Scythe: A Low-latency RDMA-enabled Distributed Transaction System for Disaggregated Memory

IF 1.5 3区 计算机科学 Q4 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
Kai Lu, Siqi Zhao, Haikang Shan, Qiang Wei, Guokuan Li, Jiguang Wan, Ting Yao, Huatao Wu, Daohui Wang
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引用次数: 0

Abstract

Disaggregated memory separates compute and memory resources into independent pools connected by RDMA (Remote Direct Memory Access) networks, which can improve memory utilization, reduce cost, and enable elastic scaling of compute and memory resources. However, existing RDMA-based distributed transactions on disaggregated memory suffer from severe long-tail latency under high-contention workloads.

In this paper, we propose Scythe, a novel low-latency RDMA-enabled distributed transaction system for disaggregated memory. Scythe optimizes the latency of high-contention transactions in three approaches: 1) Scythe proposes a hot-aware concurrency control policy that uses optimistic concurrency control (OCC) to improve transaction processing efficiency in low-conflict scenarios. Under high conflicts, Scythe designs a timestamp-ordered OCC (TOCC) strategy based on fair locking to reduce the number of retries and cross-node communication overhead. 2) Scythe presents an RDMA-friendly timestamp service for improved timestamp management. 3) Scythe designs an RDMA-optimized RPC framework to improve RDMA bandwidth utilization. The evaluation results show that, compared to state-of-the-art distributed transaction systems, Scythe achieves more than 2.5 × lower latency with 1.8 × higher throughput under high-contention workloads.

Scythe:面向分解内存的低延迟 RDMA 分布式事务系统
分解内存将计算和内存资源分成独立的池,通过 RDMA(远程直接内存访问)网络连接起来,可以提高内存利用率,降低成本,并实现计算和内存资源的弹性扩展。然而,现有的基于 RDMA 的分解内存分布式事务在高负载情况下存在严重的长尾延迟问题。在本文中,我们提出了适用于分解内存的新型低延迟 RDMA 分布式事务系统 Scythe。Scythe 通过三种方法优化了高延迟事务的延迟:1) Scythe 提出了一种热感知并发控制策略,使用乐观并发控制(OCC)来提高低冲突情况下的事务处理效率。在高冲突情况下,Scythe 设计了一种基于公平锁定的时间戳排序 OCC(TOCC)策略,以减少重试次数和跨节点通信开销。2) Scythe 提出了一种 RDMA 友好型时间戳服务,以改进时间戳管理。3) Scythe 设计了一个 RDMA 优化 RPC 框架,以提高 RDMA 带宽利用率。评估结果表明,与最先进的分布式事务处理系统相比,Scythe 在高竞争工作负载下实现了超过 2.5 倍的低延迟和 1.8 倍的高吞吐量。
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来源期刊
ACM Transactions on Architecture and Code Optimization
ACM Transactions on Architecture and Code Optimization 工程技术-计算机:理论方法
CiteScore
3.60
自引率
6.20%
发文量
78
审稿时长
6-12 weeks
期刊介绍: ACM Transactions on Architecture and Code Optimization (TACO) focuses on hardware, software, and system research spanning the fields of computer architecture and code optimization. Articles that appear in TACO will either present new techniques and concepts or report on experiences and experiments with actual systems. Insights useful to architects, hardware or software developers, designers, builders, and users will be emphasized.
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