HMComp: Extending Near-Memory Capacity using Compression in Hybrid Memory
Paper in proceeding, 2024

Hybrid memories, especially combining a first-tier near memory using High-Bandwidth Memory (HBM) and a second-tier far memory using DRAM, can realize a large and low cost, high-bandwidth main memory. State-of-the-art hybrid memories typically use a flat hierarchy where blocks are swapped between near and far memory based on bandwidth demands. However, this may cause significant overheads for metadata storage and traffic. While using a fixed-size, near-memory cache and compressing data in near memory can help, precious near-memory capacity is still wasted by the cache and the metadata needed to manage a compressed hybrid memory. This paper proposes HMComp, a flat hybrid-memory architecture, in which compression techniques free up near-memory capacity to be used as a cache for far memory data to cut down swap traffic without sacrificing any memory capacity. Moreover, through a carefully crafted metadata layout, we show that metadata can be stored in less costly far memory, thus avoiding to waste any near-memory capacity. Overall, HMComp offers a speedup of single-thread performance of up to 22%, on average 13%, and traffic reduction due to swapping of up to 60% and by 41% on average compared to flat hybrid memory designs.

Memory Compression

HBM

Hybrid Memory

Memory Management

Author

Qi Shao

Chalmers, Computer Science and Engineering (Chalmers), Computer Engineering (Chalmers)

Angelos Arelakis

ZeroPoint Technologies

Per Stenström

ZeroPoint Technologies

Chalmers, Computer Science and Engineering (Chalmers), Computer and Network Systems

Proceedings of the International Conference on Supercomputing

74-84
9798400706103 (ISBN)

38th ACM International Conference on Supercomputing, ICS 2024
Kyoto, Japan,

Subject Categories

Computer Engineering

DOI

10.1145/3650200.3656612

More information

Latest update

7/1/2024 8