Remote Memory Prefetching: Is Coarse-grained Fine?

CXL raises new questions about tiering, pooling, and remote memory access. In most disaggregated memory approaches, compute nodes access remote memory pools at page (4~KB) granularity. This is the case for two reasons: to help amortize high remote access costs and because the host CPUs' address translation hardware is set up for 4~KB pages. While fetching and caching whole remote pages helps with applications that have high spatial locality, for some applications it can introduce contention for cache capacity since potentially cold or unrelated adjacent data is also cached. Additionally, this can increase network bandwidth utilization.

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Published
2025-05-03
DOI
https://doi.org/10.1145/3680256.3721318
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
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article

Remote Memory Prefetching: Is Coarse-grained Fine?

Ryan Stutsman, Vinita Pawar, James McMahon
Parallel Computing and Optimization Techniques
article

Remote Memory Prefetching: Is Coarse-grained Fine?

Ryan Stutsman, Vinita Pawar, James McMahon
article en

Abstract

CXL raises new questions about tiering, pooling, and remote memory access. In most disaggregated memory approaches, compute nodes access remote memory pools at page (4~KB) granularity. This is the case for two reasons: to help amortize high remote access costs and because the host CPUs' address translation hardware is set up for 4~KB pages. While fetching and caching whole remote pages helps with applications that have high spatial locality, for some applications it can introduce contention for cache capacity since potentially cold or unrelated adjacent data is also cached. Additionally, this can increase network bandwidth utilization.

University of Utah (US)
Zero hunger
Openalex Percentile: Top 92%
Parallel Computing and Optimization Techniques
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