Collaborative Research: SI2-SSI:Task-Based Environment for Scientific Simulation at Extreme Scale (TESSE)

合作研究:SI2-SSI:基于任务的超大规模科学模拟环境 (TESSE)

基本信息

  • 批准号:
    1450300
  • 负责人:
  • 金额:
    $ 117.81万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2015
  • 资助国家:
    美国
  • 起止时间:
    2015-05-15 至 2019-04-30
  • 项目状态:
    已结题

项目摘要

This project, TESSE, is developing a new-generation programming environment that uniquely address the needs of emerging computational models in chemistry and other fields, and allowing these models to reap the benefits of the computer hardware of tomorrow. The project thus is bringing closer the ability to predict properties of matter and design matter transformations of importance to the technological leadership and energy security of the US. TESSE's impact has scientific, cyberinfrastructure, and interdisciplinary educational aspects. TESSE helps carry widely used scientific applications (NWChem, MADNESS, MPQC, etc.) into a whole new generation of many-core and accelerated architectures, while at the same time dramatically improving programmer productivity. In terms of cyberinfrastructure, TESSE's PaRSEC runtime system delivers capabilities that many libraries and advanced applications will require for high performance on large scale and hybridized systems.The goals of this project, Task-based Environment for Scientific Simulation at Extreme Scale (TESSE), are to design and demonstrate via substantial scientific simulations within chemistry and other disciplines a prototype software framework that provides a groundbreaking response to the twin problems of portable performance and programmer productivity for advanced scientific applications on emerging massively-parallel, hybrid, many-core systems. TESSE will create a viable foundation for a new generation of science codes, one which enables even more rapid exploration of new physical models, provides greatly enhanced performance portability through directed acyclic graph (DAG) scheduling and auto-tuned kernels, and works towards full interoperability between major chemistry packages through compatible runtimes and data structures. TESSE will mature to become a standard, widely available, community-based and broadly-applicable parallel programming environment complementing and rivaling MPI/OpenMP. This is needed due to the widely appreciated shortfalls of existing mainstream programming models and the already huge successes of the existing DAG-based runtimes that are the foundation of the next generation of NSF- and DOE-supported (Sca)LAPACK high-performance linear algebra libraries.
这个名为TESSE的项目正在开发一种新一代编程环境,该环境能够独特地满足化学和其他领域新兴计算模型的需求,并允许这些模型从未来的计算机硬件中获益。因此,该项目使预测物质特性和设计物质转化的能力更加接近,这对美国的技术领先地位和能源安全至关重要。TESSE的影响包括科学、网络基础设施和跨学科教育方面。TESSE有助于将广泛使用的科学应用程序(NWChem, MADNESS, MPQC等)带入新一代的多核和加速架构,同时显著提高程序员的工作效率。在网络基础设施方面,TESSE的PaRSEC运行时系统提供了许多库和高级应用程序在大规模和混合系统上需要的高性能功能。该项目名为“极端规模科学模拟任务环境”(Task-based Environment for Scientific Simulation at Extreme Scale,简称TESSE),其目标是通过化学和其他学科的大量科学模拟,设计并演示一个原型软件框架,为新兴的大规模并行、混合、多核系统上的先进科学应用的可移植性能和程序员生产力的双重问题提供突破性的响应。TESSE将为新一代科学代码创造一个可行的基础,它可以更快地探索新的物理模型,通过有向无环图(DAG)调度和自动调优内核提供极大增强的性能可移植性,并通过兼容的运行时和数据结构实现主要化学包之间的完全互操作性。TESSE将逐渐成熟,成为一个标准的、广泛可用的、基于社区的、广泛适用的并行编程环境,以补充和竞争MPI/OpenMP。这是必要的,因为人们普遍认识到现有主流编程模型的不足,而且现有基于dag的运行时已经取得了巨大的成功,这些运行时是NSF和doe支持的下一代(Sca)LAPACK高性能线性代数库的基础。

