Symbolic Mapping and Allocation for the Cholesky Factorization on NUMA machines: Results and Optimizations
Résumé
We discuss some performance issues of the tiled Cholesky factorization on non-uniform memory access-time (NUMA) shared memory machines. We show how to optimize thread and data placement in order to achieve performance gains up to 50% compared to state-of- the-art libraries such as PLASMA or MKL.
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