Elemental Computing for High Reliability. - Joseph Hassoun; Steve Kelemjoseph; Brian Box; Stephen Wasson; Bob Plunkett; Chris Phillips (ERSA, 2008)

A New Tact in Reconfigurable Computing Research. - John Watson; Steven H. Kelem; Brian Box; Joseph Hassoun; Stephen Wasson; Bob Plunkett; Chris Phillips (ERSA, 2008)

Resiliency in Elemental Computing. - Joseph Hassoun (ARC, 2009)

Post-training Piecewise Linear Quantization for Deep Neural Networks. - Jun Fang; Ali Shafiee; Hamzah Abdel-Aziz; David Thorsley; Georgios Georgiadis; Joseph Hassoun (ECCV (2), 2020)

Near-Lossless Post-Training Quantization of Deep Neural Networks via a Piecewise Linear Approximation. - Jun Fang; Ali Shafiee; Hamzah Abdel-Aziz; David Thorsley; Georgios Georgiadis; Joseph Hassoun (CoRR, 2020)

Sparsity-Aware and Re-configurable NPU Architecture for Samsung Flagship Mobile SoC. - Jun-Woo Jang; Sehwan Lee; Dongyoung Kim; Hyunsun Park; Ali Shafiee Ardestani; Yeongjae Choi; Channoh Kim; Yoojin Kim; Hyeongseok Yu; Hamzah Abdel-Aziz; Jun-Seok Park; Heonsoo Lee; et al. (ISCA, 2021)

Rethinking Floating Point Overheads for Mixed Precision DNN Accelerators. - Hamzah Abdel-Aziz; Ali Shafiee; Jong Hoon Shin; Ardavan Pedram; Joseph Hassoun (MLSys, 2021)

Learned Token Pruning for Transformers. - Sehoon Kim 001; Sheng Shen 001; David Thorsley; Amir Gholami; Joseph Hassoun; Kurt Keutzer (CoRR, 2021)

Design Space Exploration of Sparse Accelerators for Deep Neural Networks. - Jong Hoon Shin; Ali Shafiee; Ardavan Pedram; Hamzah Abdel-Aziz; Ling Li; Joseph Hassoun (CoRR, 2021)

Griffin: Rethinking Sparse Optimization for Deep Learning Architectures. - Jong Hoon Shin; Ali Shafiee; Ardavan Pedram; Hamzah Abdel-Aziz; Ling Li; Joseph Hassoun (HPCA, 2022)

Learned Token Pruning for Transformers. - Sehoon Kim 001; Sheng Shen 001; David Thorsley; Amir Gholami; Woosuk Kwon; Joseph Hassoun; Kurt Keutzer (KDD, 2022)

A Fast Post-Training Pruning Framework for Transformers. - Woosuk Kwon; Sehoon Kim 001; Michael W. Mahoney; Joseph Hassoun; Kurt Keutzer; Amir Gholami (NeurIPS, 2022)

MaiT: Leverage Attention Masks for More Efficient Image Transformers. - Ling Li; Ali Shafiee Ardestani; Joseph Hassoun (CoRR, 2022)

SaiT: Sparse Vision Transformers through Adaptive Token Pruning. - Ling Li; David Thorsley; Joseph Hassoun (CoRR, 2022)

Algorithm/architecture solutions to improve beyond uniform quantization in embedded DNN accelerators. - Ardavan Pedram; Ali Shafiee Ardestani; Ling Li; Hamzah Abdel-Aziz; Jun Fang; Joseph Hassoun (J. Syst. Archit., 2022)

PROV-IO+: A Cross-Platform Provenance Framework for Scientific Data on HPC Systems. - Runzhou Han; Mai Zheng; Suren Byna; Houjun Tang; Bin Dong 002; Dong Dai 001; Yong Chen 001; Dongkyun Kim; Joseph Hassoun; David Thorsley; Matthew Wolf (CoRR, 2023)

PROV-IO$^+$+: A Cross-Platform Provenance Framework for Scientific Data on HPC Systems. - Runzhou Han; Mai Zheng; Suren Byna; Houjun Tang; Bin Dong 002; Dong Dai 001; Yong Chen 001; Dongkyun Kim; Joseph Hassoun; David Thorsley (IEEE Trans. Parallel Distributed Syst., 2024)