Exascale Quantum Mechanical Simulations: Navigating the Shifting Sands of Hardware and Software

Ravindra Shinde, Claudia Filippi, Anthony Scemama, William Jalby
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Abstract

The era of exascale computing presents both exciting opportunities and unique challenges for quantum mechanical simulations. While the transition from petaflops to exascale computing has been marked by a steady increase in computational power, the shift towards heterogeneous architectures, particularly the dominant role of graphical processing units (GPUs), demands a fundamental shift in software development strategies. This review examines the changing landscape of hardware and software for exascale computing, highlighting the limitations of traditional algorithms and software implementations in light of the increasing use of heterogeneous architectures in high-end systems. We discuss the challenges of adapting quantum chemistry software to these new architectures, including the fragmentation of the software stack, the need for more efficient algorithms (including reduced precision versions) tailored for GPUs, and the importance of developing standardized libraries and programming models.
超大规模量子力学模拟:驾驭硬件和软件的风云变幻
超大规模计算时代为量子力学模拟带来了令人兴奋的机遇和独特的挑战。虽然从千万亿次计算到超大规模计算的转变标志着计算能力的稳步提升,但向异构架构的转变,特别是图形处理器(GPU)的主导作用,要求软件开发策略发生根本性转变。这篇综述探讨了面向超大规模计算的硬件和软件的变化情况,强调了在高端系统中越来越多地使用异构架构的情况下,传统算法和软件实现的局限性。我们讨论了量子化学软件适应这些新架构所面临的挑战,包括软件堆栈的碎片化、为 GPU 量身定制更高效算法(包括降低精度版本)的必要性,以及开发标准化库和编程模型的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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