Algorithm Generation via Creative Ideation
Ruiying Ma, Chieh-Jan Mike Liang, Yanjie Gao, Francis Y. Yan
October 2025
Yanjie Gao
Senior Researcher
论文与出版物
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An Empirical Study of Issues in Large Language Model Training Systems
Yanjie Gao, Ruiming Lu, Haoxiang Lin, Yueguo Chen
FSE 2025 | June 2025
The ACM International Conference on the Foundations of Software Engineering, Industry Track
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dl²: Detecting Communication Deadlocks in Deep Learning Jobs
Yanjie Gao, Jiyu Luo, Haoxiang Lin, Hongyu Zhang, Ming Wu, Mao Yang
FSE 2025 | June 2025
The ACM International Conference on the Foundations of Software Engineering, Industry Track
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Reduction Fusion for Optimized Distributed Data-Parallel Computations via Inverse Recomputation
Haoxiang Lin, Yang Wang, Yanjie Gao, Hongyu Zhang, Ming Wu, Mao Yang
FSE 2025 | June 2025
The ACM International Conference on the Foundations of Software Engineering, Ideas, Visions and Reflections Track
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An Empirical Study on Low GPU Utilization of Deep Learning Jobs
Yanjie Gao, Yichen He, Xinze Li, Bo Zhao, Haoxiang Lin, Yoyo Liang, Jing Zhong, Hongyu Zhang, Jingzhou Wang, Yonghua Zeng, Keli Gui, Jie Tong, Mao Yang
ICSE 2024 | April 2024
The 46th International Conference on Software Engineering
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GPU Occupancy Prediction of Deep Learning Models Using Graph Neural Network
Hengquan Mei, Huaizhi Qu, Jingwei Sun, Yanjie Gao, Haoxiang Lin, Guangzhong Sun
CLUSTER 2023 | October 2023
The 25th IEEE International Conference on Cluster Computing
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An Empirical Study on Quality Issues of Deep Learning Platform
Yanjie Gao, Xiaoxiang Shi, Haoxiang Lin, Hongyu Zhang, Hao Wu, Rui Li, Mao Yang
ICSE 2023 | May 2023
The 45th International Conference on Software Engineering, Software Engineering in Practice (SEIP) Track
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Runtime Performance Prediction for Deep Learning Models with Graph Neural Network
Yanjie Gao, Xianyu Gu, Hongyu Zhang, Haoxiang Lin, Mao Yang
ICSE 2023 | May 2023
The 45th International Conference on Software Engineering, Software Engineering in Practice (SEIP) Track
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Refty: Refinement Types for Valid Deep Learning Models
Yanjie Gao, Zhengxian Li, Haoxiang Lin, Hongyu Zhang, Ming Wu, Mao Yang
ICSE 2022 | May 2022
The 44th International Conference on Software Engineering
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Resource-Guided Configuration Space Reduction for Deep Learning Models
Yanjie Gao, Yonghao Zhu, Hongyu Zhang, Haoxiang Lin, Mao Yang
ICSE 2021 | May 2021
The 43rd International Conference on Software Engineering
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Runtime Performance Prediction for Deep Learning Models with Graph Neural Network (Tech Report)
Yanjie Gao, Xianyu Gu, Hongyu Zhang, Haoxiang Lin, Mao Yang
MSR-TR-2021-3 | February 2021
作者：Microsoft
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Estimating GPU Memory Consumption of Deep Learning Models
Yanjie Gao, Yu Liu, Hongyu Zhang, Zhengxian Li, Yonghao Zhu, Haoxiang Lin, Mao Yang
ESEC/FSE 2020 | November 2020
The 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, Industry Track
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Estimating GPU Memory Consumption of Deep Learning Models
Yanjie Gao, Yu Liu, Hongyu Zhang, Zhengxian Li, Yonghao Zhu, Haoxiang Lin, Mao Yang
MSR-TR-2020-20 | May 2020
作者：Microsoft
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TR-Spark: Transient Computing for Big Data Analytics
