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Safe limits on voltage reduction efficiency in GPUs: a direct measurement approach.

, , , , and . MICRO, page 294-307. ACM, (2015)

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Ivory: Early-Stage Design Space Exploration Tool for Integrated Voltage Regulators., , , , , , , and . DAC, page 1:1-1:6. ACM, (2017)Architectural Implications of Graph Neural Networks., , , , , and . IEEE Comput. Archit. Lett., 19 (1): 59-62 (2020)GMLake: Efficient and Transparent GPU Memory Defragmentation for Large-scale DNN Training with Virtual Memory Stitching., , , , , , , , , and 1 other author(s). CoRR, (2024)Block-Skim: Efficient Question Answering for Transformer., , , , , and . CoRR, (2021)CODA: Improving Resource Utilization by Slimming and Co-locating DNN and CPU Jobs., , , , , , , and . ICDCS, page 853-863. IEEE, (2020)Characterizing and Demystifying the Implicit Convolution Algorithm on Commercial Matrix-Multiplication Accelerators., , , , , , , and . IISWC, page 214-225. IEEE, (2021)Braum: Analyzing and Protecting Autonomous Machine Software Stack., , , , , and . ISSRE, page 85-96. IEEE, (2022)SALO: an efficient spatial accelerator enabling hybrid sparse attention mechanisms for long sequences., , , , , and . DAC, page 571-576. ACM, (2022)DistSim: A performance model of large-scale hybrid distributed DNN training., , , , , , , , , and 1 other author(s). CF, page 112-122. ACM, (2023)AdaptGear: Accelerating GNN Training via Adaptive Subgraph-Level Kernels on GPUs., , , , , , , , , and . CF, page 52-62. ACM, (2023)