Bradley McDanel

According to our database, Bradley McDanel authored at least 24 papers between 2015 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

StitchNet: Composing Neural Networks from Pre-Trained Fragments.

Surat Teerapittayanon, Marcus Z. Comiter, Bradley McDanel, H. T. Kung

Proceedings of the International Conference on Machine Learning and Applications, 2023

Dynamic Patch Sampling for Efficient Training and Dynamic Inference in Vision Transformers.

Bradley McDanel, Chi Phuong Ngoc Huynh

Proceedings of the International Conference on Machine Learning and Applications, 2023

2022

Accelerating Vision Transformer Training via a Patch Sampling Schedule.

Bradley McDanel, Chi Phuong Huynh

CoRR, 2022

Accelerating DNN Training with Structured Data Gradient Pruning.

Bradley McDanel, Helia Dinh, John Magallanes

Proceedings of the 26th International Conference on Pattern Recognition, 2022

FAST: DNN Training Under Variable Precision Block Floating Point with Stochastic Rounding.

Sai Qian Zhang, Bradley McDanel, H. T. Kung

Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2022

2021

Saturation RRAM Leveraging Bit-Level Sparsity Resulting from Term Quantization.

Bradley McDanel, Sai Qian Zhang, H. T. Kung

Proceedings of the IEEE International Symposium on Circuits and Systems, 2021

Training for multi-resolution inference using reusable quantization terms.

Sai Qian Zhang, Bradley McDanel, H. T. Kung, Xin Dong

Proceedings of the ASPLOS '21: 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2021

2020

Term Revealing: Furthering Quantization at Run Time on Quantized DNNs.

H. T. Kung, Bradley McDanel, Sai Qian Zhang

CoRR, 2020

Term quantization: furthering quantization at run time.

Hsiang-Tsung Kung, Bradley McDanel, Sai Qian Zhang

Proceedings of the International Conference for High Performance Computing, 2020

2019

Full-stack Optimization for Accelerating CNNs with FPGA Validation.

Bradley McDanel, Sai Qian Zhang, H. T. Kung, Xin Dong

CoRR, 2019

Systolic Building Block for Logic-on-Logic 3D-IC Implementations of Convolutional Neural Networks.

H. T. Kung, Bradley McDanel, Sai Qian Zhang, C. T. Wang, Jin Cai, C. Y. Chen, Victor C. Y. Chang, M. F. Chen, Jack Yuan-Chen Sun, Douglas Yu

Proceedings of the IEEE International Symposium on Circuits and Systems, 2019

Full-stack optimization for accelerating CNNs using powers-of-two weights with FPGA validation.

Bradley McDanel, Sai Qian Zhang, H. T. Kung, Xin Dong

Proceedings of the ACM International Conference on Supercomputing, 2019

Packing Sparse Convolutional Neural Networks for Efficient Systolic Array Implementations: Column Combining Under Joint Optimization.

H. T. Kung, Bradley McDanel, Sai Qian Zhang

Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems, 2019

Maestro: A Memory-on-Logic Architecture for Coordinated Parallel Use of Many Systolic Arrays.

H. T. Kung, Bradley McDanel, Sai Qian Zhang, Xin Dong, Chih-Chiang Chen

Proceedings of the 30th IEEE International Conference on Application-specific Systems, 2019

2018

Mapping Systolic Arrays onto 3D Circuit Structures: Accelerating Convolutional Neural Network Inference.

H. T. Kung, Bradley McDanel, Sai Qian Zhang

Proceedings of the 2018 IEEE International Workshop on Signal Processing Systems, 2018

Adaptive Tiling: Applying Fixed-size Systolic Arrays To Sparse Convolutional Neural Networks.

H. T. Kung, Bradley McDanel, Sai Qian Zhang

Proceedings of the 24th International Conference on Pattern Recognition, 2018

2017

Incomplete Dot Products for Dynamic Computation Scaling in Neural Network Inference.

Bradley McDanel, Surat Teerapittayanon, H. T. Kung

Proceedings of the 16th IEEE International Conference on Machine Learning and Applications, 2017

Distributed Deep Neural Networks Over the Cloud, the Edge and End Devices.

Surat Teerapittayanon, Bradley McDanel, H. T. Kung

Proceedings of the 37th IEEE International Conference on Distributed Computing Systems, 2017

Embedded Binarized Neural Networks.

Bradley McDanel, Surat Teerapittayanon, H. T. Kung

Proceedings of the 2017 International Conference on Embedded Wireless Systems and Networks, 2017

2016

BranchyNet: Fast inference via early exiting from deep neural networks.

Surat Teerapittayanon, Bradley McDanel, H. T. Kung

Proceedings of the 23rd International Conference on Pattern Recognition, 2016

2015

Taming Wireless Fluctuations by Predictive Queuing Using a Sparse-Coding Link-State Model.

Stephen J. Tarsa, Marcus Z. Comiter, Michael B. Crouse, Bradley McDanel, H. T. Kung

Proceedings of the 16th ACM International Symposium on Mobile Ad Hoc Networking and Computing, 2015

PNNU: Parallel Nearest-Neighbor Units for Learned Dictionaries.

H. T. Kung, Bradley McDanel, Surat Teerapittayanon

Proceedings of the Languages and Compilers for Parallel Computing, 2015

Sparse Coding Trees with application to emotion classification.

Hsieh-Chung Chen, Marcus Z. Comiter, H. T. Kung, Bradley McDanel

Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2015

Outlier detection for large scale manufacturing processes.

Abhinav Jauhri, Bradley McDanel, Chris Connor

Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015