논문 정리 Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation(ICLR 2020)

제목 Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation 저자 AmeByung Hoon Ahn, Prannoy Pilligundla, Amir Yazdanbakhsh, Hadi Esmaeilzadeh Motivation The current approaches are oblivious to the patterns in the design space of schedules that are available for exploitation, and causes inefficient search or even converges to solutions that may even be suboptimal….

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논문 정리 NeuroVectorizer: End-to-End Vectorization with Deep Reinforcement Learning (CGO 20)

제목 NeuroVectorizer: End-to-End Vectorization with Deep Reinforcement Learning 저자 Ameer Haj-Ali, Nesreen K. Ahmed, Ted Willke, Sophia Shao, Krste Asanovic, Ion Stoica Motivation Compilers are designed today to use fixed-cost models that are based on heuristics to make vectorization decisions on loops. However, these models are unable to capture the data dependency, the computation graph,…

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