CXL Memory Performance for In-Memory Data Processing
Marcel Weisgut, Daniel Ritter, Pinar Tözün, Lawrence Benson, Tilmann Rabl
摘要
The Compute Express Link (CXL) standard enables new forms of memory management and access across devices and servers. Based on PCIe, it enables cache-coherent access to remote memory. This widens the design space for database systems by expanding the available memory beyond memory local to the CPU. Efficiently utilizing CXL-attached memory requires conscious decisions by data systems about data placement and management. In this paper, we provide an in-depth analysis of database operation performance with data interleaved across multiple CXL memory devices. We experimentally evaluate the memory access performance for basic access patterns, the performance impact of placing data across multiple CXL memory devices for in-memory column scans and in-memory B+tree operations, and the performance impact of placing data in CXL memory for an in-memory database system when running the analytical TPC-H workload. Our experiments show that access to CXL-attached memory does not have to penalize performance over local access, but careful workload-aware data management is required. Our TPC-H evaluation shows that placing table columns based on access frequencies allows storing over 80% of the table data in CXL memory with a performance of 85% of a local-memory-only solution.
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引用它的顶会 Paper4
- Octopus: Enhancing CXL Memory Pods via Sparse TopologyYuhong Zhong, Fiodar Kazhamiaka, Pantea Zardoshti, Shuwei Teng 等NSDI 2026 · 被引用 15 次
- SIDLE: Tree-structure Aware Indexes for CXL-based Heterogeneous MemoryHaoru Zhao, Mingkai Dong, Fangnuo Wu, Haibo ChenVLDB 2026 · 被引用 1 次
- Performance Predictability in Heterogeneous MemoryJinshu Liu, Hanchen Xu, Daniel S. Berger, Marcos K. Aguilera 等ASPLOS 2026 · 被引用 1 次
- MAC: Metadata Acceleration for Sustainable Performance in Big-Data Systems with CXL DRAMDusol Lee, Yan Sun, Houxiang Ji, Vinit Gupta 等OSDI 2026
它引用的顶会 Paper21
- An Empirical Guide to the Behavior and Use of Scalable Persistent MemoryJian Yang, Juno Kim, Morteza Hoseinzadeh, Joseph Izraelevitz 等FAST 2020 · 被引用 470 次
- Pond: CXL-Based Memory Pooling Systems for Cloud PlatformsHuaicheng Li, Daniel S. Berger, Lisa Hsu, Daniel Ernst 等ASPLOS 2023 · 被引用 328 次
- TPP: Transparent Page Placement for CXL-Enabled Tiered-MemoryHasan Al Maruf, Hao Wang, Abhishek Dhanotia, Johannes Weiner 等ASPLOS 2023 · 被引用 255 次
- Demystifying CXL Memory with Genuine CXL-Ready Systems and DevicesYan Sun, Yifan Yuan, Zeduo Yu, Reese Kuper 等MICRO 2023 · 被引用 133 次
- TMO: transparent memory offloading in datacentersJohannes Weiner, Niket Agarwal, Dan Schatzberg, Leon Yang 等ASPLOS 2022 · 被引用 103 次
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