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1
(A) DNN accelerator architecture for the elimination of redundant computations and data = 불필요 연산 및 데이터 제거를 위한 심층 신경망 가속기 구조link

Park, Kangkyu; Kim, Lee-Sup; et al, 한국과학기술원, 2023

2
(A) redundancy-aware architecture to eliminate repeated computations in quantized convolutional neural networks = 양자화된 컨볼루셔널 신경망의 반복되는 연산을 제거하는 불필요한 연산 중복을 활용한 아키텍처link

Park, Kangkyu; Kim, Lee-Sup; et al, 한국과학기술원, 2019

3
Deferred Dropout: An Algorithm-Hardware Co-Design DNN Training Method Provisioning Consistent High Activation Sparsity

Park, Kangkyu; Han, Yunki; Kim, Lee-Sup, 40th IEEE/ACM International Conference on Computer Aided Design (ICCAD), IEEE/ACM, 2021-11

4
EGCN: An Efficient GCN Accelerator for Minimizing Off-Chip Memory Access

Han, Yunki; Park, Kangkyu; Jung, Youngbeom; Kim, Lee-Sup, IEEE TRANSACTIONS ON COMPUTERS, v.71, no.12, pp.3127 - 3139, 2022-12

5
Rare Computing: Removing Redundant Multiplications from Sparse and Repetitive Data in Deep Neural Networks

Park, Kangkyu; Choi, Seungkyu; Choi, Yeongjae; Kim, Lee-Sup, IEEE TRANSACTIONS ON COMPUTERS, v.71, no.4, pp.795 - 808, 2022-04

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