In this folder, you can find the source codes and input data-dependence matricies. To run the Strassen algorithm, you need: [1] You need to install Boost and Boost.Process and ThreadPool. [1.a] Boost 1.55.0. [1.b] Boost.Process (http://www.highscore.de/boost/process/) [1.c] ThreadPool 0.2.5 (http://threadpool.sourceforge.net/index.html) [2] You can find the source codes for Strassen in ./strassen. The main funcion is in ./strassen/strassen_main.cpp. The data-dependency matrix files are: [2.a] Strassen method : ./strassen-dmp/mat_strassen.dep [2.b] Native MM method : ./strassen-dmp/mat_multi.dep [3] You can use MSVC (Microsoft Visual Studio 2010) to run it. Command Arguments: 5000 mat_strassen.dep 10 It means matrix size = 5000, using 10 processes, and using the data-dependence matrix in mat_strassen.dep. To run the Cholesky inversion algorithm, you need: [1] Do the same procedure as mention in above [1]. [2] You need the source codes in ./strassen and ./cholesky. The main funcion is in ./cholesky/cholesky_main.cpp. The data-dependency matrix file is: ./cholesky-dmp/mat_cholesky.dep [3] You need to generate a SPD matrix as input for Cholesky. Here is a program that can help create a SPD matrix. You can find the code: ./cholesky-dmp/generateSPDmatrix.m Usage: [3.a] A = generateSPDmatrix(5000); % create the matrix [3.b] dlmwrite ('input_5000.txt', A, ' '); % save the matrix Then, make sure you have the file - input_5000.txt in your working directory. [4] You can use MSVC to run the program. Command Arguments: 5000 mat_cholesky.dep 7 It means matrix size = 5000, using 7 processes, and using the data-dependence matrix in mat_cholesky.dep. 6/5/2014 Publications: [1] Zhang, P., Ling, L., Deng, Y., "A Data-driven Paradigm for Mapping Problems", Parallel Computing, vol. 48, pp. 108-124, 2015. DOI: 10.1016/j.parco.2015.05.002 [2] Zhang, P., Gao, Y., "Matrix Multiplication on High-Density Multi-GPU Architectures: Theoretical and Experimental Investigations", in Lecture Notes in Computer Science, vol. 9137, pp 17-30, 20 June 2015. DOI: 10.1007/978-3-319-20119-1_2 [3] Zhang, P., Gao, Y., Qiu, M., "A Data-oriented Method for Scheduling Dependent Tasks on High-density Multi-GPU Systems", in High Performance Computing and Communications (HPCC), 2015 IEEE 17th International Conference on, New York, NY, August 24-26, 2015, pp. 694-699. DOI: 10.1109/HPCC-CSS-ICESS.2015.314 By Dr. Peng Zhang URL: https://www.researchgate.net/profile/Peng_Zhang79 3/31/2016