Ying Yan, Yanjie Gao, Yang Chen, Zhongxin Guo, Bole Chen, Thomas Moscibroda
SoCC '16 Proceedings of the Seventh ACM Symposium on Cloud Computing | October 2016
ISBN: 978-1-4503-4525-5
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Algorithm Generation via Creative Ideation
Ruiying Ma, Chieh-Jan Mike Liang, Yanjie Gao, Francis Y. Yan
October 2025
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An Empirical Study of Issues in Large Language Model Training Systems
Yanjie Gao, Ruiming Lu, Haoxiang Lin, Yueguo Chen
FSE 2025 | June 2025
The ACM International Conference on the Foundations of Software Engineering, Industry Track
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Reduction Fusion for Optimized Distributed Data-Parallel Computations via Inverse Recomputation
Haoxiang Lin, Yang Wang, Yanjie Gao, Hongyu Zhang, Ming Wu, Mao Yang
FSE 2025 | June 2025
The ACM International Conference on the Foundations of Software Engineering, Ideas, Visions and Reflections Track
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dl²: Detecting Communication Deadlocks in Deep Learning Jobs
Yanjie Gao, Jiyu Luo, Haoxiang Lin, Hongyu Zhang, Ming Wu, Mao Yang
FSE 2025 | June 2025
The ACM International Conference on the Foundations of Software Engineering, Industry Track
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An Empirical Study on Low GPU Utilization of Deep Learning Jobs
Yanjie Gao, Yichen He, Xinze Li, Bo Zhao, Haoxiang Lin, Yoyo Liang, Jing Zhong, Hongyu Zhang, Jingzhou Wang, Yonghua Zeng, Keli Gui, Jie Tong, Mao Yang
ICSE 2024 | April 2024
The 46th International Conference on Software Engineering
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GPU Occupancy Prediction of Deep Learning Models Using Graph Neural Network
Hengquan Mei, Huaizhi Qu, Jingwei Sun, Yanjie Gao, Haoxiang Lin, Guangzhong Sun
CLUSTER 2023 | October 2023
The 25th IEEE International Conference on Cluster Computing
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Runtime Performance Prediction for Deep Learning Models with Graph Neural Network
Yanjie Gao, Xianyu Gu, Hongyu Zhang, Haoxiang Lin, Mao Yang
ICSE 2023 | May 2023
The 45th International Conference on Software Engineering, Software Engineering in Practice (SEIP) Track
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An Empirical Study on Quality Issues of Deep Learning Platform
Yanjie Gao, Xiaoxiang Shi, Haoxiang Lin, Hongyu Zhang, Hao Wu, Rui Li, Mao Yang
ICSE 2023 | May 2023
The 45th International Conference on Software Engineering, Software Engineering in Practice (SEIP) Track
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Refty: Refinement Types for Valid Deep Learning Models
Yanjie Gao, Zhengxian Li, Haoxiang Lin, Hongyu Zhang, Ming Wu, Mao Yang
ICSE 2022 | May 2022
The 44th International Conference on Software Engineering
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Resource-Guided Configuration Space Reduction for Deep Learning Models
Yanjie Gao, Yonghao Zhu, Hongyu Zhang, Haoxiang Lin, Mao Yang
ICSE 2021 | May 2021
The 43rd International Conference on Software Engineering
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Runtime Performance Prediction for Deep Learning Models with Graph Neural Network (Tech Report)
Yanjie Gao, Xianyu Gu, Hongyu Zhang, Haoxiang Lin, Mao Yang
MSR-TR-2021-3 | February 2021
作者：Microsoft
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Estimating GPU Memory Consumption of Deep Learning Models
Yanjie Gao, Yu Liu, Hongyu Zhang, Zhengxian Li, Yonghao Zhu, Haoxiang Lin, Mao Yang
ESEC/FSE 2020 | November 2020
The 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, Industry Track
