data in memory. Like other types, pointers are varying by default.
Pointer-based expressions, & and *, sizeof, ->, pointer arithmetic,
and the array/pointer duality all bahave as in C. Array arguments
to functions are converted to pointers, also like C.
There is a built-in NULL for a null pointer value; conversion from
compile-time constant 0 values to NULL still needs to be implemented.
Other changes:
- Syntax for references has been updated to be C++ style; a useful
warning is now issued if the "reference" keyword is used.
- It is now illegal to pass a varying lvalue as a reference parameter
to a function; references are essentially uniform pointers.
This case had previously been handled via special case call by value
return code. That path has been removed, now that varying pointers
are available to handle this use case (and much more).
- Some stdlib routines have been updated to take pointers as
arguments where appropriate (e.g. prefetch and the atomics).
A number of others still need attention.
- All of the examples have been updated
- Many new tests
TODO: documentation
Makefile and vcxproj file updates.
Also modified vcxproj files so that the various files ispc generates go into $(TargetDir),
not the current directory.
Modified the ray tracer example to not have uniform short-vector types in its app-visible
datatypes (these are laid out differently on SSE vs AVX); there was an existing lurking
bug in the way this was done before.
Within each function that launches tasks, we now can easily track which
tasks that function launched, so that the sync at the end of the function
can just sync on the tasks launched by that function (not all tasks
launched by all functions.)
Implementing this led to a rework of the task system API that ispc generates
code to call; the example task systems in examples/tasksys.cpp have been
updated to conform to this API. (The updated API is also documented in
the ispc user's guide.)
As part of this, "launch[n]" syntax was added to launch a number of tasks
in a single launch statement, rather than requiring a loop over 'n' to
launch n tasks.
This commit thus fixes issue #84 (enhancement to launch multiple tasks from
a single launch statement) as well as issue #105 (recursive task launches
were broken).
fp constant undesirably causing computation to be done in double precision.
Makes C scalar versions of the options pricing models, rt, and aobench 3-5% faster.
Makes scalar version of noise about 15% faster.
Others are unchanged.
- Only have a single copy of all of the tasks_*.cpp sample implementations,
stored in examples/.
- Reduce dynamic storage allocation and locking in task launch code paths.
- Don't have a hard limit of the number of tasks that can be launched on
Windows (fix issue #85).
Modified this example to use reduce_equal() to see if all of the program
instances want to load the 8 sample values around the same voxel. When
this is the case, we can just do 8 scalar loads, rather than needing to
do a fully general gather. Once this check fails, it isn't done again,
since it's not likely to start succeeding in the future. This gives
a ~10% speedup with the low-res data set, and basically no performance
difference with the high-res one. (It makes sense that the lower-resolution
the voxel sampling, the longer all of the rays will stay in the same set
of voxels.)
