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CORF: Bridging the Gap of Complex Operator Fusion for ...
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由 J Wang 著作2022 — CORF supports complex operator fusion by transforming the calculation strategy of complex operators and adopts a variety of optimization approaches to improve ...
CORF: Bridging the Gap of Complex Operator Fusion for ...
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由 J Wang 著作2022 — CORF supports complex operator fusion by transforming the calculation strategy of complex operators and adopts a variety of optimization approaches.
CORF: Bridging the Gap of Complex Operator Fusion for ...
IEEE Xplore
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由 J Wang 著作2022 — CORF supports complex operator fusion by transforming the calculation strategy of complex operators and adopts a variety of optimization approaches to improve ...
8 頁
Zhaoyun Chen
DBLP
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Yang Shi, Zhaoyun Chen, Mei Wen: ESEN: Efficient GPU sharing of Ensemble Neural Networks. ... CORF: Bridging the Gap of Complex Operator Fusion for Faster DNN ...
DNNFusion: accelerating deep neural networks execution ...
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A novel operator fusion framework that reduces 17–75% off-chip memory accesses and obtains 1.86×–3.66× energy efficiency on state-of-the-art DNN workloads.
Optimal weighted loop fusion for parallel programs
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ZWen M(2022)CORF: Bridging the Gap of Complex Operator Fusion for Faster DNN Inference2022 IEEE 24th Int Conf on High Performance Computing & Communications ...
a deep learning optimization framework for versatile GPU ...
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... DNN inference benchmark based on CUDA with diverse representative DNN workloads. ... CORF: Bridging the Gap of Complex Operator Fusion for Faster DNN Inference.
8th Int Conf on Dependability in Sensor, Cloud & Big Data ...
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CORF: Bridging the Gap of Complex Operator Fusion for Faster DNN Inference pp. 1014-1021. Optimizing Fast Trigonometric Functions on Modern CPUs pp. 1022 ...
Applying Graph Explanation to Operator Fusion
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2024年12月31日 — Layer fusion techniques are critical to improving the inference efficiency of deep neural networks (DNN) for deployment. Fusion aims to lower ...
缺少字詞： CORF: Bridging Gap
a deep learning optimization framework for versatile GPU ...
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由 W Jung 著作2021被引用 29 次 — In this paper, we propose a DL optimization framework for versatile GPU workloads, called DeepCuts. It considers both kernel implementation parameters and GPU ...