Benchmark example using Intel MKL (for history) about laser

[Laurae2]

Newer results:

cd Downloads/Nim
rm -rf laser
source /opt/intel/mkl/bin/mklvars.sh intel64
export OMP_NUM_THREADS=1
git clone --recursive git://github.com/numforge/laser
cd laser
git checkout dbfb31d
git submodule init
git submodule update

cd build
gedit benchmarks/third_party/blas.nim
gedit benchmarks/gemm/gemm_bench_float32.nim
gedit laser/primitives/matrix_multiplication/gemm_tiling.nim

export OMP_NUM_THREADS=72
rm -rf build
mkdir build
LD_LIBRARY_PATH=/opt/intel/compilers_and_libraries_2019.0.117/linux/mkl/lib/intel64_lin nim cpp --dynlibOverride:libmkl_intel_ilp64 --passL:"/opt/intel/compilers_and_libraries_2019.0.117/linux/mkl/lib/intel64_lin/libmkl_intel_ilp64.a -Wl,--no-as-needed -lmkl_intel_ilp64 -lmkl_gnu_thread -lmkl_core -lgomp -lpthread -lm -ldl" --passC:"-D_GNU_SOURCE -L$MKLROOT/lib/intel64_lin -DMKL_ILP64 -m64" -r -d:release -d:openmp -o:build/bench_gemm benchmarks/gemm/gemm_bench_float32.nim

Results (OpenBLAS = MKL):

Hint: /home/laurae/Downloads/Nim/laser/build/bench_gemm  [Exec]

A matrix shape: (M: 1920, N: 1920)
B matrix shape: (M: 1920, N: 1920)
Output shape: (M: 1920, N: 1920)
Required number of operations: 14155.776 millions
Required bytes:                   29.491 MB
Arithmetic intensity:            480.000 FLOP/byte
Theoretical peak single-core:    179.200 GFLOP/s
Theoretical peak multi:         6451.200 GFLOP/s
Make sure to not bench Apple Accelerate or the default Linux BLAS.

OpenBLAS benchmark
Collected 10000 samples in 52.753 seconds
Average time: 3.492 ms
Stddev  time: 0.736 ms
Min     time: 3.162 ms
Max     time: 31.532 ms
Perf:         4053.552 GFLOP/s

Laser production implementation
Collected 10000 samples in 131.145 seconds
Average time: 11.152 ms
Stddev  time: 8.307 ms
Min     time: 7.360 ms
Max     time: 132.827 ms
Perf:         1269.368 GFLOP/s

PyTorch Glow: libjit matmul implementation (with AVX+FMA)
Collected 10000 samples in 2277.353 seconds
Average time: 227.735 ms
Stddev  time: 4.743 ms
Min     time: 224.159 ms
Max     time: 249.707 ms
Perf:         62.159 GFLOP/s

MKL-DNN reference GEMM benchmark
Collected 10000 samples in 268.515 seconds
Average time: 24.684 ms
Stddev  time: 6.915 ms
Min     time: 21.277 ms
Max     time: 86.476 ms
Perf:         573.477 GFLOP/s

MKL-DNN JIT AVX benchmark
Collected 10000 samples in 89.331 seconds
Average time: 6.755 ms
Stddev  time: 4.773 ms
Min     time: 5.215 ms
Max     time: 77.110 ms
Perf:         2095.728 GFLOP/s

MKL-DNN JIT AVX512 benchmark
Collected 10000 samples in 61.314 seconds
Average time: 4.260 ms
Stddev  time: 4.065 ms
Min     time: 3.071 ms
Max     time: 60.712 ms
Perf:         3322.757 GFLOP/s
Mean Relative Error compared to vendor BLAS: 4.056792022311129e-06