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Enabling CXL Memory Expansion for In-Memory Database Management Systems

Minseon Ahn, Andrew Chang, Donghun Lee, Jongmin Gim, Jungmin Kim, Jaemin Jung, Oliver Rebholz, Vincent T. Pham, Krishna T. Malladi, Yang Seok Ki

2022Data Management on New Hardware54 citationsDOIOpen Access PDF

Abstract

Limited memory volume is always a performance bottleneck in an in-memory database management system (IMDBMS) as the data size keeps increasing. To overcome the physical memory limitation, heterogeneous and disaggregated computing platforms are proposed, such as Gen-Z, CCIX, OpenCAPI, and CXL. In this work, we introduce flexible CXL memory expansion using a CXL type 3 prototype and evaluate its performance in an IMDBMS. Our evaluation shows that CXL memory devices interfaced with PCIe Gen5 are appropriate for memory expansion with nearly no throughput degradation in OLTP workloads and less than 8% throughput degradation in OLAP workloads. Thus, CXL memory is a good candidate for memory expansion with lower TCO in IMDBMSs.

Topics & Concepts

Computer scienceBottleneckOnline analytical processingThroughputMemory managementOnline transaction processingMemory mapIn-Memory ProcessingDatabaseOperating systemSemiconductor memoryEmbedded systemDatabase transactionTransaction processingSearch engineInformation retrievalData warehouseWirelessWeb search queryQuery by ExampleAdvanced Data Storage TechnologiesCloud Computing and Resource ManagementParallel Computing and Optimization Techniques
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