借助真正支持CXL的系统与设备揭开CXL内存的神秘面纱
Demystifying CXL Memory with Genuine CXL-Ready Systems and Devices
AI总结：
本文首次基于真实CXL系统与设备开展全面评估，揭示模拟与真实CXL内存的关键差异，提出感知CXL内存的动态页分配策略Caption，可将带宽密集型应用性能最高提升24%。
摘要：
对更大容量、更高带宽内存的需求持续增长，推动了基于Compute eXpress Link（计算高速链路，简称CXL）的内存扩展与分解技术的近期创新。尤其是基于CXL的内存扩展技术，近期备受关注，因为它不仅能以经济的方式扩展内存容量与带宽，还能将内存技术与CPU的特定内存接口解耦。然而，由于CXL内存设备尚未广泛普及，此前研究一直使用远程NUMA（非一致性内存访问）节点中的DDR内存来模拟CXL内存。\n本文首次基于最新的第四代Intel Xeon CPU，搭配三款不同厂商的CXL内存设备，对真正支持CXL的系统开展了全面评估。具体而言，我们运行了一组微基准测试，既对比了真实CXL内存与模拟CXL内存的性能，也深入分析了CPU与CXL内存之间复杂的相互作用。这揭示了模拟CXL内存与真实CXL内存之间的重要差异，其中部分差异将促使研究人员重新审视近期工作中的分析与方案。随后，我们明确了内存带宽密集型应用可从CXL内存使用中获益的机会。最后，我们提出了一种感知CXL内存的动态页分配策略Caption，以更高效地将CXL内存用作带宽扩展器。我们证实，Caption能自动收敛到经验上最优的CXL内存页分配比例，与针对传统NUMA系统设计的默认页分配策略相比，可将内存带宽密集型应用的性能提升最高达24%。
英文摘要：
The ever-growing demands for memory with larger capacity and higher bandwidth have driven recent innovations on memory expansion and disaggregation technologies based on Compute eXpress Link (CXL). Especially, CXL-based memory expansion technology has recently gained notable attention for its ability not only to economically expand memory capacity and bandwidth but also to decouple memory technologies from a specific memory interface of the CPU. However, since CXL memory devices have not been widely available, they have been emulated using DDR memory in a remote NUMA node. In this paper, for the first time, we comprehensively evaluate a true CXL-ready system based on the latest 4th-generation Intel Xeon CPU with three CXL memory devices from different manufacturers. Specifically, we run a set of microbenchmarks not only to compare the performance of true CXL memory with that of emulated CXL memory but also to analyze the complex interplay between the CPU and CXL memory in depth. This reveals important differences between emulated CXL memory and true CXL memory, some of which will compel researchers to revisit the analyses and proposals from recent work. Next, we identify opportunities for memory-bandwidth-intensive applications to benefit from the use of CXL memory. Lastly, we propose a CXL-memory-aware dynamic page allocation policy, Caption to more efficiently use CXL memory as a bandwidth expander. We demonstrate that Caption can automatically converge to an empirically favorable percentage of pages allocated to CXL memory, which improves the performance of memory-bandwidth-intensive applications by up to 24% when compared to the default page allocation policy designed for traditional NUMA systems.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
