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Deep reuse: streamline CNN inference on the fly via coarse-grained computation reuse., and . ICS, page 438-448. ACM, (2019)Optimizing Data Placement on GPU Memory: A Portable Approach., , , and . IEEE Trans. Computers, 66 (3): 473-487 (2017)Special Issue: Graph Computing., , , and . Concurr. Comput. Pract. Exp., (2020)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)CoCoPIE: Making Mobile AI Sweet As PIE -Compression-Compilation Co-Design Goes a Long Way., , , and . CoRR, (2020)TOP: A Framework for Enabling Algorithmic Optimizations for Distance-Related Problems., , , and . Proc. VLDB Endow., 8 (10): 1046-1057 (2015)Hyperparameter Optimization for Effort Estimation., , , , , and . CoRR, (2018)An Infrastructure for Tackling Input-Sensitivity of GPU Program Optimizations., , , and . Int. J. Parallel Program., 41 (6): 855-869 (2013)Predicting locality phases for dynamic memory optimization., , and . J. Parallel Distributed Comput., 67 (7): 783-796 (2007)