TY - JOUR
T1 - Shifting sands of hardware and software in exascale quantum mechanical simulations
AU - Shinde, Ravindra
AU - Filippi, Claudia
AU - Scemama, Anthony
AU - Jalby, William
PY - 2025/4/25
Y1 - 2025/4/25
N2 - The era of exascale computing presents both exciting opportunities and unique challenges for quantum mechanical simulations. Although the transition from petaflops to exascale computing has been marked by a steady increase in computational power, it is accompanied by a shift towards heterogeneous architectures, with graphical processing units (GPUs) in particular gaining a dominant role. The exascale era therefore demands a fundamental shift in software development strategies. This Perspective 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.
AB - The era of exascale computing presents both exciting opportunities and unique challenges for quantum mechanical simulations. Although the transition from petaflops to exascale computing has been marked by a steady increase in computational power, it is accompanied by a shift towards heterogeneous architectures, with graphical processing units (GPUs) in particular gaining a dominant role. The exascale era therefore demands a fundamental shift in software development strategies. This Perspective 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.
KW - 2025 OA procedure
UR - http://www.scopus.com/inward/record.url?scp=105003721333&partnerID=8YFLogxK
U2 - 10.1038/s42254-025-00823-7
DO - 10.1038/s42254-025-00823-7
M3 - Article
SN - 2522-5820
JO - Nature Reviews Physics
JF - Nature Reviews Physics
M1 - e1692
ER -