Asynchronous Scientific Continuous Computations Exploiting Disaggregation (ASCCED)

高效和可扩展的科学模拟软件的设计正在达到一个临界点，持续的进步越来越困难，劳动密集型，因此实现成本更高。这一挑战源于大规模高性能计算系统的不断发展的设计。世界领先的（前）兆级系统及其后继产品的特点是数百万规模的并行计算活动和高度异构的处理器类型混合，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的计算单元。开发高效的，可扩展的科学仿真软件，这些系统变得越来越困难，因为在模拟代码的并行性的限制。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，软件会反复优化和重新优化，因为硬件中可能每隔几年就会发生有影响力的变化。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，并使软件更健壮，以适应未来计算硬件的发展。我们的方法的关键区别因素是结构的科学模拟软件作为一个松散耦合的并行活动的集合。我们将探讨应用以前开发的并行离散事件仿真（PDES）编排这些松散耦合的并行活动的技术的机遇和挑战。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规模，并最大限度地减少由于同步而导致的性能低下。ASCCED提出的计算模型如果成功，将在高性能计算的编程模型中开创一个新的研究方向，这不仅会极大地影响科学仿真软件的性能，而且还可以减少产生有效的科学模拟软件所需的工程工作。它将对高度依赖领导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。

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 One may thus find that the guiding principles that underpin such software are outdated.The ASCCED project will fundamentally change the status quo in the design of scientific simulation software by simplifying the design to reduce software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