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UID:submissions.supercomputing.org_SC23_sess291_rpost154@linklings.com
SUMMARY:Exploring Userspace Memory Mapping for RDMA-Enabled Network-Attach
 ed Memory
DESCRIPTION:Jacob Wahlgren and Jennifer Faj (KTH Royal Institute of Techno
 logy, Sweden); Eric Green and Maya Gokhale (Lawrence Livermore National La
 boratory (LLNL)); and Ivy Peng (KTH Royal Institute of Technology, Sweden)
 \n\nMemory-bound applications like graph processing applications often req
 uire large memory capacity beyond a single node. Current HPC systems over-
 provision compute and memory resources to meet requirements of diverse wor
 kloads. In this work, we explore using network-attached memory for disaggr
 egating memory from compute nodes to satisfy the demand of memory-intensiv
 e workloads. We provide a library that enables applications to access netw
 ork-attached memory as if in its main memory, and exposes critical control
 s to userspace, including concurrency level and page-level data compressio
 n. 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 c
 ompression offloading could significantly speed up compression and is impo
 rtant for future optimizations.\n\nTag: Artificial Intelligence/Machine Le
 arning, Architecture and Networks, Heterogeneous Computing, I/O and File S
 ystems, Performance Measurement, Modeling, and Tools, Post-Moore Computing
 , Programming Frameworks and System Software, Quantum Computing\n\nRegistr
 ation Category: Tech Program Reg Pass, Exhibits Reg Pass\n\n
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