PET: Proactive Demotion for Efficient Tiered Memory Management

Tiered memory is a promising approach for increasing main-memory capacity at a lower cost by using DRAM as the upper tier (fast memory) and slower-but-cheap byte-addressable memory as the lower tier (slow memory). A proactive demotion, one of the ways to use tiered memory efficiently, demotes cold data to slow memory even when fast memory has sufficient free space. Prior works have utilized proactive demotion to reduce the high cost of main memory by reducing applications' resident set size in fast memory. Further, proactive demotion helps mitigate severe performance degradation caused by fast memory shortages when there is a spike in demand for hot data. Still, we observe that leveraging memory access locality within the allocation units of applications enables larger fast-memory savings with lower system overhead.

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Publication Details

Published
2025-03-26
DOI
https://doi.org/10.1145/3689031.3717471
Citations
4
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
9.08
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article

PET: Proactive Demotion for Efficient Tiered Memory Management

Kwanhee Kyung, Yaebin Moon, Eojin Lee, Seoyoung Ko et al.
4 citations
Parallel Computing and Optimization Techniques
9.08
article

PET: Proactive Demotion for Efficient Tiered Memory Management

Kwanhee Kyung, Yaebin Moon, Eojin Lee, Seoyoung Ko, Jung Ho Ahn, Wanju Doh, Seunghwan Chung
article en
4 citations

Abstract

Tiered memory is a promising approach for increasing main-memory capacity at a lower cost by using DRAM as the upper tier (fast memory) and slower-but-cheap byte-addressable memory as the lower tier (slow memory). A proactive demotion, one of the ways to use tiered memory efficiently, demotes cold data to slow memory even when fast memory has sufficient free space. Prior works have utilized proactive demotion to reduce the high cost of main memory by reducing applications' resident set size in fast memory. Further, proactive demotion helps mitigate severe performance degradation caused by fast memory shortages when there is a spike in demand for hot data. Still, we observe that leveraging memory access locality within the allocation units of applications enables larger fast-memory savings with lower system overhead.

Seoul National University (KR), Inha University (KR), Samsung (South Korea) (KR)
Openalex Percentile: Top 3%
Parallel Computing and Optimization Techniques
9.08
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