Pengfei Xu

Affiliations:
  • Rice University, Houston, TX, USA


According to our database1, Pengfei Xu authored at least 12 papers between 2019 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

On csauthors.net:

Bibliography

2023
SmartDeal: Remodeling Deep Network Weights for Efficient Inference and Training.
IEEE Trans. Neural Networks Learn. Syst., October, 2023

2021
SmartDeal: Re-Modeling Deep Network Weights for Efficient Inference and Training.
CoRR, 2021

2020
Dual Dynamic Inference: Enabling More Efficient, Adaptive, and Controllable Deep Inference.
IEEE J. Sel. Top. Signal Process., 2020

Timely: Pushing Data Movements And Interfaces In Pim Accelerators Towards Local And In Time Domain.
Proceedings of the 47th ACM/IEEE Annual International Symposium on Computer Architecture, 2020

Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks.
Proceedings of the 8th International Conference on Learning Representations, 2020

DNN-Chip Predictor: An Analytical Performance Predictor for DNN Accelerators with Various Dataflows and Hardware Architectures.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

AutoDNNchip: An Automated DNN Chip Predictor and Builder for Both FPGAs and ASICs.
Proceedings of the FPGA '20: The 2020 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2020

Fractional Skipping: Towards Finer-Grained Dynamic CNN Inference.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
E2-Train: Energy-Efficient Deep Network Training with Data-, Model-, and Algorithm-Level Saving.
CoRR, 2019

Drawing early-bird tickets: Towards more efficient training of deep networks.
CoRR, 2019

E2-Train: Training State-of-the-art CNNs with Over 80% Energy Savings.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Live Demonstration: Bringing Powerful Deep Learning into Daily-Life Devices (Mobiles and FPGAs) Via Deep k-Means.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2019


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