Change register blocking for SGEMM (and STRMM) on z14 from 8x4 to 16x4
by adjusting SGEMM_DEFAULT_UNROLL_M and choosing the appropriate copy
implementations. Actually make KERNEL.Z14 more flexible, so that the
change in param.h suffices. As a result, performance for SGEMM improves
by around 30% on z15.
On z14, FP SIMD instructions can operate on float-sized scalars in
vector registers, while z13 could do that for double-sized scalars only.
Thus, we can double the amount of elements of C that are held in
registers in an SGEMM kernel.
Signed-off-by: Marius Hillenbrand <mhillen@linux.ibm.com>
As shown in #2538, default buffersizes on some platforms were smaller than required in memory.c
and the requirement could never be fulfilled for a calculated GEMM_R on PPC given the fomula used
There is currently no simple way to query cache sizes on ARMV8, so this takes the number of cores as a trivial indication if the target is a server-class device with a big cache, or just a single-board toy or smartphone.
fixes:
gemm.c: In function 'sgemm_':
../common_param.h:981:18: error: 'SGEMM_DEFAULT_P' undeclared (first use in this function)
#define SGEMM_P SGEMM_DEFAULT_P
^
OpenBLAS has a fancy algorithm for copying the input data while laying
it out in a more CPU friendly memory layout.
This is great for large matrixes; the cost of the copy is easily
ammortized by the gains from the better memory layout.
But for small matrixes (on CPUs that can do efficient unaligned loads) this
copy can be a net loss.
This patch adds (for SKYLAKEX initially) a "sgemm direct" mode, that bypasses
the whole copy machinary for ALPHA=1/BETA=0/... standard arguments,
for small matrixes only.
What is small? For the non-threaded case this has been measured to be
in the M*N*K = 28 * 512 * 512 range, while in the threaded case it's
less, around M*N*K = 1 * 512 * 512
ARMv8 builds were a bit mixed up, with ThunderX2 code in ARMv8 mode
(which is not right because TX2 is ARMv8.1) as well as requiring a few
redundancies in the defines, making it harder to maintain and understand
what core has what. A few other minor issues were also fixed.
Tests were made on the following cores: A53, A57, A72, Falkor, ThunderX,
ThunderX2, and XGene.
Tests were: OpenBLAS/test, OpenBLAS/benchmark, BLAS-Tester.
A summary:
* Removed TX2 code from ARMv8 build, to make sure it is compatible with
all ARMv8 cores, not just v8.1. Also, the TX2 code has actually
harmed performance on big cores.
* Commoned up ARMv8 architectures' defines in params.h, to make sure
that all will benefit from ARMv8 settings, in addition to their own.
* Adding a few more cores, using ARMv8's include strategy, to benefit
from compiler optimisations using mtune. Also updated cache
information from the manuals, making sure we set good conservative
values by default. Removed Vulcan, as it's an alias to TX2.
* Auto-detecting most of those cores, but also updating the forced
compilation in getarch.c, to make sure the parameters are the same
whether compiled natively or forced arch.
Benefits:
* ARMv8 build is now guaranteed to work on all ARMv8 cores
* Improved performance for ARMv8 builds on some cores (A72, Falkor,
ThunderX1 and 2: up to 11%) over current develop
* Improved performance for *all* cores comparing to develop branch
before TX2's patch (9% ~ 36%)
* ThunderX1 builds are 14% faster than ARMv8 on TX1, 9% faster than
current develop's branch and 8% faster than deveop before tx2 patches
Issues:
* Regression from current develop branch for A53 (-12%) and A57 (-3%)
with ARMv8 builds, but still faster than before TX2's commit (+15%
and +24% respectively). This can be improved with a simplification of
TX2's code, to be done in future patches. At least the code is
guaranteed to be ARMv8.0 now.
Comments:
* CortexA57 builds are unchanged on A57 hardware from develop's branch,
which makes sense, as it's untouched.
* CortexA72 builds improve over A57 on A72 hardware, even if they're
using the same includes due to new compiler tunning in the makefile.
The current gemm threading code can make very unfortunate choices, for
example on my 10 core system a 1024x1024x1024 matrix multiply ends up
chunking into blocks of 102... which is not a vector friendly size
and performance ends up horrible.
this patch adds a helper define where an architecture can specify
a preference for size multiples.
This is different from existing defines that are minimum sizes and such.
The performance increase with this patch for the 1024x1024x1024 sgemm
is 2.3x (!!)
Marius Hillenbrand
Martin Kroeker
wjc404
Ali Saidi
Wang,Long
AbdelRauf
pkubaj
maomao194313
ken-cunningham-webuse
Arjan van de Ven
Renato Golin
Ashwin Sekhar T K