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Estimating GPU Memory Consumption of Deep Learning Models
Yanjie Gao, Yu Liu, Hongyu Zhang, Zhengxian Li, Yonghao Zhu, Haoxiang Lin, Mao Yang
MSR-TR-2020-20 | May 2020
作者：Microsoft
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Algorithm Generation via Creative Ideation
Ruiying Ma, Chieh-Jan Mike Liang, Yanjie Gao, Francis Y. Yan
October 2025
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An Empirical Study of Issues in Large Language Model Training Systems
Yanjie Gao, Ruiming Lu, Haoxiang Lin, Yueguo Chen
FSE 2025 | June 2025
The ACM International Conference on the Foundations of Software Engineering, Industry Track
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Reduction Fusion for Optimized Distributed Data-Parallel Computations via Inverse Recomputation
Haoxiang Lin, Yang Wang, Yanjie Gao, Hongyu Zhang, Ming Wu, Mao Yang
FSE 2025 | June 2025
The ACM International Conference on the Foundations of Software Engineering, Ideas, Visions and Reflections Track
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dl²: Detecting Communication Deadlocks in Deep Learning Jobs
Yanjie Gao, Jiyu Luo, Haoxiang Lin, Hongyu Zhang, Ming Wu, Mao Yang
FSE 2025 | June 2025
The ACM International Conference on the Foundations of Software Engineering, Industry Track
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An Empirical Study on Low GPU Utilization of Deep Learning Jobs
Yanjie Gao, Yichen He, Xinze Li, Bo Zhao, Haoxiang Lin, Yoyo Liang, Jing Zhong, Hongyu Zhang, Jingzhou Wang, Yonghua Zeng, Keli Gui, Jie Tong, Mao Yang
ICSE 2024 | April 2024
The 46th International Conference on Software Engineering
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GPU Occupancy Prediction of Deep Learning Models Using Graph Neural Network
Hengquan Mei, Huaizhi Qu, Jingwei Sun, Yanjie Gao, Haoxiang Lin, Guangzhong Sun
CLUSTER 2023 | October 2023
The 25th IEEE International Conference on Cluster Computing
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Runtime Performance Prediction for Deep Learning Models with Graph Neural Network
Yanjie Gao, Xianyu Gu, Hongyu Zhang, Haoxiang Lin, Mao Yang
ICSE 2023 | May 2023
The 45th International Conference on Software Engineering, Software Engineering in Practice (SEIP) Track
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An Empirical Study on Quality Issues of Deep Learning Platform
Yanjie Gao, Xiaoxiang Shi, Haoxiang Lin, Hongyu Zhang, Hao Wu, Rui Li, Mao Yang
ICSE 2023 | May 2023
The 45th International Conference on Software Engineering, Software Engineering in Practice (SEIP) Track
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Refty: Refinement Types for Valid Deep Learning Models
Yanjie Gao, Zhengxian Li, Haoxiang Lin, Hongyu Zhang, Ming Wu, Mao Yang
ICSE 2022 | May 2022
The 44th International Conference on Software Engineering
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Resource-Guided Configuration Space Reduction for Deep Learning Models
Yanjie Gao, Yonghao Zhu, Hongyu Zhang, Haoxiang Lin, Mao Yang
ICSE 2021 | May 2021
The 43rd International Conference on Software Engineering
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Runtime Performance Prediction for Deep Learning Models with Graph Neural Network (Tech Report)
Yanjie Gao, Xianyu Gu, Hongyu Zhang, Haoxiang Lin, Mao Yang
MSR-TR-2021-3 | February 2021
作者：Microsoft
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Estimating GPU Memory Consumption of Deep Learning Models
Yanjie Gao, Yu Liu, Hongyu Zhang, Zhengxian Li, Yonghao Zhu, Haoxiang Lin, Mao Yang
ESEC/FSE 2020 | November 2020
The 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, Industry Track
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Estimating GPU Memory Consumption of Deep Learning Models
