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ABSTRACT
The Sony/Toshiba/IBM (STI) CELL processor introduces pioneering solutions in processor architecture. At the same time it presents new challenges for the development of numerical algorithms. One is effective exploitation of the differential between the speed of single and double precision arithmetic; the other is efficient parallelization between the short vector SIMD cores. The first challenge is addressed by utilizing the well known technique of iterative refinement for the solution of a dense symmetric positive definite system of linear equations, resulting in a mixed-precision algorithm, which delivers double precision accuracy, while performing the bulk of the work in single precision. The main contribution of this paper lies in addressing the second challenge by successful thread-level parallelization, exploiting fine-grained task granularity and a lightweight decentralized synchronization. The implementation of the computationally intensive sections gets within 90 percent of peak floating point performance, while the implementation of the memory intensive sections reaches within 90 percent of peak memory bandwidth. On a single CELL processor, the algorithm achieves over 170~Gflop/s when solving a symmetric positive definite system of linear equation in single precision and over 150~Gflop/s when delivering the result in double precision accuracy.
INDEX TERMS
Parallel algorithms, Numerical Linear Algebra, Linear systems
CITATION
Jakub Kurzak, Jack Dongarra, Alfredo Buttari, "Solving Systems of Linear Equations on the CELL Processor Using Cholesky Factorization", IEEE Transactions on Parallel & Distributed Systems, vol. 19, no. , pp. 1175-1186, September 2008, doi:10.1109/TPDS.2007.70813
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