This is the source code of the paper

Weifeng Liu and Brian Vinter. 2015. CSR5: An Efficient Storage Format for Cross-Platform Sparse Matrix-Vector Multiplication. In Proceedings of the 29th ACM international conference on Supercomputing (ICS '15). (To appear).

A draft version is downloadable at http://arxiv.org/abs/1503.05032.

Contact: Weifeng Liu (weifeng.liu at nbi.ku.dk) and/or Brian Vinter (vinter at nbi.ku.dk).

• Execution

1. Set environments for the Intel C/C++ Compilers. For example, use source /opt/intel/composer_xe_2015.1.133/bin/compilervars.sh intel64,
2. Run make,
3. Run ./spmv example.mtx.

• Tested environments

1. Intel Core i7-4770R CPU with Ubuntu 14.04 64-bit Linux installed.
2. Intel Xeon E5-2667 v3 dual-socket CPUs with Redhat 6.5 64-bit Linux installed.

• Data type

1. Currently, only 64-bit double precision SpMV is supported.

• Execution

1. Set CUDA path in the Makefile,
2. Run make,
3. Run ./spmv example.mtx.

• Tested environments

1. nVidia GeForce GTX 980 GPU in a host with Ubuntu 14.04 64-bit Linux installed.
2. nVidia GeForce GT 650M GPU in a host with Mac OS X 10.9.2 installed.

• Data type

1. The code supports both double precision and single precision SpMV. Use make VALUE_TYPE=double for double precision or make VALUE_TYPE=float for single precision.

• Execution

1. Set OpenCL path in the Makefile,
2. Run make,
3. Run ./spmv example.mtx.

• Tested environments

1. AMD Radeon R9-290X GPU in a host with Ubuntu 14.04 64-bit Linux installed.

• Data type

1. The code supports both double precision and single precision SpMV. Use make VALUE_TYPE=double for double precision or make VALUE_TYPE=float for single precision.

• Execution

1. Set environments for the Intel C/C++ Compilers. For example, use source /opt/intel/composer_xe_2015.1.133/bin/compilervars.sh intel64,
2. Run make,
3. Run ./spmv example.mtx.

• Tested environments

1. Intel Xeon Phi 5110p in a host with Redhat 6.5 64-bit Linux installed.

• Data type

1. Currently, only 64-bit double precision SpMV is supported.