Exploiting Locality in Flat Memory with CXL for In-Memory Database Management Systems
Minseon Ahn, Thomas Willhalm, Donghun Lee, Norman May, Jungmin Kim, Daniel Ritter, Oliver Rebholz · 2025
Memory tiering is an effective strategy for enhancing the memoryto-core ratio in modern compute servers.Intel's Flat Memory Mode (FLAT) represents a cutting-edge, hardware-managed memory tiering system for CXL memory, operating at cache-line (64B) granularity with yet unknown potential for database management systems.In this paper, we evaluate the performance of FLAT using OLAP workloads in SAP HANA, an in-memory database management system.Our findings demonstrate that flat memory outperforms directly attached CXL memory by leveraging data placement and exploiting locality.However, FLAT currently accepts only a 1:1 ratio between local and CXL memory.When the local memory capacity increases, FLAT operates in a mixed mode (MIXED) containing flat memory and additional dedicated memory with remaining local memory in a separate NUMA node.Our evaluation of MIXED shows that performance degradation depends on access patterns and the amount of exploited data locality when moving table data to flat memory or allocating heap memory in flat memory.To address the configuration complexity of two separate NUMA nodes in MIXED, we propose a new CONSOLIDATED mode that merges two NUMA nodes.Our evaluation shows that the consolidated mode results in negligible performance degradation, regardless of the ratio between dedicated memory and flat memory, and requires no software modifications at the application level.