Beyond data and model parallelism for deep neural networks Z Jia, M Zaharia, A Aiken SysML 19, 2019 | 422 | 2019 |
TASO: Optimizing Deep Learning Computation with Automatic Generation of Graph Substitutions Z Jia, O Padon, J Thomas, T Warszawski, M Zaharia, A Aiken SOSP'19, 2019 | 219 | 2019 |
Improving the Accuracy, Scalability, and Performance of Graph Neural Networks with Roc Z Jia, S Lin, M Gao, M Zaharia, A Aiken MLSys'20, 2020 | 173 | 2020 |
Improving integer security for systems with {KINT} X Wang, H Chen, Z Jia, N Zeldovich, MF Kaashoek 10th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2012 | 155 | 2012 |
Undefined behavior: what happened to my code? X Wang, H Chen, A Cheung, Z Jia, N Zeldovich, MF Kaashoek Proceedings of the Asia-Pacific Workshop on Systems, 1-7, 2012 | 124 | 2012 |
Exploring hidden dimensions in parallelizing convolutional neural networks Z Jia, S Lin, CR Qi, A Aiken ICML 18, 2018 | 117 | 2018 |
Dorylus: Affordable, scalable, and accurate {GNN} training with distributed {CPU} servers and serverless threads J Thorpe, Y Qiao, J Eyolfson, S Teng, G Hu, Z Jia, J Wei, K Vora, ... 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2021 | 90 | 2021 |
Optimizing DNN Computation With Relaxed Graph Substitutions Z Jia, J Thomas, T Warszawski, M Gao, M Zaharia, A Aiken SysML 2019, 2019 | 78 | 2019 |
A distributed multi-gpu system for fast graph processing Z Jia, Y Kwon, G Shipman, P McCormick, M Erez, A Aiken Proceedings of the VLDB Endowment 11 (3), 297-310, 2017 | 78 | 2017 |
Redundancy-Free Computation for Graph Neural Networks Z Jia, S Lin, R Ying, J You, J Leskovec, A Aiken KDD'20, 2019 | 71 | 2019 |
Software-hardware co-design for fast and scalable training of deep learning recommendation models D Mudigere, Y Hao, J Huang, Z Jia, A Tulloch, S Sridharan, X Liu, ... Proceedings of the 49th Annual International Symposium on Computer …, 2022 | 58 | 2022 |
{SLIK}: Scalable {Low-Latency} Indexes for a {Key-Value} Store A Kejriwal, A Gopalan, A Gupta, Z Jia, S Yang, J Ousterhout 2016 USENIX Annual Technical Conference (USENIX ATC 16), 57-70, 2016 | 55 | 2016 |
Ios: Inter-operator scheduler for cnn acceleration Y Ding, L Zhu, Z Jia, G Pekhimenko, S Han Proceedings of Machine Learning and Systems 3, 167-180, 2021 | 45 | 2021 |
{PET}: Optimizing tensor programs with partially equivalent transformations and automated corrections H Wang, J Zhai, M Gao, Z Ma, S Tang, L Zheng, Y Li, K Rong, Y Chen, ... 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2021 | 43 | 2021 |
Exploring hidden dimensions in accelerating convolutional neural networks Z Jia, S Lin, CR Qi, A Aiken International Conference on Machine Learning, 2274-2283, 2018 | 42 | 2018 |
Unity: Accelerating {DNN} training through joint optimization of algebraic transformations and parallelization C Unger, Z Jia, W Wu, S Lin, M Baines, CEQ Narvaez, V Ramakrishnaiah, ... 16th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2022 | 40 | 2022 |
Bond: Benchmarking unsupervised outlier node detection on static attributed graphs K Liu, Y Dou, Y Zhao, X Ding, X Hu, R Zhang, K Ding, C Chen, H Peng, ... Advances in Neural Information Processing Systems 35, 27021-27035, 2022 | 35 | 2022 |
Quartz: superoptimization of quantum circuits M Xu, Z Li, O Padon, S Lin, J Pointing, A Hirth, H Ma, J Palsberg, A Aiken, ... Proceedings of the 43rd ACM SIGPLAN International Conference on Programming …, 2022 | 24 | 2022 |
Mahmoud khorashadi, Pallab Bhattacharya, Petr Lapukhov, Maxim Naumov, Ajit Mathews, Lin Qiao, Mikhail Smelyanskiy, Bill Jia, and Vijay Rao. 2021. Software-Hardware Co-design … D Mudigere, Y Hao, J Huang, Z Jia, A Tulloch, S Sridharan, X Liu, ... arXiv preprint arXiv:2104.05158, 2022 | 24 | 2022 |
Pygod: A python library for graph outlier detection K Liu, Y Dou, Y Zhao, X Ding, X Hu, R Zhang, K Ding, C Chen, H Peng, ... arXiv preprint arXiv:2204.12095, 2022 | 20 | 2022 |