Yanjie Gao, Yu Liu, Hongyu Zhang, Zhengxian Li, Yonghao Zhu, Haoxiang Lin, Mao Yang
MSR-TR-2020-20 | May 2020
作者：Microsoft
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TR-Spark: Transient Computing for Big Data Analytics
Ying Yan, Yanjie Gao, Yang Chen, Zhongxin Guo, Bole Chen, Thomas Moscibroda
SoCC '16 Proceedings of the Seventh ACM Symposium on Cloud Computing | October 2016
ISBN: 978-1-4503-4525-5
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An Empirical Study of Issues in Large Language Model Training Systems
Yanjie Gao, Ruiming Lu, Haoxiang Lin, Yueguo Chen
FSE 2025 | June 2025
The ACM International Conference on the Foundations of Software Engineering, Industry Track
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Reduction Fusion for Optimized Distributed Data-Parallel Computations via Inverse Recomputation
Haoxiang Lin, Yang Wang, Yanjie Gao, Hongyu Zhang, Ming Wu, Mao Yang
FSE 2025 | June 2025
The ACM International Conference on the Foundations of Software Engineering, Ideas, Visions and Reflections Track
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dl²: Detecting Communication Deadlocks in Deep Learning Jobs
Yanjie Gao, Jiyu Luo, Haoxiang Lin, Hongyu Zhang, Ming Wu, Mao Yang
FSE 2025 | June 2025
The ACM International Conference on the Foundations of Software Engineering, Industry Track
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An Empirical Study on Low GPU Utilization of Deep Learning Jobs
Yanjie Gao, Yichen He, Xinze Li, Bo Zhao, Haoxiang Lin, Yoyo Liang, Jing Zhong, Hongyu Zhang, Jingzhou Wang, Yonghua Zeng, Keli Gui, Jie Tong, Mao Yang
ICSE 2024 | April 2024
The 46th International Conference on Software Engineering
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Runtime Performance Prediction for Deep Learning Models with Graph Neural Network
Yanjie Gao, Xianyu Gu, Hongyu Zhang, Haoxiang Lin, Mao Yang
ICSE 2023 | May 2023
The 45th International Conference on Software Engineering, Software Engineering in Practice (SEIP) Track
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An Empirical Study on Quality Issues of Deep Learning Platform
Yanjie Gao, Xiaoxiang Shi, Haoxiang Lin, Hongyu Zhang, Hao Wu, Rui Li, Mao Yang
ICSE 2023 | May 2023
The 45th International Conference on Software Engineering, Software Engineering in Practice (SEIP) Track
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Refty: Refinement Types for Valid Deep Learning Models
Yanjie Gao, Zhengxian Li, Haoxiang Lin, Hongyu Zhang, Ming Wu, Mao Yang
ICSE 2022 | May 2022
The 44th International Conference on Software Engineering
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Resource-Guided Configuration Space Reduction for Deep Learning Models
Yanjie Gao, Yonghao Zhu, Hongyu Zhang, Haoxiang Lin, Mao Yang
ICSE 2021 | May 2021
The 43rd International Conference on Software Engineering
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Runtime Performance Prediction for Deep Learning Models with Graph Neural Network (Tech Report)
Yanjie Gao, Xianyu Gu, Hongyu Zhang, Haoxiang Lin, Mao Yang
MSR-TR-2021-3 | February 2021
作者：Microsoft
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Estimating GPU Memory Consumption of Deep Learning Models
Yanjie Gao, Yu Liu, Hongyu Zhang, Zhengxian Li, Yonghao Zhu, Haoxiang Lin, Mao Yang
ESEC/FSE 2020 | November 2020
The 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, Industry Track
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Estimating GPU Memory Consumption of Deep Learning Models
Yanjie Gao, Yu Liu, Hongyu Zhang, Zhengxian Li, Yonghao Zhu, Haoxiang Lin, Mao Yang
MSR-TR-2020-20 | May 2020
作者：Microsoft
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Algorithm Generation via Creative Ideation
