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Deep NLP-based co-evolvement for synthesizing code analysis from natural language.

, , , and . CC, page 141-152. ACM, (2021)

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Hyperparameter Optimization for Effort Estimation., , , , , and . CoRR, (2018)Deep reuse: streamline CNN inference on the fly via coarse-grained computation reuse., and . ICS, page 438-448. ACM, (2019)Special Issue: Graph Computing., , , and . Concurr. Comput. Pract. Exp., (2020)Optimizing Data Placement on GPU Memory: A Portable Approach., , , and . IEEE Trans. Computers, 66 (3): 473-487 (2017)Understanding co-run performance on CPU-GPU integrated processors: observations, insights, directions., , , , , and . Frontiers Comput. Sci., 11 (1): 130-146 (2017)GLORE: generalized loop redundancy elimination upon LER-notation., and . Proc. ACM Program. Lang., 1 (OOPSLA): 74:1-74:28 (2017)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)Expanding the Edge: Enabling Efficient Winograd CNN Inference With Deep Reuse on Edge Device., , , , , , , and . IEEE Trans. Knowl. Data Eng., 35 (10): 10181-10196 (October 2023)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)