Chen, Yu-Hsin

Efficient Processing of Deep Neural Networks: A Tutorial and Survey

Sze, V., Chen, Y.-H., Yang, T.-J., & Emer, J. S. (2017) · Proceedings of the IEEE

Advanced Neural Network ApplicationsParallel Computing and Optimization Techniques

Cited by 4,215

Eyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks

Chen, Y.-H., Krishna, T., Emer, J. S., & Sze, V. (2017) · IEEE Journal of Solid-State Circuits

Advanced Neural Network ApplicationsParallel Computing and Optimization Techniques

Cited by 3,247

Eyeriss: a spatial architecture for energy-efficient dataflow for convolutional neural networks

Chen, Y.-H., Emer, J., & Sze, V. (2016) · ACM SIGARCH Computer Architecture News

Parallel Computing and Optimization TechniquesAdvanced Neural Network Applications

Cited by 1,182

Designing Energy-Efficient Convolutional Neural Networks Using Energy-Aware Pruning

Yang, T.-J., Chen, Y.-H., & Sze, V. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsGreen IT and Sustainability

Cited by 732

Heterogeneous Dataflow Accelerators for Multi-DNN Workloads

Kwon, H., Lai, L., Pellauer, M., Krishna, T., Chen, Y.-H., & Chandra, V. (2021) · 2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA)

Parallel Computing and Optimization TechniquesEmbedded Systems Design Techniques

Cited by 144

How to Evaluate Deep Neural Network Processors: TOPS/W (Alone) Considered Harmful

Sze, V., Chen, Y.-H., Yang, T.-J., & Emer, J. S. (2020) · IEEE Solid-State Circuits Magazine

Advanced Neural Network ApplicationsParallel Computing and Optimization Techniques

Cited by 80