使用Maxwell微架构GPU加速低延迟引力波搜索
Acceleration of low-latency gravitational wave searches using Maxwell-microarchitecture GPUs
摘要：
引力波（GW）的低延迟探测对于通过常规望远镜对天体物理瞬变进行及时的后续观测至关重要。我们已经开发了一个低延迟流水线使用的技术称为求和并行无限脉冲响应（SPIIR）滤波，实现了图形处理单元（GPU）。在本文中，我们开发了新的\textit{Maxwell}存储器访问架构的NVIDIA GPU，即只读数据缓存，翘曲洗牌，交叉翘曲原子技术。我们报告了3倍的速度比我们以前的实现这种过滤技术。为了用相对较少的滤波器来处理SPIIR，我们开发了一种新的GPU线程配置，具有近10倍的加速。此外，我们使用Maxwell GPU实现了一种多速率SPIIR滤波方案。对于多速率滤波方案，我们在单核CPU上实现了超过100倍的加速。这使得整个SPIIR流水线的CPU使用量减少了21倍。
英文摘要：
Low-latency detections of gravitational waves (GWs) are crucial to enable prompt follow-up observations to astrophysical transients by conventional telescopes. We have developed a low-latency pipeline using a technique called Summed Parallel Infinite Impulse Response (SPIIR) filtering, realized by a Graphic Processing Unit (GPU). In this paper, we exploit the new \textit{Maxwell} memory access architecture in NVIDIA GPUs, namely the read-only data cache, warp-shuffle, and cross-warp atomic techniques. We report a 3-fold speed-up over our previous implementation of this filtering technique. To tackle SPIIR with relatively few filters, we develop a new GPU thread configuration with a nearly 10-fold speedup. In addition, we implement a multi-rate scheme of SPIIR filtering using Maxwell GPUs. We achieve more than 100-fold speed-up over a single core CPU for the multi-rate filtering scheme. This results in an overall of 21-fold CPU usage reduction for the entire SPIIR pipeline.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
