| Towards a holistic approach to auto-parallelization: integrating profile-driven parallelism detection and machine-learning based mapping Z Wang, G Tournavitis, B Franke, MFP O'Boyle ACM PLDI 2009 44 (6), 177-187, 2009 | 249* | 2009 |
| Mapping parallelism to multi-cores: a machine learning based approach Z Wang, MFP O'Boyle ACM PPoPP 2009 44 (4), 75-84, 2009 | 217 | 2009 |
| Portable Mapping of Data Parallel Programs to OpenCL for Heterogeneous Systems D Grewe, Z Wang, MFP O’Boyle ACM/IEEE Code Generation and Optimization (CGO) 2013, 2013 | 111* | 2013 |
| Partitioning streaming parallelism for multi-cores: a machine learning based approach Z Wang, MFP O'Boyle ACM/IEEE Proceedings of the 19th international conference on Parallel …, 2010 | 92 | 2010 |
| Smart multi-task scheduling for OpenCL programs on CPU/GPU heterogeneous platforms Y Wen, Z Wang, MFP O'boyle 2014 21st International Conference on High Performance Computing (HiPC), 1-10, 2014 | 79 | 2014 |
| 黄土丘陵沟壑区地形定量因子的关联性分析 张婷， 汤国安， 王春， 龙毅， 吴良超， 王峥 地理科学 25 (004), 467-472, 2005 | 62* | 2005 |
| OpenCL task partitioning in the presence of GPU contention D Grewe, Z Wang, MFP O’Boyle LCPC, 87-101, 2013 | 58 | 2013 |
| Smart, Adaptive Mapping of Parallelism in the Presence of External Workload MK Emani, Z Wang, MFP O'Boyle ACM/IEEE Code Generation and Optimization (CGO), 2013 | 57 | 2013 |
| End-to-end Deep Learning of Optimization Heuristics C Cummins, P Petoumenos, Z Wang, H Leather ACM/IEEE The 26th International Conference on Parallel Architectures and …, 2017 | 55 | 2017 |
| A workload-aware mapping approach for data-parallel programs D Grewe, Z Wang, MFP O'Boyle HiPEAC, 117-126, 2011 | 49 | 2011 |
| Integrating profile-driven parallelism detection and machine-learning-based mapping Z Wang, G Tournavitis, B Franke, MFP O'boyle ACM Transactions on Architecture and Code Optimization (TACO) 11 (1), 2, 2014 | 46 | 2014 |
| Cracking Android pattern lock in five attempts G Ye, Z Tang, D Fang, X Chen, KI Kim, B Taylor, Z Wang The Network and Distributed System Security Symposium (NDSS), 2017 | 45 | 2017 |
| Machine Learning in Compiler Optimisation Z Wang, M O'Boyle Proceedings of the IEEE, 2018 | 42 | 2018 |
| Automatic and Portable Mapping of Data Parallel Programs to OpenCL for GPU-Based Heterogeneous Systems Z Wang, D Grewe, MFP O’boyle ACM Transactions on Architecture and Code Optimization (TACO) 11 (4), 42, 2015 | 37 | 2015 |
| Adaptive optimization for OpenCL programs on embedded heterogeneous systems B Taylor, V Sanz Marco, Z Wang Proceedings of the 18th ACM SIGPLAN/SIGBED Conference on Languages …, 2017 | 36 | 2017 |
| Optimise web browsing on heterogeneous mobile platforms: a machine learning based approach J Ren, L Gao, H Wang, Z Wang INFOCOM 2017-IEEE Conference on Computer Communications, IEEE, 1-9, 2017 | 33 | 2017 |
| Minimizing the cost of iterative compilation with active learning WF Ogilvie, P Petoumenos, Z Wang, H Leather ACM/IEEE Proceedings of the 2017 International Symposium on Code Generation …, 2017 | 32 | 2017 |
| Using machine learning to partition streaming programs Z Wang, MFP O'boyle ACM Transactions on Architecture and Code Optimization (TACO) 10 (3), 20, 2013 | 32 | 2013 |
| Synthesizing benchmarks for predictive modeling C Cummins, P Petoumenos, Z Wang, H Leather 2017 IEEE/ACM International Symposium on Code Generation and Optimization …, 2017 | 30 | 2017 |
| Fast automatic heuristic construction using active learning WF Ogilvie, P Petoumenos, Z Wang, H Leather LCPC, 146-160, 2014 | 28 | 2014 |
Xiaojiang ChenNorthwest University, Xi'an, ChinaVerified email at nwu.edu.cn
