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TwinKernels: an execution model to improve GPU hardware scheduling at compile time.

, , , , and . CGO, page 39-49. ACM, (2017)

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Analyzing power efficiency of optimization techniques and algorithm design methods for applications on heterogeneous platforms., , , , and . Int. J. High Perform. Comput. Appl., 28 (3): 319-334 (2014)UMH: A Hardware-Based Unified Memory Hierarchy for Systems with Multiple Discrete GPUs., , , , , , , , and . TACO, 13 (4): 35:1-35:25 (2016)Leveraging Silicon-Photonic NoC for Designing Scalable GPUs., , , , , and . ICS, page 273-282. ACM, (2015)TwinKernels: an execution model to improve GPU hardware scheduling at compile time., , , , and . CGO, page 39-49. ACM, (2017)A comprehensive performance analysis of HSA and OpenCL 2.0., , , , and . ISPASS, page 183-193. IEEE Computer Society, (2016)REMAP: a reliability/endurance mechanism for advancing PCM., , , , , and . MEMSYS, page 385-398. ACM, (2017)Asymmetric NoC Architectures for GPU Systems., , , , and . NOCS, page 25:1-25:8. ACM, (2015)Live together or Die Alone: Block cooperation to extend lifetime of resistive memories., , and . DATE, page 1098-1103. IEEE, (2017)Hetero-mark, a benchmark suite for CPU-GPU collaborative computing., , , , , , , , and . IISWC, page 13-22. IEEE Computer Society, (2016)MGPUSim: enabling multi-GPU performance modeling and optimization., , , , , , , , , and 8 other author(s). ISCA, page 197-209. ACM, (2019)