CXL Memory Performance for In-Memory Data Processing

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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Publication Details

Journal
Proceedings of the VLDB Endowment
Published
2025-05-01
DOI
https://doi.org/10.14778/3746405.3746432
Citations
1
Primary Topic
Advanced Data Storage Technologies
Type
article
Field-Weighted Citation Impact
1.49
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CXL Memory Performance for In-Memory Data Processing

Marcel Weisgut, Tilmann Rabl, Pınar Tözün, Daniel Ritter et al.
1 citations
Proceedings of the VLDB Endowment
Advanced Data Storage Technologies
1.49
article

CXL Memory Performance for In-Memory Data Processing

Marcel Weisgut, Tilmann Rabl, Pınar Tözün, Daniel Ritter, Lawrence Benson
article en
1 citations

Abstract

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.

Proceedings of the VLDB EndowmentVol. 18(9)
Hasso Plattner Institute (DE), University of Potsdam (DE), Systems, Applications & Products in Data Processing (Germany) (DE), IT University of Copenhagen (DK)
Openalex Percentile: Top 13%
Advanced Data Storage Technologies
1.49
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