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Enabling a high throughput real time data pipeline for a large radio telescope array with GPUs

机译:为具有GPU的大型射电望远镜阵列启用高吞吐量实时数据管道

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摘要

The Murchison Widefield Array (MWA) is a next-generation radio telescope currently under construction in the remote Western Australia Outback. Raw data will be generated continuously at 5 GiB s~(-1), grouped into 8 s cadences. This high throughput motivates the development of on-site, real time processing and reduction in preference to archiving, transport and off-line processing. Each batch of 8 s data must be completely reduced before the next batch arrives. Maintaining real time operation will require a sustained performance of around 2.5 TFLOP s~(-1) (including convolutions, FFTs, interpolations and matrix multiplications). We describe a scalable heterogeneous computing pipeline implementation, exploiting both the high computing density and FLOP-per-Watt ratio of modern GPUs. The architecture is highly parallel within and across nodes, with all major processing elements performed by GPUs. Necessary scatter-gather operations along the pipeline are loosely synchronized between the nodes hosting the GPUs. The MWA will be a frontier scientific instrument and a pathfinder for planned peta- and exa-scale facilities.
机译:默奇森宽场阵列(Murchison Widefield Array,MWA)是目前在偏远的西澳大利亚内陆地区正在建设的下一代射电望远镜。原始数据将以5 GiB s〜(-1)连续生成,分为8 s个节奏。如此高的吞吐量推动了现场实时处理技术的发展,并降低了归档,运输和离线处理的优先级。在下一批到达之前,必须完全减少每批8 s的数据。维持实时操作将需要约2.5 TFLOP s〜(-1)的持续性能(包括卷积,FFT,内插和矩阵乘法)。我们利用现代GPU的高计算密度和FLOP / Watt比来描述可扩展的异构计算管道实现。该架构在节点内部和节点之间高度并行,所有主要处理元素均由GPU执行。沿管线进行的必要的分散收集操作在托管GPU的节点之间宽松地同步。 MWA将是前沿的科学仪器,也是计划中的peta和exa级设施的探路者。

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