Asynchronous Scientific Continuous Computations Exploiting Disaggregation (ASCCED)

利用分解的异步科学连续计算 (ASCCED)

• 批准号: EP/X01794X/1
• 负责人: Hans Vandierendonck
• 金额: $ 25.77万
• 依托单位: Queen's University Belfast
• 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: https://gtr.ukri.org/projects?ref=EP%2FX01794X%2F1
• 关键词: Asynchronous; Scientific; Continuous; Computations; Exploiting

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 One may thus find that the guiding principles that underpin such software are outdated.The ASCCED project will fundamentally change the status quo in the design of scientific simulation software by simplifying the design to reduce software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.

高效和可扩展的科学模拟软件的设计正达到一个临界点，在这个临界点上，持续的进步越来越困难，越来越劳动密集型，因此也更昂贵。这种挑战来自于大规模高性能计算系统的不断发展的设计。世界领先的（预）百亿亿级系统及其后继者，其特点是数百万级并行计算活动和处理器类型的高度异构混合，如高端多核处理器、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，科学的仿真软件必须分解成各种独立的组件，并同时使用各种异构计算单元。随着仿真代码的并行性极限的逼近，为这些系统开发高效、可扩展的科学仿真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几十年。随着目标硬件的设计和规模以更快的速度发展，软件被反复优化和重新优化，因为硬件可能每隔几年就会发生有影响的变化。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，简化设计，减少软件开发和维护工作，促进性能优化，并使软件更强大，以适应未来计算硬件的发展。我们方法的关键区别因素是将科学仿真软件结构为松散耦合并行活动的集合。我们将探讨应用先前为并行离散事件模拟（PDES）开发的技术来编排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提取前所未有的并行性规模，并最大限度地减少由于同步而导致的性能低下。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，将为高性能计算编程模型的研究开辟一个新的方向，这不仅可能极大地影响科学仿真软件的性能，而且还可以减少生产高效科学仿真软件所需的工程努力。它将对气候建模和癌症研究等高度依赖领导力计算能力的科学产生深远影响。