Ruiying Ma, Chieh-Jan Mike Liang, Yanjie Gao, Francis Y. Yan
October 2025
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An Empirical Study of Issues in Large Language Model Training Systems
Yanjie Gao, Ruiming Lu, Haoxiang Lin, Yueguo Chen
FSE 2025 | June 2025
The ACM International Conference on the Foundations of Software Engineering, Industry Track
-
Reduction Fusion for Optimized Distributed Data-Parallel Computations via Inverse Recomputation
Haoxiang Lin, Yang Wang, Yanjie Gao, Hongyu Zhang, Ming Wu, Mao Yang
FSE 2025 | June 2025
The ACM International Conference on the Foundations of Software Engineering, Ideas, Visions and Reflections Track
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dl²: Detecting Communication Deadlocks in Deep Learning Jobs
Yanjie Gao, Jiyu Luo, Haoxiang Lin, Hongyu Zhang, Ming Wu, Mao Yang
FSE 2025 | June 2025
The ACM International Conference on the Foundations of Software Engineering, Industry Track
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An Empirical Study on Low GPU Utilization of Deep Learning Jobs
Yanjie Gao, Yichen He, Xinze Li, Bo Zhao, Haoxiang Lin, Yoyo Liang, Jing Zhong, Hongyu Zhang, Jingzhou Wang, Yonghua Zeng, Keli Gui, Jie Tong, Mao Yang
ICSE 2024 | April 2024
The 46th International Conference on Software Engineering
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GPU Occupancy Prediction of Deep Learning Models Using Graph Neural Network
Hengquan Mei, Huaizhi Qu, Jingwei Sun, Yanjie Gao, Haoxiang Lin, Guangzhong Sun
CLUSTER 2023 | October 2023
The 25th IEEE International Conference on Cluster Computing
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Runtime Performance Prediction for Deep Learning Models with Graph Neural Network
Yanjie Gao, Xianyu Gu, Hongyu Zhang, Haoxiang Lin, Mao Yang
ICSE 2023 | May 2023
The 45th International Conference on Software Engineering, Software Engineering in Practice (SEIP) Track
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An Empirical Study on Quality Issues of Deep Learning Platform
Yanjie Gao, Xiaoxiang Shi, Haoxiang Lin, Hongyu Zhang, Hao Wu, Rui Li, Mao Yang
ICSE 2023 | May 2023
The 45th International Conference on Software Engineering, Software Engineering in Practice (SEIP) Track
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Refty: Refinement Types for Valid Deep Learning Models
Yanjie Gao, Zhengxian Li, Haoxiang Lin, Hongyu Zhang, Ming Wu, Mao Yang
ICSE 2022 | May 2022
The 44th International Conference on Software Engineering
-
Resource-Guided Configuration Space Reduction for Deep Learning Models
Yanjie Gao, Yonghao Zhu, Hongyu Zhang, Haoxiang Lin, Mao Yang
ICSE 2021 | May 2021
The 43rd International Conference on Software Engineering
-
Estimating GPU Memory Consumption of Deep Learning Models
Yanjie Gao, Yu Liu, Hongyu Zhang, Zhengxian Li, Yonghao Zhu, Haoxiang Lin, Mao Yang
ESEC/FSE 2020 | November 2020
The 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, Industry Track
-
TR-Spark: Transient Computing for Big Data Analytics
Ying Yan, Yanjie Gao, Yang Chen, Zhongxin Guo, Bole Chen, Thomas Moscibroda
SoCC '16 Proceedings of the Seventh ACM Symposium on Cloud Computing | October 2016
ISBN: 978-1-4503-4525-5
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-
-
Runtime Performance Prediction for Deep Learning Models with Graph Neural Network (Tech Report)
Yanjie Gao, Xianyu Gu, Hongyu Zhang, Haoxiang Lin, Mao Yang
MSR-TR-2021-3 | February 2021
作者：Microsoft
-
Estimating GPU Memory Consumption of Deep Learning Models
Yanjie Gao, Yu Liu, Hongyu Zhang, Zhengxian Li, Yonghao Zhu, Haoxiang Lin, Mao Yang
MSR-TR-2020-20 | May 2020
作者：Microsoft
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