Ruili Liu, Tsinghua University and University of Electronic Science and Technology of China; Teng Ma, Alibaba Group; Mingxing Zhang, Jialiang Huang, and Yingdi Shan, Tsinghua University; Zheng Liu, Alibaba Group; Lingfeng Xiang, Zhen Lin, Hui Lu, and Jia Rao, The University of Texas at Arlington; Kang Chen and Yongwei Wu, Tsinghua University
Tiered Memory is critical to manage heterogeneous memory devices, such as Persistent Memory or CXL Memory. Existing works make difficult trade-offs between optimal data placement and costly data movement. With the advent of Intel Data Streaming Accelerator (DSA), a CPU-free hardware to move data between memory regions, data movement can be up to 4× faster than a single CPU core. However, the fine memory movement granularity in Linux kernel undermines the potential performance improvement. To this end, we have developed DSA-2LM, a new tiered memory system that adaptively integrates DSA into page migration. The proposed framework integrates fast memory migration workflow and adaptable concurrent data paths with well-tuned DSA configurations. Experimental results show that, compared to three representative tiered memory works: MEMTIS, TPP and NOMAD, DSA-2LM can achieve 20%, 30% and 16% performance improvement under real-world applications.
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