Abstract
The Chip Multiprocessor (CMP) will be the basic building block for computer systems ranging from laptops to supercomputers. New software developments at all levels are needed to fully utilize these systems. In this work, we evaluate performance of different high-performance sparse LU factorization and triangular solution algorithms on several representative multicore machines. We include both pthreads and MPI implementations in this study, and found that the pthreads implementation consistently delivers good performance and a left-looking algorithm is usually superior.
This research was supported by the Director, Office of Science, Office of Advanced Scientific Computing Research, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.
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Li, X.S. (2008). Evaluation of Sparse LU Factorization and Triangular Solution on Multicore Platforms. In: Palma, J.M.L.M., Amestoy, P.R., Daydé, M., Mattoso, M., Lopes, J.C. (eds) High Performance Computing for Computational Science - VECPAR 2008. VECPAR 2008. Lecture Notes in Computer Science, vol 5336. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92859-1_26
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DOI: https://doi.org/10.1007/978-3-540-92859-1_26
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