项目成果

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George Bosilca其他文献

An evaluation of User-Level Failure Mitigation support in MPI
  • DOI:
    10.1007/s00607-013-0331-3
  • 发表时间:
    2013-05-29
  • 期刊:
  • 影响因子:
    2.800
  • 作者:
    Wesley Bland;Aurelien Bouteiller;Thomas Herault;Joshua Hursey;George Bosilca;Jack J. Dongarra
  • 通讯作者:
    Jack J. Dongarra
Cache Optimization and Performance Modeling of Batched, Small, and Rectangular Matrix Multiplication on Intel, AMD, and Fujitsu Processors
Intel、AMD 和 Fujitsu 处理器上的批量、小型和矩形矩阵乘法的缓存优化和性能建模
Self-healing network for scalable fault-tolerant runtime environments
  • DOI:
    10.1016/j.future.2009.04.001
  • 发表时间:
    2010-03-01
  • 期刊:
  • 影响因子:
  • 作者:
    Thara Angskun;Graham Fagg;George Bosilca;Jelena Pješivac-Grbović;Jack Dongarra
  • 通讯作者:
    Jack Dongarra
Kernel-assisted and topology-aware MPI collective communications on multicore/many-core platforms
  • DOI:
    10.1016/j.jpdc.2013.01.015
  • 发表时间:
    2013-07-01
  • 期刊:
  • 影响因子:
  • 作者:
    Teng Ma;George Bosilca;Aurelien Bouteiller;Jack J. Dongarra
  • 通讯作者:
    Jack J. Dongarra

George Bosilca的其他文献

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{{ truncateString('George Bosilca', 18)}}的其他基金

Collaborative Research: Frameworks: Production quality Ecosystem for Programming and Executing eXtreme-scale Applications (EPEXA)
合作研究:框架:用于编程和执行超大规模应用程序的生产质量生态系统 (EPEXA)
  • 批准号:
    1931384
  • 财政年份:
    2019
  • 资助金额:
    $ 117.81万
  • 项目类别:
    Standard Grant
OAC Core: Small: Collaborative Research: Scalable Run-Time for Highly Parallel, Heterogeneous Systems
OAC 核心:小型:协作研究:高度并行、异构系统的可扩展运行时
  • 批准号:
    1909015
  • 财政年份:
    2019
  • 资助金额:
    $ 117.81万
  • 项目类别:
    Standard Grant
SPX: Collaborative Research: Cross-layer Application-Aware Resilience at Extreme Scale (CAARES)
SPX:协作研究:超大规模跨层应用程序感知弹性 (CAARES)
  • 批准号:
    1725692
  • 财政年份:
    2017
  • 资助金额:
    $ 117.81万
  • 项目类别:
    Standard Grant
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
  • 财政年份:
    2017
  • 资助金额:
    $ 117.81万
  • 项目类别:
    Standard Grant
SI2-SSE: Collaborative Research: ADAPT: Next Generation Message Passing Interface (MPI) Library - Open MPI
SI2-SSE:协作研究:ADAPT:下一代消息传递接口 (MPI) 库 - 开放 MPI
  • 批准号:
    1339820
  • 财政年份:
    2013
  • 资助金额:
    $ 117.81万
  • 项目类别:
    Standard Grant
G8 Initiative: Collaborative Research: ECS: Enabling Climate Simulation at Extreme Scale
G8 倡议:合作研究:ECS:实现极端规模的气候模拟
  • 批准号:
    1063019
  • 财政年份:
    2011
  • 资助金额:
    $ 117.81万
  • 项目类别:
    Continuing Grant
Collaborative: CSR-AES: System Support for Auto-tuning MPI Applications
协作:CSR-AES:自动调整 MPI 应用程序的系统支持
  • 批准号:
    0720678
  • 财政年份:
    2007
  • 资助金额:
    $ 117.81万
  • 项目类别:
    Continuing Grant

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