Beyond data and model parallelism for deep neural networks Z Jia, M Zaharia, A Aiken SysML 19, 2019 | 152 | 2019 |

Beyond data and model parallelism for deep neural networks Z Jia, M Zaharia, A Aiken SysML 19, 2019 | 151 | 2019 |

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 …, 2012 | 123 | 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 | 93 | 2012 |

Exploring hidden dimensions in parallelizing convolutional neural networks Z Jia, S Lin, CR Qi, A Aiken ICML 18, 2018 | 53 | 2018 |

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 | 46 | 2017 |

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 | 45 | 2019 |

{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 | 39 | 2016 |

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 | 26 | 2020 |

Optimizing DNN Computation With Relaxed Graph Substitutions Z Jia, J Thomas, T Warszawski, M Gao, M Zaharia, A Aiken SysML 2019, 2019 | 25 | 2019 |

Exploring hidden dimensions in accelerating convolutional neural networks Z Jia, S Lin, CR Qi, A Aiken International Conference on Machine Learning, 2274-2283, 2018 | 16 | 2018 |

Automatic and transparent I/O optimization with storage integrated application runtime support N Watkins, Z Jia, G Shipman, C Maltzahn, A Aiken, P McCormick Proceedings of the 10th Parallel Data Storage Workshop, 49-54, 2015 | 8 | 2015 |

Redundancy-Free Computation for Graph Neural Networks Z Jia, S Lin, R Ying, J You, J Leskovec, A Aiken KDD'20, 2019 | 7* | 2019 |

Integrating External Resources with a Task-Based Programming Model Z Jia, S Treichler, G Shipman, M Bauer, N Watkins, C Maltzahn, ... 2017 IEEE 24th International Conference on High Performance Computing (HiPC …, 2017 | 4 | 2017 |

Dorylus: Affordable, Scalable, and Accurate GNN Training over Billion-Edge Graphs J Thorpe, Y Qiao, J Eyolfson, S Teng, G Hu, Z Jia, J Wei, K Vora, ... arXiv preprint arXiv:2105.11118, 2021 | 1 | 2021 |

Ios: Inter-operator scheduler for cnn acceleration Y Ding, L Zhu, Z Jia, G Pekhimenko, S Han Proceedings of Machine Learning and Systems 3, 2021 | 1 | 2021 |

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, ... arXiv e-prints, arXiv: 2105.11118, 2021 | | 2021 |

Scaling Implicit Parallelism via Dynamic Control Replication M Bauer, W Lee, E Slaughter, Z Jia, M Di Renzo, M Papadakis, ... PPoPP, 2021 | | 2021 |

Automated Discovery of Machine Learning Optimizations Z Jia PQDT-Global, 2020 | | 2020 |

Accelerate DNN Inference By Inter-Operator Parallelization Y Ding, L Zhu, Z Jia, S Han | | 2019 |