research-article

Linearly compressed pages: a low-complexity, low-latency main memory compression framework

Authors:

Gennady Pekhimenko,

Vivek Seshadri,

Phillip B. Gibbons,

Michael A. Kozuch,

Todd C. MowryAuthors Info & Claims

MICRO-46: Proceedings of the 46th Annual IEEE/ACM International Symposium on Microarchitecture

Pages 172 - 184

https://doi.org/10.1145/2540708.2540724

Published: 07 December 2013 Publication History

Abstract

Data compression is a promising approach for meeting the increasing memory capacity demands expected in future systems. Unfortunately, existing compression algorithms do not translate well when directly applied to main memory because they require the memory controller to perform non-trivial computation to locate a cache line within a compressed memory page, thereby increasing access latency and degrading system performance. Prior proposals for addressing this performance degradation problem are either costly or energy inefficient.

By leveraging the key insight that all cache lines within a page should be compressed to the same size, this paper proposes a new approach to main memory compression--Linearly Compressed Pages (LCP)--that avoids the performance degradation problem without requiring costly or energy-inefficient hardware. We show that any compression algorithm can be adapted to fit the requirements of LCP, and we specifically adapt two previously-proposed compression algorithms to LCP: Frequent Pattern Compression and Base-Delta-Immediate Compression.

Evaluations using benchmarks from SPEC CPU2006 and five server benchmarks show that our approach can significantly increase the effective memory capacity (by 69% on average). In addition to the capacity gains, we evaluate the benefit of transferring consecutive compressed cache lines between the memory controller and main memory. Our new mechanism considerably reduces the memory bandwidth requirements of most of the evaluated benchmarks (by 24% on average), and improves overall performance (by 6.1%/13.9%/10.7% for single-/two-/four-core workloads on average) compared to a baseline system that does not employ main memory compression. LCP also decreases energy consumed by the main memory subsystem (by 9.5% on average over the best prior mechanism).

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Linearly compressed pages: a low-complexity, low-latency main memory compression framework

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cover image ACM Conferences

MICRO-46: Proceedings of the 46th Annual IEEE/ACM International Symposium on Microarchitecture

December 2013

498 pages

ISBN:9781450326384

DOI:10.1145/2540708

General Chair:
Matthew Farrens
UC Davis
,
Program Chair:
Christos Kozyrakis
Stanford University

Copyright © 2013 ACM.

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Published: 07 December 2013

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MICRO-46: The 46th Annual IEEE/ACM International Symposium on Microarchitecture

December 7 - 11, 2013

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Overall Acceptance Rate 484 of 2,242 submissions, 22%

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https://doi.org/10.1109/VLSID64188.2025.00029
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