UART Publications
Performance of a High-Accuracy PDE Solver on a Self Optimizing NUMA Architecture
Sverker Holmgren and Dan Wallin
In Proceedings of the 7th International Euro-Par Conference (Euro-Par 2001), Manchester, UK, August 2001.
Abstract
High-accuracy PDE solvers use multi-dimensional fast Fourier transforms. The FFTs exhibits a static and structured memory access pattern which results in a large amount of communication. Performance analysis of a non-trivial kernel representing a PDE solution algorithm has been carried out on a Sun WildFire computer. Here, different architecture, system and programming models can be studied. The WildFire system uses self-optimization techniques such as data migration and replication to change the placement of data at runtime. If the data placement is not optimal, the initial performance is degraded. However, after a few iterations the page migration daemon is able to modify the placement of data. The performance is improved, and equals what is achieved if the data is optimally placed at the start of the execution using hand tuning. The speedup for the PDE solution kernel is surprisingly good.
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BibTeX file entry: Holmgren:2001:aug