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Efficient instruction scheduling using finite state automata.

, and . Int. J. Parallel Program., 25 (2): 53-82 (1997)

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Data Flow Computing and the Conjugate Gradient Method.. Architectures and Compilation Techniques for Fine and Medium Grain Parallelism, volume A-23 of IFIP Transactions, page 257-264. North-Holland, (1993)Enabling task-level scheduling on heterogeneous platforms., , , , and . GPGPU@ASPLOS, page 84-93. ACM, (2012)Analyzing program flow within a many-kernel OpenCL application., , , , and . GPGPU, page 10. ACM, (2011)Efficient instruction scheduling using finite state automata., and . Int. J. Parallel Program., 25 (2): 53-82 (1997)PRISM: predicting resilience of GPU applications using statistical methods., , , , and . SC, page 69:1-69:14. IEEE / ACM, (2018)ATI Stream Profiler: a tool to optimize an OpenCL kernel on ATI Radeon GPUs., , and . SIGGRAPH Posters, page 54:1. ACM, (2010)Griffin: Hardware-Software Support for Efficient Page Migration in Multi-GPU Systems., , , , , , , , , and . HPCA, page 596-609. IEEE, (2020)A Case for a Flexible Scalar Unit in SIMT Architecture., , , , , , and . IPDPS, page 93-102. IEEE Computer Society, (2014)A new method for GPU based irregular reductions and its application to k-means clustering., and . GPGPU, page 2. ACM, (2011)Efficient instruction scheduling using finite state automata., and . MICRO, page 46-56. ACM / IEEE Computer Society, (1995)