Emer, Joel S.

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

SASSIFI: An architecture-level fault injection tool for GPU application resilience evaluation

Hari, S. K. S., Tsai, T., Stephenson, M., Keckler, S. W., & Emer, J. (2017) · 2017 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)

Radiation Effects in ElectronicsParallel Computing and Optimization Techniques

Cited by 181

A 0.32–128 TOPS, Scalable Multi-Chip-Module-Based Deep Neural Network Inference Accelerator With Ground-Referenced Signaling in 16 nm

Zimmer, B., Venkatesan, R., Shao, Y. S., Clemons, J., Fojtik, M., Jiang, N., Keller, B., Klinefelter, A., Pinckney, N., Raina, P., et al. (2020) · IEEE Journal of Solid-State Circuits

Advanced Neural Network ApplicationsInterconnection Networks and Systems

Cited by 122

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