The Persistent Challenge of Data Locality in the Post-Exascale Era
The era of exascale computing, exemplified by systems like Frontier, achieving exaflop-level performance marks a milestone. However, the quest for sheer compute power leads to strong imbalance in system design. Hence, scaling advancements in memory, network bandwidth, and storage are also necessary and poses challenges, with a crucial need to address data locality issues. This paper underscores the fundamental importance of data locality as a key abstraction for optimizing application performance. Despite notable software solutions, the growing complexity of parallelism and memory hierarchy demands performance portable data locality solutions across diverse computing platforms. The manuscript revisits data locality aspects, covering hardware considerations, application perspectives, software stack abstractions and tool support. It concludes with insights into data locality challenges and opportunities, emphasizing the ongoing significance of collaborative research for progress in this critical issue.
Authors
- Emmanuel Jeannot (ORCID: https://orcid.org/0000-0002-3956-2997)
- John Shalf
- Didem Unat (ORCID: https://orcid.org/0000-0002-2351-0770)
- Anshu Dubey (ORCID: https://orcid.org/0000-0003-3299-7426)
Institutions
- Argonne National Laboratory (US)
- Institut national de recherche en sciences et technologies du numérique (FR)
- Koç University (TR)
- Lawrence Berkeley National Laboratory (US)
- Université de Bordeaux (FR)
- Laboratoire Bordelais de Recherche en Informatique (FR)
Publication Details
- Journal
- Computing in Science & Engineering
- Published
- 2025-05-07
- DOI
- https://doi.org/10.1109/mcse.2025.3567586
- Primary Topic
- Big Data Technologies and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00