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Software-level scheduling to exploit non-uniformly shared data cache on GPGPU.

, , and . MSPC@PLDI, page 10:1-10:2. ACM, (2013)

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Combining Locality Analysis with Online Proactive Job Co-scheduling in Chip Multiprocessors., , and . HiPEAC, volume 5952 of Lecture Notes in Computer Science, page 201-215. Springer, (2010)Exploration of the Influence of Program Inputs on CMP Co-scheduling., and . Euro-Par, volume 5168 of Lecture Notes in Computer Science, page 263-273. Springer, (2008)Optimizing Data Placement on GPU Memory: A Portable Approach., , , and . IEEE Trans. Computers, 66 (3): 473-487 (2017)Deep reuse: streamline CNN inference on the fly via coarse-grained computation reuse., and . ICS, page 438-448. ACM, (2019)Understanding co-run performance on CPU-GPU integrated processors: observations, insights, directions., , , , , and . Frontiers Comput. Sci., 11 (1): 130-146 (2017)Predicting locality phases for dynamic memory optimization., , and . J. Parallel Distributed Comput., 67 (7): 783-796 (2007)Supporting Legacy Libraries on Non-Volatile Memory: A User-Transparent Approach., , , , , and . ISCA, page 443-455. IEEE, (2021)Localization of concurrency bugs using shared memory access pairs., , , , , , , , and . ASE, page 611-622. ACM, (2014)Adaptive Data Partition for Sorting Using Probability Distribution., and . ICPP, page 250-257. IEEE Computer Society, (2004)Adaptive Software Speculation for Enhancing the Cost-Efficiency of Behavior-Oriented Parallelization., and . ICPP, page 270-278. IEEE Computer Society, (2008)