20 citations · 23 across the 4 of their papers we have counts for
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cs.AR2024
Panacea: Novel DNN Accelerator using Accuracy-Preserving Asymmetric Quantization and Energy-Saving Bit-Slice Sparsity
Dongyun Kam, Myeongji Yun, Sunwoo Yoo +3
Low bit-precisions and their bit-slice sparsity have recently been studied to accelerate general matrix-multiplications (GEMM) during large-scale deep neural network (DNN) inferenc…
cs.AR2022★ 1 cited
GROW: A Row-Stationary Sparse-Dense GEMM Accelerator for Memory-Efficient Graph Convolutional Neural Networks
Ranggi Hwang, Minhoo Kang, Jiwon Lee +3
Graph convolutional neural networks (GCNs) have emerged as a key technology in various application domains where the input data is relational. A unique property of GCNs is that its…
cs.AR2021★ 2 cited
Design and Evaluation Frameworks for Advanced RISC-based Ternary Processor
Dongyun Kam, Jung Gyu Min, Jongho Yoon +3
In this paper, we introduce the design and verification frameworks for developing a fully-functional emerging ternary processor. Based on the existing compiling environments for bi…