多核心技术在高能物理实验在线事件重建中的应用

A. Gianelle, S. Amerio, D. Bastieri, M. Corvo, W. Ketchum, Ted Liu, A. Lonardo, D. Lucchesi, S. Poprocki, R. Rivera, L. Tosoratto, P. Vicini, P. Wittich
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引用次数: 1

摘要

在高能物理(HEP)实验中,对应用于实时选择的多核架构的兴趣正在增长。在本文中,我们描述了应用于典型HEP在线任务的多核设备的性能测量:基于带电粒子轨迹的事件选择。我们使用在Tevatron的CDF实验中用于在线轨道重建的算法的缩放版本作为基准- SVT算法-作为使用LHC实验的新计算架构的低延迟触发系统的现实测试案例。我们研究了将现有串行算法移植到多核设备中的复杂性/性能权衡。我们测量不同架构(Intel Xeon Phi和AMD gpu,以及NVidia gpu)和不同软件环境(OpenCL,以及NVidia CUDA)的性能。考虑到多核设备之间的不同I/O策略,显示了数据处理和数据传输延迟的测量结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Applications of many-core technologies to on-line event reconstruction in High Energy Physics experiments
Interest in many-core architectures applied to real time selections is growing in High Energy Physics (HEP) experiments. In this paper we describe performance measurements of many-core devices when applied to a typical HEP online task: the selection of events based on the trajectories of charged particles. We use as benchmark a scaled-up version of the algorithm used at CDF experiment at Tevatron for online track reconstruction - the SVT algorithm - as a realistic test-case for low-latency trigger systems using new computing architectures for LHC experiment. We examine the complexity/performance trade-off in porting existing serial algorithms to many-core devices. We measure performance of different architectures (Intel Xeon Phi and AMD GPUs, in addition to NVidia GPUs) and different software environments (OpenCL, in addition to NVidia CUDA). Measurements of both data processing and data transfer latency are shown, considering different I/O strategies to/from the many-core devices.
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