From Design and Construction to Discovery: Machine Learning Algorithms for Particle Physics Triggering and Tracking with GPUs and FPGAs in Malaysia

从设计和施工到发现：马来西亚使用 GPU 和 FPGA 进行粒子物理触发和跟踪的机器学习算法

• 批准号: ST/R006741/1
• 负责人: Yoshi Uchida
• 金额: $ 42.01万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ST%2FR006741%2F1
• 关键词: Design; Construction; Discovery; Machine; Learning

Malaysia is currently in the midst of its own Data Analytics (DA) revolution. Through governmental policy, it supports both academic research and industrial avenues to increase Malaysia's capacity for DA and High Performance Computing (HPC). In the proposed project, which will run for three years from April 2018, physicists at Imperial College London seek to participate in this effort by working together with leading researchers from Malaysia on the Coherent Muon to Electron Transition (COMET) Experiment. COMET is designed to investigate charged lepton flavour violation (CLFV) by searching for the as-yet-unseen muon to electron conversion on an aluminium nucleus. This process is not allowed in the Standard Model of particle physics, but has very good sensitivity to Beyond the Standard Model physics. A positive discovery of CLFV would be a Nobel Prize-class result and revolutionise our understanding of the building blocks of the universe. The experiment is currently under construction at the internationally-renowned Japan Proton Accelerator Research Complex (J-PARC) laboratory.The first phase of the COMET experiment will begin taking data in 2019. This phase is designed to probe this process 100 times better than the current limit, with a second phase reaching a sensitivity that is 10,000 times better. To achieve this sensitivity, we are building the world's most intense muon beam which will deliver over a billion muons per second. Very few of these muons will result in anything that is relevant to muon to electron conversion, and instead will form the unwanted background to our sought-after CLFV signal. Therefore COMET (a search for a miniscule "signal" in the midst of a billion billion mundane "background" occurrences) presents a huge technical challenge which will be met by the use of a combination of modern technologies: these include cutting-edge applications of Field-Programmable Gate Arrays (FPGAs; programmable integrated circuits which allow real-time data algorithms to be implemented) and Graphics Processing Units (GPUs) as accelerative computing components, supercomputing via a cloud-based computing solutions, and Machine Learning (ML) techniques. Whilst these will be employed to allow COMET to pursue its particle-physics goals, these are technologies that are known to offer novel solutions to common problems in a growing number of global DA industries, from communications and networking to financial applications and blockchain research.COMET's first data-taking runs are scheduled for 2019, in the second year of the project. Over a hundred physicists from 35 institutions in 14 countries currently participate, and top scientists from Malaysia will work with researchers from Imperial on the preparations for the experiment, real data-taking and the physics analysis of the data. The Imperial group designed the software that is being used by COMET and participants will take part in the global collaborative coding effort, and the production of massive amounts of computer simulations that are needed to allow us to study the data, and work with experts in FPGA and GPU programming to produce and test the hardware and software that is needed by the experiment. The project includes attachments in the UK and Malaysia to allow the exchange of skills, as well as extended time at the J-PARC laboratory to build and run the experiment together with our international colleagues.The project will result in participants taking on valuable roles within the experiment, being trained in modern DA techniques and applying them to this world-leading experiment. In addition to a particle physics measurement that has the potential to be a paradigm-changing discovery, it will provide for a solid basis for future leadership in a broad range of pure and applied research.

马来西亚目前正处于自己的数据分析（DA）革命之中。通过政府政策，它支持学术研究和工业途径，以增加马来西亚的数据处理和高性能计算（HPC）的能力。在拟议的项目中，伦敦帝国理工学院的物理学家将与马来西亚的主要研究人员一起参与相干μ子到电子跃迁（COMET）实验，该项目将从2018年4月开始运行三年。彗星被设计用来研究带电轻子味违逆（CLFV），通过寻找在铝核上尚未见过的介子到电子的转换。这一过程在粒子物理的标准模型中是不允许的，但对超出标准模型的物理有很好的敏感性。CLFV的积极发现将是诺贝尔奖级别的结果，并彻底改变我们对宇宙组成部分的理解。该实验目前正在国际知名的日本质子加速器研究中心（J-PARC）实验室进行建设。彗星实验的第一阶段将于2019年开始采集数据。这一阶段的目的是探测这一过程比目前的极限好100倍，第二阶段的灵敏度达到10,000倍。为了达到这种灵敏度，我们正在建造世界上最强烈的μ子束，每秒将产生超过10亿个μ子。这些μ子很少会导致任何与μ子到电子转换相关的东西，而是会形成我们所追求的CLFV信号的不必要的背景。因此，彗星（在亿亿个平凡的“背景”事件中寻找一个微小的“信号”）提出了一个巨大的技术挑战，将通过使用现代技术的组合来满足：这些技术包括现场可编程门阵列（fpga）的尖端应用；可编程集成电路（允许实现实时数据算法）和图形处理单元（gpu）作为加速计算组件，通过基于云的计算解决方案进行超级计算，以及机器学习（ML）技术。虽然这些技术将用于COMET实现其粒子物理目标，但众所周知，这些技术可以为越来越多的全球数据处理行业（从通信和网络到金融应用和区块链研究）中的常见问题提供新颖的解决方案。彗星的第一次数据采集将于2019年，也就是项目的第二年进行。目前，来自14个国家35个机构的100多名物理学家参与了这项研究，马来西亚的顶尖科学家将与帝国理工学院的研究人员合作，为实验做准备，采集实际数据，并对数据进行物理分析。帝国团队设计了COMET使用的软件，参与者将参与全球协作编码工作，以及大量计算机模拟的生产，这些模拟需要让我们研究数据，并与FPGA和GPU编程专家合作，生产和测试实验所需的硬件和软件。该项目包括在英国和马来西亚的附件，以便进行技能交流，以及在J-PARC实验室延长时间，与我们的国际同事一起建立和运行实验。该项目将使参与者在实验中发挥重要作用，接受现代数据分析技术的培训，并将其应用于这个世界领先的实验。除了粒子物理测量有可能成为一个改变范式的发现之外，它还将为未来在广泛的纯粹和应用研究中的领导地位提供坚实的基础。

项目成果

Radiation hardness study for the COMET Phase-I electronics

• DOI: 10.1016/j.nima.2019.163247
• 发表时间: 2019-12
• 期刊: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
• 作者: Y. Nakazawa;Y. Fujii;E. Gillies;E. Hamada;Y. Igarashi;M. Lee;M. Moritsu;Y. Matsuda;Y. Miyazaki;Y. Nakai;H. Natori;K. Oishi;A. Sato;Y. Uchida;K. Ueno;H. Yamaguchi;B. Yeo;H. Yoshida;Jie Zhang

COMET Phase-I technical design report

• DOI: 10.1093/ptep/ptz125
• 发表时间: 2018-12
• 期刊: arXiv: Instrumentation and Detectors
• 作者: R. Abramishvili;G. Adamov;R. Akhmetshin;A. Allin;J. Ang'elique;V. Anishchik;M. Aoki;D. Aznabayev-D.-Azn