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@INPROCEEDINGS{Tsai:1052213,
author = {Tsai, Yu-Hsiang and Bode, Mathis and Anzt, Hartwig},
title = {{W}hat {W}ill the {G}race {H}opper-{P}owered {J}upiter
{S}upercomputer {B}ring for {S}parse {L}inear {A}lgebra?},
address = {New York, NY, USA},
publisher = {ACM New York, NY, USA},
reportid = {FZJ-2026-00840},
pages = {228 - 235},
year = {2026},
abstract = {The first exascale supercomputer in Europe, JUPITER, is
currently being built using the NVIDIA Grace Hopper
superchips as main building blocks. JUPITER is designed to
provide computing power for both data-driven (AI) workloads
and numerics-based simulation workloads. For both workload
types, and particularly for PDE-based simulations,
high-performance sparse linear algebra operations are
crucial. In this paper, we analyze the performance levels
that sparse linear algebra operations can achieve on the
JUPITER supercomputer and identify algorithmic modifications
that can improve performance by acknowledging the Grace
Hopper architecture.},
month = {Jan},
date = {2026-01-26},
organization = {SCA/HPCAsia 2026: Supercomputing Asia
and International Conference on High
Performance Computing in Asia Pacific
Region, Osaka (Japan), 26 Jan 2026 - 29
Jan 2026},
cin = {JSC},
cid = {I:(DE-Juel1)JSC-20090406},
pnm = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
and Research Groups (POF4-511) / Inno4Scale - Innovative
Algorithms for Applications on European Exascale
Supercomputers (101118139)},
pid = {G:(DE-HGF)POF4-5112 / G:(EU-Grant)101118139},
typ = {PUB:(DE-HGF)8},
doi = {10.1145/3773656.3773691},
url = {https://juser.fz-juelich.de/record/1052213},
}