This fixes the build and tests on `NEOVERSEV1` target, which was failing
with specific constants for `SBGEMM`

Co-authored-by: Ye Tao <ye.tao@arm.com>

Previously dynamic builds were either using the default SWITCH_RATIO
or one from the higher level architecture; this patch ensures the
dynamic builds can use this parameter as well.

1. Use UZP instructions but not gather load and scatter store instructions to get lower latency.
    2. Padding k to a power of 4.

Enable new build target platform -- COOPERLAKE. This target platform
supports all the SKYLAKEX supported ISAs + avx512bf16. So all the
SKYLAKEX specific kernels/drivers and related code are now extended
to be also active on COOPERLAKE. Besides, new BF16 related kernels
are active under this target.

This patch adds support for bfloat16 data type matrix multiplication kernel.
For architectures that don't support bfloat16, it is defined as unsigned short
(2 bytes).  Default unroll sizes can be changed as per architecture as done for
SGEMM and for now 8 and 4 are used for M and N.  Size of ncopy/tcopy can be
changed as per architecture requirement and for now, size 2 is used.

Added shgemm in kernel/power/KERNEL.POWER9 and tested in powerpc64le and
powerpc64.  For reference, added a small test compare_sgemm_shgemm.c to compare
sgemm and shgemm output.

This patch does not cover OpenBLAS test, benchmark and lapack tests for shgemm.
Complex type implementation can be discussed and added once this is approved.

Serialize accesses to parallelized level3 functions from multiple cal…

for #1851

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 (!!)

a few places in the gemm scheduler code were missing barriers;
the code likely worked OK due to heavy use of volatile / _Atomic
but there's no reason to get this incorrect

The use of _Atomic leads to really bad code generation in the compiler
(on x86, you get 2 "mfence" memory barriers around each access with gcc8, despite
x86 being ordered and cache coherent). But there's a fallback in the code that
just uses volatile which is more than plenty in practice.

If we're nervous about cross thread synchronization for these variables, we should
make the YIELD function be a compiler/memory barrier instead.

performance before (after last commit)

   Matrix          SGEMM cycles    MPC                                   DGEMM cycles      MPC
  48 x 48               10630.0   10.6       0.7%                             18112.8      6.2      -0.7%
  64 x 64               20374.8   13.0       1.9%                             40487.0      6.5       0.4%
  65 x 65              141955.2    1.9    -428.3%                            146708.8      1.9    -179.2%
  80 x 80              178921.1    2.9    -369.6%                            186032.7      2.8    -156.6%
  96 x 96              205436.2    4.3    -233.4%                            224513.1      3.9     -97.0%
 112 x 112             244408.2    5.8    -162.7%                            262158.7      5.4     -47.1%
 128 x 128             321334.5    6.5    -141.3%                            333829.0      6.3     -29.2%

Performance with this patch (roughly a 2x improvement):

   Matrix          SGEMM cycles    MPC                                   DGEMM cycles      MPC
  48 x 48               10756.0   10.5      -0.5%                             18296.7      6.1      -1.7%
  64 x 64               20490.0   12.9       1.4%                             40615.0      6.5       0.0%
  65 x 65               83528.3    3.3    -210.9%                             96319.0      2.9     -83.3%
  80 x 80              101453.5    5.1    -166.3%                            128021.7      4.0     -76.6%
  96 x 96              149795.1    5.9    -143.1%                            168059.4      5.3     -47.4%
 112 x 112             191481.2    7.3    -105.8%                            204165.0      6.9     -14.6%
 128 x 128             265019.2    7.9     -99.0%                            272006.4      7.7      -5.3%

The jobs array is getting initialized in O(compiled cpus^2) complexity.
Distros and people with bigger systems will use pretty high values
(128 or 256 or more) for this value, leading to interesting bubbles
in performance.

Baseline (single threaded performance) gets roughly 13 - 15 multiplications per cycle
in the interesting range (threading kicks in at 65x65 mult by 65x65).
The hardware is capable of 32 multiplications per cycle theoretically.

   Matrix          SGEMM cycles    MPC                                   DGEMM cycles      MPC
  48 x 48               10703.9   10.6       0.0%                             17990.6      6.3       0.0%
  64 x 64               20778.4   12.8       0.0%                             40629.2      6.5       0.0%
  65 x 65               26869.9   10.3       0.0%                             52545.7      5.3       0.0%
  80 x 80               38104.5   13.5       0.0%                             72492.7      7.1       0.0%
  96 x 96               61626.4   14.4       0.0%                            113983.8      7.8       0.0%
 112 x 112              91803.8   15.3       0.0%                            180987.3      7.8       0.0%
 128 x 128             133161.4   15.8       0.0%                            258374.3      8.1       0.0%

When threading is turned on
TARGET=SKYLAKEX F_COMPILER=GFORTRAN  SHARED=1 DYNAMIC_THREADS=1 USE_OPENMP=0  NUM_THREADS=128

  Matrix          SGEMM cycles    MPC                                   DGEMM cycles      MPC
  48 x 48               10725.9   10.5      -0.2%                             18134.9      6.2      -0.8%
  64 x 64               20500.6   12.9       1.3%                             40929.1      6.5      -0.7%
  65 x 65             2040832.1    0.1   -7495.2%                           2097633.6      0.1   -3892.0%
  80 x 80             2063129.1    0.2   -5314.4%                           2119925.2      0.2   -2824.3%
  96 x 96             2070374.5    0.4   -3259.6%                           2173604.4      0.4   -1806.9%
 112 x 112            2111721.5    0.7   -2169.6%                           2263330.8      0.6   -1170.0%
 128 x 128            2276181.5    0.9   -1609.3%                           2377228.9      0.9    -820.1%

There is a deep deep cliff once you hit 65x65

With this patch

   Matrix          SGEMM cycles    MPC                                   DGEMM cycles      MPC
  48 x 48               10630.0   10.6       0.7%                             18112.8      6.2      -0.7%
  64 x 64               20374.8   13.0       1.9%                             40487.0      6.5       0.4%
  65 x 65              141955.2    1.9    -428.3%                            146708.8      1.9    -179.2%
  80 x 80              178921.1    2.9    -369.6%                            186032.7      2.8    -156.6%
  96 x 96              205436.2    4.3    -233.4%                            224513.1      3.9     -97.0%
 112 x 112             244408.2    5.8    -162.7%                            262158.7      5.4     -47.1%
 128 x 128             321334.5    6.5    -141.3%                            333829.0      6.3     -29.2%

The cliff is very significantly reduced.
(more to follow)

Change-Id: Id3fa4e8d9eedd4ef7230df69b611e7f397301a42

Suggested by dodomorandi in #660

Allows maximum use of available cores if one of M and N is small and the other is large.

Signed-off-by: Timothy Gu <timothygu99@gmail.com>

I used a smaller threshold since the stack size is 1MB on windows.

When NUM_THREADS(MAX_CPU_NUNBERS) is very large ,e.g. 256.

typedef struct {
  volatile BLASLONG working[MAX_CPU_NUMBER][CACHE_LINE_SIZE * DIVIDE_RATE];
} job_t;

job_t          job[MAX_CPU_NUMBER];

The job array is equal 8MB.

Thus, We use malloc instead of stack allocation.