Trimma: Trimming Metadata Storage and Latency for Hybrid Memory Systems

Hybrid main memory systems combine both performance and capacity advantages from heterogeneous memory technologies. With larger capacities, higher associativities, and finer granularities, hybrid memory systems currently exhibit significant metadata storage and lookup overheads for flexibly remapping data blocks between the two memory tiers. To alleviate the inefficiencies of existing designs, we propose Trimma, the combination of a multi-level metadata structure and an efficient metadata cache design. Trimma uses a multi-level metadata table to only track truly necessary address remap entries. The saved memory space is effectively utilized as extra DRAM cache capacity to improve performance. Trimma also uses separate formats to store the entries with non-identity and identity address mappings. This improves the overall remap cache hit rate, further boosting the performance. Trimma is transparent to software and compatible with various types of hybrid memory systems. When evaluated on a representative hybrid memory system with HBM3 and DDR5, Trimma achieves up to 1.68 × and on average 1.33 × speedup benefits, compared to state-of-the-art hybrid memory designs. These results show that Trimma effectively addresses metadata management overheads, especially for future scalable large-scale hybrid memory architectures.

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Publication Details

Published
2024-10-11
DOI
https://doi.org/10.1145/3656019.3689612
Citations
1
Primary Topic
Advanced Data Storage Technologies
Type
article
Field-Weighted Citation Impact
0.35
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Trimma: Trimming Metadata Storage and Latency for Hybrid Memory Systems

Yiwei Li, Mingyu Gao, Boyu Tian
1 citations
Advanced Data Storage Technologies
0.35
article

Trimma: Trimming Metadata Storage and Latency for Hybrid Memory Systems

Yiwei Li, Mingyu Gao, Boyu Tian
article en
1 citations

Abstract

Hybrid main memory systems combine both performance and capacity advantages from heterogeneous memory technologies. With larger capacities, higher associativities, and finer granularities, hybrid memory systems currently exhibit significant metadata storage and lookup overheads for flexibly remapping data blocks between the two memory tiers. To alleviate the inefficiencies of existing designs, we propose Trimma, the combination of a multi-level metadata structure and an efficient metadata cache design. Trimma uses a multi-level metadata table to only track truly necessary address remap entries. The saved memory space is effectively utilized as extra DRAM cache capacity to improve performance. Trimma also uses separate formats to store the entries with non-identity and identity address mappings. This improves the overall remap cache hit rate, further boosting the performance. Trimma is transparent to software and compatible with various types of hybrid memory systems. When evaluated on a representative hybrid memory system with HBM3 and DDR5, Trimma achieves up to 1.68 × and on average 1.33 × speedup benefits, compared to state-of-the-art hybrid memory designs. These results show that Trimma effectively addresses metadata management overheads, especially for future scalable large-scale hybrid memory architectures.

ShangHai JiAi Genetics & IVF Institute (CN), Tsinghua University (CN)
Affordable and clean energy
Openalex Percentile: Top 38%
Advanced Data Storage Technologies
0.35
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