Asynchronous Scientific Continuous Computations Exploiting Disaggregation (ASCCED)
利用分解的异步科学连续计算 (ASCCED)
基本信息
- 批准号:EP/X01794X/1
- 负责人:
- 金额:$ 25.77万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Research Grant
- 财政年份:2023
- 资助国家:英国
- 起止时间:2023 至 无数据
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
The design of efficient and scalable scientific simulation software is reaching a critical point whereby continued advances are increasingly harder, more labour-intensive, and thus more expensive to achieve. This challenge emanates from the constantly evolving design of large-scale high-performance computing systems. World-leading (pre-)exascale systems, as well as their successors, are characterised by multi-million-scale parallel computing activities and a highly heterogeneous mix of processor types such as high-end many-core processors, Graphics Processing Units (GPU), machine learning accelerators, and various accelerators for compression, encryption and in-network processing. To make efficient use of these systems, scientific simulation software must be decomposed in various independent components and make simultaneous use of the variety of heterogeneous compute units.Developing efficient, scalable scientific simulation software for these systems becomes increasingly harder as the limits of parallelism available in the simulation codes is approached. Moreover, the limit of parallelism cannot be reached in practice due to heterogeneity, system imbalances and synchronisation overheads. Scientific simulation software often persists over several decades. The software is optimised and re-optimised repeatedly as the design and scale of the target hardware evolves at a much faster pace, as impactful changes in the hardware may occur every few years. One may thus find that the guiding principles that underpin such software are outdated.The ASCCED project will fundamentally change the status quo in the design of scientific simulation software by simplifying the design to reduce software development and maintenance effort, to facilitate performance optimisation, and to make software more robust to future evolution of computing hardware. The key distinguishing factor of our approach is to structure scientific simulation software as a collection of loosely coupled parallel activities. We will explore the opportunities and challenges of applying techniques previously developed for Parallel Discrete Event Simulation (PDES) to orchestrate these loosely coupled parallel activities. This radically novel approach will enable runtime system software to extract unprecedented scales of parallelism and to minimise performance inefficiencies due to synchronisation. Additionally, based on a speculative execution mechanism, it will uncover parallelism that has not been feasible to extract before.The computational model proposed by ASCCED will, if successful, initiate a new direction of research within programming models for high-performance computing that may dramatically impact not only the performance of scientific simulation software, but can also reduce the engineering effort required to produce efficient scientific simulation software. It will have a profound impact on the sciences that are highly dependent on leadership computing capabilities, such as climate modeling and cancer research.
高效且可扩展的科学模拟软件的设计正达到一个临界点,持续的进步变得越来越困难、更加劳动密集,因此实现成本也越来越高。这一挑战源于大规模高性能计算系统不断发展的设计。世界领先的(前)百亿亿级系统及其后继系统的特点是数百万级并行计算活动和高度异构的处理器类型组合,例如高端众核处理器、图形处理单元 (GPU)、机器学习加速器以及用于压缩、加密和网络内处理的各种加速器。为了有效地利用这些系统,科学模拟软件必须分解为各种独立的组件,并同时使用各种异构计算单元。随着接近模拟代码中可用并行性的极限,为这些系统开发高效、可扩展的科学模拟软件变得越来越困难。此外,由于异构性、系统不平衡和同步开销,在实践中无法达到并行性的极限。科学模拟软件通常会持续数十年。随着目标硬件的设计和规模以更快的速度发展,软件会反复优化和重新优化,因为硬件每隔几年就会发生一次有影响力的变化。因此,人们可能会发现支撑此类软件的指导原则已经过时了。 ASCCED 项目将从根本上改变科学模拟软件设计的现状,通过简化设计来减少软件开发和维护工作,促进性能优化,并使软件对计算硬件的未来发展更加稳健。我们的方法的关键区别因素是将科学模拟软件构建为松散耦合的并行活动的集合。我们将探讨应用先前为并行离散事件模拟 (PDES) 开发的技术来协调这些松散耦合的并行活动的机遇和挑战。这种全新的方法将使运行时系统软件能够获得前所未有的并行规模,并最大限度地减少同步导致的性能低下。此外,基于推测执行机制,它将揭示以前无法提取的并行性。ASCCED提出的计算模型如果成功,将在高性能计算编程模型中开启一个新的研究方向,这不仅可能极大地影响科学模拟软件的性能,而且还可以减少生产高效科学模拟软件所需的工程工作量。它将对高度依赖领先计算能力的科学产生深远的影响,例如气候建模和癌症研究。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Hans Vandierendonck其他文献
Parallel Programming of General-Purpose Programs Using Task-Based Programming Models
使用基于任务的编程模型对通用程序进行并行编程
- DOI:
- 发表时间:
2011 - 期刊:
- 影响因子:0
- 作者:
Hans Vandierendonck;Polyvios Pratikakis;Dimitrios S. Nikolopoulos - 通讯作者:
Dimitrios S. Nikolopoulos
Towards automatic program partitioning
走向自动程序分区
- DOI:
10.1145/1531743.1531759 - 发表时间:
2009 - 期刊:
- 影响因子:0
- 作者:
S. Rul;Hans Vandierendonck;K. D. Bosschere - 通讯作者:
K. D. Bosschere
A significance-driven programming framework for energy-constrained approximate computing
用于能量约束近似计算的显着性驱动编程框架
- DOI:
10.1145/2742854.2742857 - 发表时间:
2015 - 期刊:
- 影响因子:0
- 作者:
V. Vassiliadis;Charalampos Chalios;K. Parasyris;C. Antonopoulos;S. Lalis;Nikolaos Bellas;Hans Vandierendonck;Dimitrios S. Nikolopoulos - 通讯作者:
Dimitrios S. Nikolopoulos
PGT: a prompt based generative transformer for the patent domain
PGT:专利领域基于提示的生成变压器
- DOI:
- 发表时间:
2022 - 期刊:
- 影响因子:0
- 作者:
Dimitrios Christofidellis;Antonio Berrios Torres;A. Dave;M. Roveri;Kristin Schmidt;Sarath Swaminathan;Hans Vandierendonck;D. Zubarev;Matteo Manica - 通讯作者:
Matteo Manica
Language and Runtime System: Requirements
语言和运行时系统:要求
- DOI:
- 发表时间:
2016 - 期刊:
- 影响因子:0
- 作者:
Hans Vandierendonck - 通讯作者:
Hans Vandierendonck
Hans Vandierendonck的其他文献
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{{ truncateString('Hans Vandierendonck', 18)}}的其他基金
The Kelvin Living Lab: Towards Net Zero High-Performance Computing
开尔文生活实验室:迈向净零高性能计算
- 批准号:
EP/Z531054/1 - 财政年份:2024
- 资助金额:
$ 25.77万 - 项目类别:
Research Grant
Relaxed Semantics Across the Data Analytics Stack
整个数据分析堆栈的宽松语义
- 批准号:
EP/X029174/1 - 财政年份:2023
- 资助金额:
$ 25.77万 - 项目类别:
Research Grant
DiPET: Distributed Stream Processing on Fog and Edge Systems via Transprecise Computing
DiPET:通过 Transprecise 计算在雾和边缘系统上进行分布式流处理
- 批准号:
EP/T022345/1 - 财政年份:2020
- 资助金额:
$ 25.77万 - 项目类别:
Research Grant
Hybrid Static/Dynamic Scheduling for Task Dataflow Parallel Programs
任务数据流并行程序的混合静态/动态调度
- 批准号:
EP/L027402/1 - 财政年份:2014
- 资助金额:
$ 25.77万 - 项目类别:
Research Grant
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