Ravindra Shinde, Claudia Filippi, Anthony Scemama, William Jalby
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引用次数: 0
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.