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Speculative Execution of Parallel Programs with Precise Exception Semantics on GPUs.

A. Hayashi, M. Grossman, J. Zhao, J. Shirako, and V. Sarkar. LCPC, volume 8664 of Lecture Notes in Computer Science, page 342-356. Springer, (2013)

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Max Schäfer University of Stuttgart

Dr. -Ing. Max Hoßfeld University of Stuttgart

Max Mustermann Universität Stuttgart

Max Dombrowski University of Stuttgart

Max Weinmann University of Stuttgart

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A Pluggable Framework for Composable HPC Scheduling Libraries.M. Grossman, V. Kumar, N. Vrvilo, Z. Budimlic, and V. Sarkar. IPDPS Workshops, page 723-732. IEEE Computer Society, (2017)S2FA: an accelerator automation framework for heterogeneous computing in datacenters.C. Yu, P. Wei, M. Grossman, P. Zhang, V. Sarkar, and J. Cong. DAC, page 153:1-153:6. ACM, (2018)Dynamic Task Parallelism with a GPU Work-Stealing Runtime System.S. Chatterjee, M. Grossman, A. Sbîrlea, and V. Sarkar. LCPC, volume 7146 of Lecture Notes in Computer Science, page 203-217. Springer, (2011)Speculative Execution of Parallel Programs with Precise Exception Semantics on GPUs.A. Hayashi, M. Grossman, J. Zhao, J. Shirako, and V. Sarkar. LCPC, volume 8664 of Lecture Notes in Computer Science, page 342-356. Springer, (2013)CnC-CUDA: Declarative Programming for GPUs.M. Grossman, A. Sbîrlea, Z. Budimlic, and V. Sarkar. LCPC, volume 6548 of Lecture Notes in Computer Science, page 230-245. Springer, (2010)Accelerating Habanero-Java programs with OpenCL generation.A. Hayashi, M. Grossman, J. Zhao, J. Shirako, and V. Sarkar. PPPJ, page 124-134. ACM, (2013)Auto-grading for parallel programs.M. Aziz, H. Chi, A. Tibrewal, M. Grossman, and V. Sarkar. EduHPC@SC, page 3:1-3:8. ACM, (2015)Efficient Checkpointing of Multi-threaded Applications as a Tool for Debugging, Performance Tuning, and Resiliency.M. Grossman, and V. Sarkar. IPDPS, page 232-241. IEEE Computer Society, (2016)A survey of sparse matrix-vector multiplication performance on large matrices.M. Grossman, C. Thiele, M. Araya-Polo, F. Frank, F. Alpak, and V. Sarkar. CoRR, (2016)Data-parallel distributed training of very large models beyond GPU capacity.S. Matzek, M. Grossman, M. Cho, A. Yusifov, B. Nelson, and A. Juneja. CoRR, (2018)