Enabling High Energy Physics at the Information Frontier Using GPUs and Other Many/Multi-Core Architectures

高能物理（HEP）实验使用极其庞大的数据集来研究物质的基本成分和控制它们相互作用的力。为了最有效地利用计算资源，研究人员将研究算法并开发在计算机上运行良好的代码，这些计算机为并行执行指令提供了特别高的性能，包括通用图形处理单元（gpu）和其他多核/多核架构。这些研究以及在此开发的社区工具将扩大HEP和相关领域的定量范围，使其能够实现定性进展。为了增强这项工作的广泛影响，研究人员将把统计分析工具包作为免费和开源软件分发。此外，研究人员将通过讲座、短期课程和期刊文章传播他们关于有效编写gpu友好算法的结果。本项目的具体HEP背景将是开发用于分析下一代实验数据的工具。粒子物理学标准模型（描述基本粒子的电磁、弱核和强核相互作用）的最后几个主要元素在过去十年中已经得到了实验验证。BABAR和Belle合作对b介子衰变中粒子-反粒子不对称性的详细测量使小林和益川分享了2008年诺贝尔物理学奖。2012年，欧洲核子研究中心的ATLAS和CMS实验发现了一种类希格斯玻色子，恩格尔特和希格斯共同获得了2013年诺贝尔物理学奖。在这里开发的代码和工具包将使HEP实验能够更有效地搜索SM（有时称为超越标准模型（BSM）物理学）没有描述的现象。ATLAS和CMS正在寻找最高能量的BSM物理的直接证据。正在日本建设的下一代电子-正电子风味工厂Belle- ii的设计光度比Belle高两个数量级，在b介子衰变、粲子混合和轻子风味违背搜索的高统计研究中提供互补的BSM灵敏度。欧洲核子研究中心的大型强子对撞机实验在许多方面已经超过了BaBar和Belle一个数量级以上，由此产生的BSM约束是对ATLAS和CMS的补充。分析来自所有这些实验的数据将需要不成比例的更多的计算能力，而成本则会适度增加。除了开发一般有用的工具外，这里开发的统计分析工具包还将用于分析来自LHCb的数据。

High energy physics (HEP) experiments use extremely large data sets to study the fundamental constituents of matter and the forces that govern their interactions. To use computing resources most effectively, the investigators will study algorithms and develop codes that run well on computers which provide especially high performance for parallel execution of instructions, including general purpose graphics processing units (GPUs) and other many-core/multi-core architectures. These studies, and the community tools to be developed here, will extend the quantitative reach in HEP and allied fields to the point where they enable qualitative advances. To enhance the broader impact of this work, the investigators will distribute the statistical analysis toolkit as Free and Open Source Software. In addition, the investigators will disseminate their results about effectively writing GPU-friendly algorithms via talks, short courses, and journal articles.The specific HEP context for this project will be developing tools for analyzing data from the next generation of experiments. The last major elements of the Standard Model (SM) of particle physics (which describes the electromagnetic, weak nuclear, and strong nuclear interactions of fundamental particles) have been experimentally validated in the past decade. Detailed measurements of particle-antiparticle asymmetries in the decays of B-mesons by the BABAR and Belle collaborations led to Kobayashi and Maskawa sharing the 2008 Nobel Prize in Physics. The ATLAS and CMS experiments at CERN discovered a Higgs-like boson in 2012, leading to Englert and Higgs sharing the 2013 Nobel prize in physics. The codes and toolkits to be developed here will enable HEP experiments to search more effectively for phenomena not described by the SM, sometimes called Beyond-the-Standard-Model (BSM) physics. ATLAS and CMS are searching for direct evidence of BSM physics at the highest energies. Belle-II, the next generation electron-positron flavor factory being built in Japan, has a design luminosity two orders of magnitude greater than that of Belle, providing complementary BSM sensitivity in very high statistics studies of B-meson decays, charm mixing, and searches for lepton flavor violation. The LHCb experiment at CERN has already surpassed BaBar and Belle by more than an order of magnitude in many channels, and the resulting BSM constraints complement those from ATLAS and CMS. Analyzing the data from all these experiments will require disproportionately more computing power at a modest increase in cost. In addition to developing generally useful tools, the statistical analysis toolkit developed here will be applied to analyze data from LHCb.