• g++ $\ge$ 11
• cmake $\ge$ 3.14
• git
• python $\ge$ 3.9
• CUDA $=$ 12.1
• NVIDIA GPU with sm $\ge$ 80

Change some variables, CUDA_PATH and CUDA_ARCH, in the env.sh file according to your computer. CUDA_PATH denotes the path where nvcc is installed. And change CUDA_ARCH following the specification. Other environmental variables will be setup automatically.

export CUDA_PATH=/usr/local/cuda-12.1
export CUDA_ARCH=86

And then, execute the env.sh file with source command to export the environmental variables and install python packages.

source env.sh

bash install_sputnik.sh

bash download_data.sh

The Debian user should install the bc package as shown below because the bc package is not pre-installed in the Debian system.

sudo apt-get install bc

After running the shell script, The each figure file is generated and located in plots directory.

bash build.sh

Benchmarking all algorithms in Figure 4 on the large DLMC dataset takes more than 5 hours. The paper includes ASpT-RR as a benchmark baseline in figure 4, but as it is not currently open-source, we are unable to provide it. Therefore, we ask for your understanding that it is not included in the released artifact.

bash run_fig4_dlmc_sh       

If you want to shorten the execution time and conduct a brief experiment, just run run_fig4_dlmc_short.sh.

This script conducts the experiment on just 2 matrices for each sparsity in a subfigure.

bash run_fig4_dlmc_short.sh # Brief version

It will take about 30 minutes to run and plot the figure.

bash run_fig5_dlmc_sh

Similar to Figure 4, there is a brief version of Figure 5 that requires about 5 minutes to execute.

bash run_fig5_dlmc_short.sh # Brief version

It will take about 30 minutes to run and plot the figure.

bash run_fig6_dlmc_sh