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Exploring Userspace Memory Mapping for RDMA-Enabled Network-Attached Memory
DescriptionMemory-bound applications like graph processing applications often require large memory capacity beyond a single node. Current HPC systems over-provision compute and memory resources to meet requirements of diverse workloads. In this work, we explore using network-attached memory for disaggregating memory from compute nodes to satisfy the demand of memory-intensive workloads. We provide a library that enables applications to access network-attached memory as if in its main memory, and exposes critical controls to userspace, including concurrency level and page-level data compression. Our preliminary results show that the flexibility of tuning concurrency and compression is important for improving performance and reducing data movement. Also, our results on 12 scientific data sets indicate that DPU compression offloading could significantly speed up compression and is important for future optimizations.
Event Type
ACM Student Research Competition: Graduate Poster
ACM Student Research Competition: Undergraduate Poster
Doctoral Showcase
Posters
Research Posters
Scientific Visualization & Data Analytics Showcase
TimeTuesday, 14 November 20235:15pm - 7pm MST
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TP