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Collaborative Research: SI2-SSI: EVOLVE: Enhancing the Open MPI Software for Next Generation Architectures and Applications

Collaborative Research: SI2-SSI: EVOLVE: Enhancing the Open MPI Software for Next Generation Architectures and Applications
合作研究:SI2-SSI:EVOLVE:增强下一代架构和应用的开放式 MPI 软件
批准号:
1664142
负责人:
George Bosilca
金额:
$156.62万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-06-01 至 2022-05-31

项目摘要

项目成果

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中文摘要
翻译
近二十年来,消息传递接口(MPI)一直是高性能计算生态系统的重要组成部分,因此是重要科学突破的关键推动因素。它是从物理、化学、生物、材料科学到工程的大多数大规模模拟的基本构件。开放MPI是MPI规范的开源实现,被研究界和工业界广泛使用和采用。Open MPI库是由学术机构、国家实验室和工业合作伙伴组成的联盟共同开发和维护的。它几乎安装在美国和世界其他地区的所有大型计算机系统上。该项目的目标是在现代计算机系统不断发展的背景下,加强开放式MPI图书馆并使其现代化,并确保其未来在所有即将到来的体系结构上的可操作性。我们的目标是实现可在多核系统中使用的基本软件技术,以更高效地执行基于MPI的并行应用程序,并容忍从当前系统到预计在十年末之前的极端规模的所有级别的进程和内存故障。Open MPI是消息传递接口(MPI)规范的开源实现。目前正在对MPI API进行扩展,以考虑应用程序开发人员在效率、生产力和弹性方面的需求。该项目还将支持学术界参与Open MPI软件的设计、开发和评估,并确保学术界参与MPI论坛。该方案的目标是增强Open MPI软件库,主要集中在两个方面:(1)扩展Open MPI以支持MPI规范的新功能。Open MPI将继续支持当前和即将到来的MPI规范的所有新功能。这项提议范围内最重要的两个领域是:(A)扩展以更好地支持混合编程模型和(B)支持MPI应用程序中的容错。为了改进对混合编程模型的支持,MPI论坛目前正在考虑引入MPI端点的概念,MPI级别的不同线程可以使用它来实例化多个独立的通信上下文。该项目的目标是开发一个端点实现,以支持有效的混合编程模型,并将这一概念扩展到并行应用程序的其他方面,如文件I/O操作。其中一个项目合作伙伴(UTK)在MPI论坛上领导当前的提案,以暴露故障并确保MPI应用程序的继续执行。在这项SSI提案的背景下,目标是加强、改进和扩大对Open MPI中现有ULFM实施的支持,从而使最终用户能够为未来的平台设计特定于应用的弹性方法。(2)增强Open MPI核心以支持新的体系结构,提高可伸缩性。虽然Open MPI在过去展示了非常好的可伸缩性,但要确保在未来的体系结构上具有类似的良好性能,还有大量的工作要做。具体地说,我们建议对启动环境进行开创性的改造,以提高进程启动的可扩展性,增加对操作的异步进度的支持,启用对加速器的支持,并降低对系统噪声的敏感度。该项目还将加强对作为Open MPI包一部分的文件I/O操作的支持,方法是通过委派扩大我们在高度可伸缩的集体I/O操作方面的工作,并探索将突发缓冲区用作临时存储。
英文摘要
For nearly two decades, the Message Passing Interface (MPI) has been an essential part of the High-Performance Computing ecosystem and consequently a key enabler for important scientific breakthroughs. It is a fundamental building block for most large-scale simulations from physics, chemistry, biology, material sciences as engineering. Open MPI is an open source implementation of the MPI specification, widely used and adopted by the research community as well as industry. The Open MPI library is jointly developed and maintained by a consortium of academic institutions, national labs and industrial partners. It is installed on virtually all large-scale computer systems in the US as well as in the rest of the world. The goal of this project is to enhance and modernize the Open MPI library in the context of the ongoing evolution of modern computer systems, and to ensure its future operability on all upcoming architectures. We aim at implementing fundamental software techniques that can be used in many-core systems to execute MPI-based parallel applications more efficiently, and to tolerate process and memory failures at all scales, from current systems, up to the extreme scales expected before the end of the decade.Open MPI is an open source implementation of the Message Passing Interface (MPI) specification. The MPI API is currently being extended to consider the needs of application developers in terms of efficiency, productivity and resilience. The project will also support academic involvement in the design, development and evaluation of the Open MPI software, and ensure academic presence in the MPI Forum. The goal of this proposal is to enhance the Open MPI software library, focusing on two aspects: (1) Extend Open MPI to support new features of the MPI specification. Open MPI will continue to support all new features of current and upcoming MPI specifications. The two most significant areas within the context of this proposal are (a) extensions to better support hybrid programming models and (b) support for fault tolerance in MPI applications. To improve support for hybrid programming models, the MPI Forum is currently considering introducing the notion of MPI Endpoints, which could be used by different threads of an MPI rank to instantiate