Benchmark for sparse-dense matrix multiplications

Benchmark for matrix multiplications between dense and block sparse (BSR) matrix in TVM, blocksparse (Gray et al.) and cuSparse.

Please refer to our paper for details.

Benchmark for TVM:

python3 test_topi_sparse.py --help
usage: test_topi_sparse.py [-h] [--n_trial N_TRIAL] [--repeat REPEAT] [--tune]
                           [--autotvm_log AUTOTVM_LOG]
                           {PEP,PTP,PROB,PRWB,PRWB_AT}

Positional arguments:

PEP       Per Element Parallization  
PTP       Per Tile Paralliza-tion.  
PROB      Parallel Reduction Over Blocks. 
PRWB      Parallel Reduction With Blocks.  
PRWB_AT   Parallel Reduction Within Blocks + AutoTuning

Optional arguments:

  -h, --help            show this help message and exit
  --n_trial N_TRIAL     Number of trials for AutoTVM
  --repeat REPEAT       Number of repeat for AutoTVM to profile on the device
  --tune                Enable AutoTVM tuning for setting PRWB_AT
  --autotvm_log AUTOTVM_LOG
                        Log file for auto tuning

Benchmark for blocksparse [Gray et al., 2017]:

python3 test_blocksparse_gray.py

Benchmark for cuSparse:

cd cusparse
make
./test