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Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation., , , и . ICLR, OpenReview.net, (2020)ReLeQ: A Reinforcement Learning Approach for Deep Quantization of Neural Networks., , , , и . CoRR, (2018)Mitigating the Memory Bottleneck With Approximate Load Value Prediction., , , , , и . IEEE Des. Test, 33 (1): 32-42 (2016)Neuro-general computing an acceleration-approximation approach.. Georgia Institute of Technology, Atlanta, GA, USA, (2018)base-search.net (ftgeorgiatech:oai:smartech.gatech.edu:1853/60224).Accelerating attention through gradient-based learned runtime pruning., , , , и . ISCA, стр. 902-915. ACM, (2022)Architecture 2.0: Challenges and Opportunities., и . DAC, стр. 1-2. IEEE, (2023)Energy-aware design space exploration of registerfile for extensible processors., , , , и . ICSAMOS, стр. 273-281. IEEE, (2010)AxMemo: hardware-compiler co-design for approximate code memoization., , , , и . ISCA, стр. 685-697. ACM, (2019)Towards the Co-design of Neural Networks and Accelerators., , , , , , , , , и . MLSys, mlsys.org, (2022)DACAPO: Accelerating Continuous Learning in Autonomous Systems for Video Analytics., , , , , , , , и . ISCA, стр. 1246-1261. IEEE, (2024)