multiple separate communication contexts. The goal within this project is to develop an implementation of endpoints to support effective hybrid programming model, and to extend the concept to other aspects of parallel applications such as File I/O operations. One of the project partners (UTK) leads the current proposal in the MPI Forum to expose failures and ensure the continuation of the execution of MPI applications. In the context of this SSI proposal, the goal is to harden, improve, and expand the support of the existing ULFM implementation in Open MPI and thus enable end-users to design application-specific resilience approaches for future platforms. (2) Enhance the Open MPI core to support new architectures and improve scalability. While Open MPI has demonstrated very good scalability in the past, there is significant work to be done to ensure similarly good performance on future architectures. Specifically, we propose a groundbreaking rework of the startup environment that will improve process launch scalability, increase support for asynchronous progress of operations, enable support for accelerators, and reduce sensitivity to system noise. The project would also enhance the support for File I/O operations as part of the Open MPI package by expanding our work on highly scalable collective I/O operations through delegation and exploring the utilization of burst buffers as temporary storage.
期刊论文(25)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1177/1094342017711505
发表时间: 2018-01-01
期刊: INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS
影响因子: 3.1
作者: [Bosilca, George, Bouteiller, Aurelien, Dongarra, Jack]
通讯作者: Dongarra, Jack
Using Advanced Vector Extensions AVX-512 for MPI Reductions
使用高级矢量扩展 AVX-512 减少 MPI
DOI: 10.1145/3416315.3416316
发表时间: 2020
期刊: EuroMPI/USA '20: 27th European MPI Users' Group Meeting
影响因子: --
作者: [Zhong, Dong, Cao, Qinglei, Bosilca, George, Dongarra, Jack]
通讯作者: Dongarra, Jack
DOI: 10.1145/3208040.3208054
发表时间: 2018-06
期刊: Proceedings of the 27th International Symposium on High-Performance Parallel and Distributed Computing
影响因子: --
作者: [Xi Luo;Wei Wu;G. Bosilca;Thananon Patinyasakdikul;Linnan Wang;J. Dongarra]
通讯作者: Xi Luo;Wei Wu;G. Bosilca;Thananon Patinyasakdikul;Linnan Wang;J. Dongarra
Predicting MPI Collective Communication Performance Using Machine Learning
使用机器学习预测 MPI 集体通信性能
DOI: 10.1109/cluster49012.2020.00036
发表时间: 2020
期刊: 2020 IEEE International Conference on Cluster Computing (CLUSTER
影响因子: --
作者: [Hunold, Sascha, Bhatele, Abhinav, Bosilca, George, Knees, Peter]
通讯作者: Knees, Peter
22
    Collaborative Research: Frameworks: Production quality Ecosystem for Programming and Executing eXtreme-scale Applications (EPEXA)
    • 批准号:
      1931384
    • 项目类别:
      Standard Grant
    • 资助金额:
      $199.57万
    • 财政年份:
      2019
    • 负责人:
      George Bosilca
    • 依托单位:
    OAC Core: Small: Collaborative Research: Scalable Run-Time for Highly Parallel, Heterogeneous Systems
    • 批准号:
      1909015
    • 项目类别:
      Standard Grant
    • 资助金额:
      $25.0万
    • 财政年份:
      2019
    • 负责人:
      George Bosilca
    • 依托单位:
    SPX: Collaborative Research: Cross-layer Application-Aware Resilience at Extreme Scale (CAARES)
    • 批准号:
      1725692
    • 项目类别:
      Standard Grant
    • 资助金额:
      $26.61万
    • 财政年份:
      2017
    • 负责人:
      George Bosilca
    • 依托单位:
    Collaborative Research: SI2-SSI:Task-Based Environment for Scientific Simulation at Extreme Scale (TESSE)
    • 批准号:
      1450300
    • 项目类别:
      Standard Grant
    • 资助金额:
      $117.81万
    • 财政年份:
      2015
    • 负责人:
      George Bosilca
    • 依托单位:
    国内基金
    海外基金
    Research on Quantum Field Theory without a Lagrangian Description
    • 批准号:
      24ZR1403900
    • 项目类别:
      省市级项目
    • 资助金额:
      --
    • 批准年份:
      2024
    • 负责人:
      SATOSHI NAWATA
    • 依托单位:
    Cell Research
    Cell Research
    Cell Research (细胞研究)