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Understanding and Profiling CXL.mem Using PathFinder

Xiao Li, Zerui Guo, Yuebin Bai, Mahesh Ketkar, Hugh Wilkinson, Ming Liu

2025Year
6Citations
5Top-tier citations

Abstract

CXL.mem and the resulting memory pool are promising and gaining great attention. Unlike local memory, CXL DIMMs stay at the I/O subsystem, whose inferior performance can easily impact the processor pipeline and memory subsystem, yielding performance interference, hardware contention, obscure behaviors, and underutilized communication and computing resources. However, our community lacks a tool to understand and profile the CXL.mem protocol execution end-to-end between CPU and remote DIMM.

This paper fills the gap by designing and implementing PathFinder 1 , a systematic, informative, and lightweight CXL.mem profiler. PathFinder leverages the capabilities of existing hardware performance monitors (PMUs) and dissects the CXL.mem protocol at adequate granularities. Our key idea is to view the server processor and its chipset as a multi-stage Clos network, equip each architectural module with a PMU-based telemetry engine, track different CXL.mem paths, and apply conventional traffic analysis techniques. PathFinder performs snapshot-based path-driven profiling and introduces four techniques, i.e., path construction, stall cycle breakdown, interference analyzer, and cross-snapshot analysis. We build PathFinder atop Linux Perf and apply it to seven case studies.

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