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UID:dac_DAC 2026_sess315_RESEARCH1113@linklings.com
SUMMARY:Achieving Intra- and Inter-Operator Communication Lower Bounds in 
 Near-Memory Processing
DESCRIPTION:Lei Xu, Chen Yin, Zelong Yuan, Weiguang Sheng, Jianfei Jiang, 
 Qin Wang, and Naifeng Jing (Shanghai Jiao Tong University)\n\nNear-memory 
 processing (NMP) is a promising way to overcome the memory wall in large l
 anguage models (LLMs). However, dataflow optimization in NMP is fundamenta
 lly constrained, as existing analyses cannot efficiently handle the new di
 stributed vault/channel organization. We propose the Remote-Access-Free (R
 AF) dataflow, which uses tensor rotation to abstract this distributed orga
 nization and eliminate all intra-operator remote access. On top of RAF, we
  apply analytical optimization to minimize intra-operator local access, th
 ereby achieving the intra-operator communication lower bound. We then intr
 oduce data partitioning that removes inter-operator remote access and enab
 le operator fusion to minimize inter-operator local access, so that the in
 ter-operator communication lower bound is also reached. Experimental resul
 ts show that RAF reduces energy by 50.4%, 39.0%, and 37.8%, and delivers s
 peedups of 3.98×, 1.72×, and 1.57× over IANUS, H^2LLM, and OptiPIM, respec
 tively.\n\nTopics: Quantum\n\nTrack: DES6. Quantum Computing, Systems\n\nS
 ession Chairs: Hokeun Kim (Arizona State University); BaekGyu Kim (Daegu G
 yeongbuk Institute of Science and Technology); Xiang Chen (Peking Universi
 ty); Sangyeob Kim (Yonsei University); Robert M. Radway (University of Pen
 nsylvania); Prashanth Mohan (University of Pittsburgh); Xiaoxuan Yang (Uni
 versity of Virginia, Stanford University); Ramtin Zand (University of Sout
 h Carolina); Hadi Kamali (University of Central Florida); Jiafeng Xie (Vil
 lanova University); Prabuddha Chakraborty (University of Maine); Junichiro
  Kadomoto (University of Tokyo); and Yosuke Ueno (RIKEN)\n\n
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