P4: Phase-based power/performance prediction of heterogeneous systems via neural networks

Author:

Kim Yeseong,Mercati Pietro,More Ankit,Shriver Emily,Rosing Tajana

Publisher

IEEE

Cited by 23 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. NetHD: Neurally Inspired Integration of Communication and Learning in Hyperspace;Advanced Intelligent Systems;2024-05-26

2. Work in Progress: Early Timing Prediction of Real-Time Tasks in Continuous Integration Environments;2024 IEEE 30th Real-Time and Embedded Technology and Applications Symposium (RTAS);2024-05-13

3. Predictive Modeling of Run Time for Model and Data Distributed Inferencing Using Gradient Boosting Regression;2023 IEEE International Conference on Big Data (BigData);2023-12-15

4. Predicting Software Performance with Divide-and-Learn;Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering;2023-11-30

5. NPU-Accelerated Imitation Learning for Thermal Optimization of QoS-Constrained Heterogeneous Multi-Cores;ACM Transactions on Design Automation of Electronic Systems;2023-11-15

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