These compute the average of two given values, rounding up and down,
respectively, if the result isn't exact. When possible, these are
mapped to target-specific intrinsics (PADD[BW] on IA and VH[R]ADD[US]
on NEON.)
A subsequent commit will add pattern-matching to generate calls to
these intrinsincs when the corresponding patterns are detected in the
IR.)
Like SSE4-8 and SSE4-16, these use 8-bit and 16-bit values for mask
elements, respectively, and thus should generate the best code when used
for computation with datatypes of those sizes.
Along the lines of sse4-8, this is an 8-wide target for SSE4, using
16-bit elements for the mask. It's thus (in principle) the best
target for SIMD computation with 16-bit datatypes.
This change adds a new 'sse4-8' target, where programCount is 16 and
the mask element size is 8-bits. (i.e. the most appropriate sizing of
the mask for SIMD computation with 8-bit datatypes.)
There were a number of places throughout the system that assumed that the
execution mask would only have either 32-bit or 1-bit elements. This
commit makes it possible to have a target with an 8- or 16-bit mask.
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.
The stdilb code just calls the signed int{32,64} functions,
which gives the right result for the unsigned case anyway.
The various targets didn't consistently define the unsigned
variants in any case.
For KNC (gather/scatter), it's not helpful to factor base+offsets gathers
and scatters into base_ptr + {1/2/4/8} * varying_offsets + const_offsets.
Now, if a HW instruction is available for gather/scatter, we just factor
into base + {1/2/4/8} * offsets (if possible). Not only is this simpler,
but it's also what we need to pass a value along to the scale by
2/4/8 available directly in those instructions.
Finishes issue #325.
We now have two ways of approaching gather/scatters with a common base
pointer and with offset vectors. For targets with native gather/scatter,
we just turn those into base + {1/2/4/8}*offsets. For targets without,
we turn those into base + {1/2/4/8}*varying_offsets + const_offsets,
where const_offsets is a compile-time constant.
Infrastructure for issue #325.
No functional change; just preparation for having a path that doesn't
factor the offsets into constant and varying parts, which will be better
for AVX2 and KNC.
