Evaluating Emerging CXL-enabled Memory Pooling for HPC Systems

Jacob Wahlgren, M. Gokhale, I. Peng
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引用次数: 9

Abstract

Current HPC systems provide memory resources that are statically configured and tightly coupled with compute nodes. However, workloads on HPC systems are evolving. Diverse workloads lead to a need for configurable memory resources to achieve high performance and utilization. In this study, we evaluate a memory subsystem design leveraging CXL-enabled memory pooling. Two promising use cases of composable memory subsystems are studied – fine-grained capacity provisioning and scalable bandwidth provisioning. We developed an emulator to explore the performance impact of various memory compositions. We also provide a profiler to identify the memory usage patterns in applications and their optimization opportunities. Seven scientific and six graph applications are evaluated on various emulated memory configurations. Three out of seven scientific applications had less than 10% performance impact when the pooled memory backed 75% of their memory footprint. The results also show that a dynamically configured high-bandwidth system can effectively support bandwidth-intensive unstructured mesh-based applications like OpenFOAM. Finally, we identify interference through shared memory pools as a practical challenge for adoption on HPC systems.
为HPC系统评估新兴的支持cxl的内存池
当前的HPC系统提供的内存资源是静态配置的,并且与计算节点紧密耦合。然而,HPC系统上的工作负载正在不断发展。不同的工作负载导致需要可配置的内存资源来实现高性能和利用率。在本研究中,我们评估了利用支持cxl的内存池的内存子系统设计。研究了可组合内存子系统的两个有前途的用例——细粒度容量供应和可扩展带宽供应。我们开发了一个模拟器来探索不同内存组合对性能的影响。我们还提供了一个分析器来识别应用程序中的内存使用模式及其优化机会。七个科学和六个图形应用程序在各种模拟内存配置上进行了评估。当池内存支持75%的内存占用时,七分之三的科学应用程序的性能影响不到10%。结果还表明,动态配置的高带宽系统可以有效地支持带宽密集型非结构化网格应用程序,如OpenFOAM。最后,我们将通过共享内存池的干扰识别为在高性能计算系统上采用的实际挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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