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Climate data assimilation on a massively parallel Supercomputer

机译:大规模并行超级计算机上的气候数据同化

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We have designed and implemented a set of highly efficient and highly scalable algorithms for an unstructured computational package, the PSAS data assimilation package, as demonstrated by detailed performance analysis of systematic runs on up to 512-nodes of an Intel Paragon. The preconditioned Conjugate Gradient solver achieves a sustained 18 Gflops performance. Consequently, we achieve an unprecedented 100-fold reduction in time to solution on the Intel Paragon over a single head of a Cray C90. This not only exceeds the daily performance requirement of the Data Assimilation Office at NASA's Goddard Space Flight Center, but also makes it possible to explore much larger and challenging data assimilation problems which are unthinkable on a traditional computer platform such as the Cray C90.

机译:

我们已经为非结构化计算程序包(PSAS数据同化程序包)设计和实现了一套高效且高度可扩展的算法,这通过对多达512个节点的Intel Paragon的系统运行进行详细的性能分析证明了这一点。预处理的共轭梯度求解器可实现持续的18 Gflops性能。因此,在Cray C90的单头上,我们在Intel Paragon上解决问题的时间就空前减少了100倍。这不仅超出了美国宇航局戈达德太空飞行中心数据同化办公室的日常性能要求,而且使探索更大的,具有挑战性的数据同化问题成为可能,而这些问题在Cray C90等传统计算机平台上是无法想象的。 P>

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