利用GPU为大型Radio Telescope阵列实现高吞吐量实时数据流水线
Enabling a High Throughput Real Time Data Pipeline for a Large Radio Telescope Array with GPUs
摘要：
Murchison Widefield Array（MWA）是一个下一代射电望远镜，目前正在偏远的西澳大利亚内陆建造。原始数据将以5GiB/s的速度连续生成，并分组为8 s节奏。这种高吞吐量促进了现场实时处理的发展，并减少了对存档、传输和离线处理的偏好。每一批8 s数据必须在下一批到来之前完全还原。维持实时操作将需要大约2.5TFLOP/s的持续性能（包括卷积、FFT、插值和矩阵乘法）。我们描述了一个可扩展的异构计算流水线实现，利用现代GPU的高计算密度和FLOP-per-Watt比。该架构在节点内部和节点之间高度并行，所有主要处理元素都由GPU执行。沿着流水线的必要的分散-聚集操作在托管GPU的节点之间松散地同步。MWA将是一种前沿科学仪器，也是计划中的千万亿次和百万亿次设施的开拓者。
英文摘要：
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 5GiB/s, grouped into 8s 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 8s data must be completely reduced before the next batch arrives. Maintaining real time operation will require a sustained performance of around 2.5TFLOP/s (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 exascale facilities.
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