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Re-LSM: A ReRAM-Based Processing-in-Memory Framework for LSM-Based Key-Value Store

Published: 22 December 2022 Publication History

Abstract

Log-structured merge (LSM) tree based key-value (KV) stores organize writes into hierarchical batches for high-speed writing. However, the notorious compaction process of LSM-tree severely hurts system performance. It not only involves huge I/O operations but also consumes tremendous computation and memory resources. In this paper, first we find that when compaction happens in the high levels (i.e., L0, L1) of the LSM-tree, it may saturate all system computation and memory resources, and eventually stall the whole system. Based on this observation, we present Re-LSM, a ReRAM-based Processing-in-Memory (PIM) framework for LSM-based Key-Value Store. Specifically, in Re-LSM, we propose to offload certain computation and memory-intensive tasks in the high levels of the LSM-tree to the ReRAM-based PIM space. A high parallel ReRAM compaction accelerator is designed by decomposing the three-phased compaction into basic logic operating units. Evaluation results based on db_bench and YCSB show that Re-LSM achieves 2.2× improvement on the throughput of random writes compared to RocksDB, and the ReRAM-based compaction accelerator speedups the CPU-based implementation by 64.3× and saves 25.5× energy.

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  • (2023) A Write-Optimized PM-oriented B + -tree with Aligned Flush and Selective Migration 2023 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom)10.1109/ISPA-BDCloud-SocialCom-SustainCom59178.2023.00135(789-794)Online publication date: 21-Dec-2023

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cover image ACM Conferences
ICCAD '22: Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design
October 2022
1467 pages
ISBN:9781450392174
DOI:10.1145/3508352
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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New York, NY, United States

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Published: 22 December 2022

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Author Tags

  1. KV store
  2. LSM-tree
  3. compaction
  4. processing-in-memory

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  • Research-article

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ICCAD '22
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ICCAD '22: IEEE/ACM International Conference on Computer-Aided Design
October 30 - November 3, 2022
California, San Diego

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  • (2023) A Write-Optimized PM-oriented B + -tree with Aligned Flush and Selective Migration 2023 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom)10.1109/ISPA-BDCloud-SocialCom-SustainCom59178.2023.00135(789-794)Online publication date: 21-Dec-2023

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