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Shihui Yin

2 accepted papers

2020

Efficient and Modularized Training on FPGA for Real-time Applications

IJCAI 2020poster

Training of deep Convolution Neural Networks (CNNs) requires a tremendous amount of computation and memory and thus, GPUs are widely used to meet the computation demands of these complex training tasks. However, lacking the flexibility to exploit architectural optimizations, GPUs have poor energy ef…

2019

Joint Optimization of Quantization and Structured Sparsity for Compressed Deep Neural Networks

ICASSP 2019accepted

The usage of Deep Neural Networks (DNN) on resource-constrained edge devices has been limited due to their high computation and large memory requirement. In this work, we propose an algorithm to compress DNNs by jointly optimizing structured sparsity and quantization constraints in a single DNN trai…

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