Exploring Performance and Cost Optimization with ASIC-Based CXL Memory
Yupeng Tang, Ping Zhou, Wenhui Zhang, Henry Hu, Qirui Yang, Hao Xiang, Tongping Liu, Jiaxin Shan, Ruoyun Huang, Cheng Zhao, Cheng Chen, Hui Zhang
Abstract
As memory-intensive applications continue to drive the need for advanced architectural solutions, Compute Express Link (CXL) has risen as a promising interconnect technology that enables seamless high-speed, low-latency communication between host processors and various peripheral devices. In this study, we explore the application performance of ASIC CXL memory in various data-center scenarios. We then further explore multiple potential impacts (e.g., throughput, latency, and cost reduction) of employing CXL memory via carefully designed policies and strategies. Our empirical results show the high potential of CXL memory, reveal multiple intriguing observations of CXL memory and contribute to the wide adoption of CXL memory in real-world deployment environments. Based on our benchmarks, we also develop an Abstract Cost Model that can estimate the cost benefit from using CXL memory.
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Install the CLIlune papers get 665b5480-dc7c-42c5-b10e-10241bfc25a2Cited by top-tier papers18
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- CXL Memory Performance for In-Memory Data ProcessingMarcel Weisgut, Daniel Ritter, Pinar Tözün, Lawrence Benson et al.VLDB 2025 · 7 citations
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