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Leo: A Profile-Driven Dynamic Optimization Framework for GPU Applications.

, , , and . TRIOS, USENIX Association, (2014)

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HeteroCheckpoint: Efficient Checkpointing for Accelerator-Based Systems., , , and . DSN, page 738-743. IEEE Computer Society, (2014)Affinity-aware work-stealing for integrated CPU-GPU processors., , , , and . PPOPP, page 30:1-30:2. ACM, (2016)Leo: A Profile-Driven Dynamic Optimization Framework for GPU Applications., , , and . TRIOS, USENIX Association, (2014)GPUShare: Fair-Sharing Middleware for GPU Clouds., , , , , , and . IPDPS Workshops, page 1769-1776. IEEE Computer Society, (2016)Accelerating graph applications on integrated GPU platforms via instrumentation-driven optimizations., , , , and . Conf. Computing Frontiers, page 19-28. ACM, (2016)A framework for dynamically instrumenting GPU compute applications within GPU Ocelot., , , , and . GPGPU, page 9. ACM, (2011)A black-box approach to energy-aware scheduling on integrated CPU-GPU systems., , , , and . CGO, page 70-81. ACM, (2016)Slices: Provisioning Heterogeneous HPC Systems., , , , , and . XSEDE, page 46:1-46:8. ACM, (2014)Lynx: A dynamic instrumentation system for data-parallel applications on GPGPU architectures., , , , and . ISPASS, page 58-67. IEEE Computer Society, (2012)Accelerating Data Analytics on Integrated GPU Platforms via Runtime Specialization., , , , , , , and . International Journal of Parallel Programming, 46 (2): 336-375 (2018)