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Valkyrie: Leveraging Inter-TLB Locality to Enhance GPU Performance., , , , , , , , and . PACT, page 455-466. ACM, (2020)MGSim + MGMark: A Framework for Multi-GPU System Research., , , , , , , , , and 3 other author(s). CoRR, (2018)GPU-accelerated charge mapping., , , and . HPEC, page 1-7. IEEE, (2016)GNNMark: A Benchmark Suite to Characterize Graph Neural Network Training on GPUs., , , , , , , , , and 1 other author(s). ISPASS, page 13-23. IEEE, (2021)MGPUSim: enabling multi-GPU performance modeling and optimization., , , , , , , , , and 8 other author(s). ISCA, page 197-209. ACM, (2019)Griffin: Hardware-Software Support for Efficient Page Migration in Multi-GPU Systems., , , , , , , , , and . HPCA, page 596-609. IEEE, (2020)True shared memory architecture for next-generation multi-GPU systems. Boston University, USA, (2021)Leveraging thermally-aware chiplet organization in 2.5D systems to reclaim dark silicon., , , , , and . DATE, page 1441-1446. IEEE, (2018)Profiling DNN Workloads on a Volta-based DGX-1 System., , , , , , , and . IISWC, page 122-133. IEEE Computer Society, (2018)