Climate Data Assimilation on a Massively Parallel Supercomputer
Climate Data Assimilation on a Massively Parallel Supercomputer
复制标题
大规模并行超级计算机上的气候数据同化
DOI：
10.1145/369028.369058
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发表时间：
1996
期刊：
影响因子：
--
通讯作者：
R. Ferraro
中科院分区：
文献类型：
--
作者：
C. Ding;R. Ferraro
我们已经设计并实现了一套高效和高度可扩展的算法的非结构化计算包，PSAS数据同化包，证明了系统运行的详细性能分析高达512个节点的英特尔Paragon。预处理的共轭梯度解算器可实现18 Gflops的持续性能。因此，与Cray C90的单个磁头相比，我们在Intel Paragon上实现了前所未有的100倍缩短。这不仅超过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，而且使其有可能探索更大的和具有挑战性的数据同化问题，这是不可想象的传统计算机平台，如克雷C90。
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.