Showing results 13 to 16 of 16
PNPU: An Energy-Efficient Deep-Neural-Network Learning Processor with Stochastic Coarse-Fine Level Weight Pruning and Adaptive Input/Output/Weight Zero Skipping Kim, Sangyeob; Lee, Juhyoung; Kang, Sanghoon; Lee, Jinmook; Jo, Wooyoung; Yoo, Hoi-Jun, IEEE Solid-State Circuits Letters, v.4, pp.22 - 25, 2021 |
The Hardware and Algorithm Co-Design for Energy-Efficient DNN Processor on Edge/Mobile Devices Lee, Jinsu; Kang, Sanghoon; Lee, Jinmook; Shin, Dongjoo; Han, Donghyeon; Yoo, Hoi-Jun, IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, v.67, no.10, pp.3458 - 3470, 2020-10 |
TSUNAMI: Triple Sparsity-Aware Ultra Energy-Efficient Neural Network Training Accelerator With Multi-Modal Iterative Pruning Kim, Sangyeob; Lee, Juhyoung; Kang, Sanghoon; Han, Donghyeon; Jo, Wooyoung; Yoo, Hoi-Jun, IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, v.69, no.4, pp.1494 - 1506, 2022-04 |
UNPU: An Energy-Efficient Deep Neural Network Accelerator With Fully Variable Weight Bit Precision Lee, Jinmook; Kim, Changhyeon; Kang, Sanghoon; Shin, Dongjoo; Sangyeob Kim; Yoo, Hoi-Jun, IEEE JOURNAL OF SOLID-STATE CIRCUITS, v.54, no.1, pp.1 - 13, 2019-01 |
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