├── data_example
│   └── ash219.mtx  # SparseSuite data example
├── download #Please kindly download the dataset, the whole dataset is over 300GB
│   ├── download.py # script to download sparsesuite
│   └── download.sh # script to launch the download.py
├── README.md
├── scripts
│   ├── get_matrix_feature.cpp # collect the matrix feature, such as nrow, ncol, nnz 
│   ├── preprocess_data.py 
│   └── spmm.cu # launch the test
├── experiment_result # experiments result for sparsesuite
│   ├── 1024.csv
│   ├── 128.csv
│   ├── 16.csv
│   ├── 20.csv
│   ├── 256.csv
│   └── 64.csv
└── src
    ├── kernel
    │   ├── csrspmm_non_transpose.cu
    │   ├── csrspmm_parreduce.cu
    │   ├── csrspmm_rowcaching.cu
    │   ├── csrspmm_seqreduce.cu
    │   ├── gespmm.cc
    │   ├── gespmm_csrcoo_v2.cu
    │   ├── gespmm.h
    │   ├── gespmm_v2.cu
    │   ├── gespmm_v2.h
    │   └── Makefile
    └── util
        ├── cuda_util.cuh
        ├── mmio.hpp
        └── sp_util.hpp

cd ./src/kernel
make 
cd ../../scripts
nvcc spmm.cu -I../src/kernel -L../src/kerenl -lgespmm -Lcuda_path/lib64 -lcusparse -o run

./run ../data_example ./out
[INFO] Start 1-th/1 file, filename is ash219.mtx
[INFO] Successful 1-th/1 file, filename is ash219.mtx
cat ./out
filename,nrow,ncol,nnz,sparsity,degree,std_node_dgree,N,cusparse,SEQREDUCE_ROWBALANCE,SR_RB_speed,PARREDUCE_ROWBALANCE,PR_RB_speed,SEQREDUCE_NNZBALANCE,SR_NB_speed,PARREDUCE_NNZBALANCE,PR_NB_speed,ROWCACHING_ROWBALANCE,RC_RB_speed,ROWCACHING_NNZBALANCE,RC_NB_speed,THE_BEST_ALG_INDEX,THE_BEST_ALG_NAME,THE_BEST_ALG_TIME,THE_BEST_ALG_SPEED
ash219.mtx,219,85,438,0.0235294,2,0,128,0.0142976,0.003312,4.31691,0.0077632,1.84171,0.008592,1.66406,0.0070624,2.02447,0.0041056,3.48246,0.01024,1.39625,1,SEQREDUCE_ROWBALANCE,0.003312,4.31691