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Joseph Hassoun
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2020 – today
- 2024
- [j2]Runzhou Han
, Mai Zheng
PROV-IO$^+$+: A Cross-Platform Provenance Framework for Scientific Data on HPC Systems. IEEE Trans. Parallel Distributed Syst. 35(5): 844-861 (2024) - 2023
- [i8]Runzhou Han, Mai Zheng, Suren Byna, Houjun Tang, Bin Dong, Dong Dai, Yong Chen, Dongkyun Kim, Joseph Hassoun, David Thorsley, Matthew Wolf:
PROV-IO+: A Cross-Platform Provenance Framework for Scientific Data on HPC Systems. CoRR abs/2308.00891 (2023) - 2022
- [j1]Ardavan Pedram
Algorithm/architecture solutions to improve beyond uniform quantization in embedded DNN accelerators. J. Syst. Archit. 126: 102454 (2022) - [c9]Jong Hoon Shin, Ali Shafiee, Ardavan Pedram, Hamzah Abdel-Aziz, Ling Li, Joseph Hassoun:
Griffin: Rethinking Sparse Optimization for Deep Learning Architectures. HPCA 2022: 861-875 - [c8]Sehoon Kim, Sheng Shen, David Thorsley, Amir Gholami, Woosuk Kwon, Joseph Hassoun, Kurt Keutzer:
Learned Token Pruning for Transformers. KDD 2022: 784-794 - [c7]Woosuk Kwon, Sehoon Kim, Michael W. Mahoney, Joseph Hassoun, Kurt Keutzer, Amir Gholami:
A Fast Post-Training Pruning Framework for Transformers. NeurIPS 2022 - [i7]Woosuk Kwon, Sehoon Kim, Michael W. Mahoney, Joseph Hassoun, Kurt Keutzer, Amir Gholami:
A Fast Post-Training Pruning Framework for Transformers. CoRR abs/2204.09656 (2022) - [i6]Ling Li, Ali Shafiee Ardestani, Joseph Hassoun:
MaiT: Leverage Attention Masks for More Efficient Image Transformers. CoRR abs/2207.03006 (2022) - [i5]Ling Li, David Thorsley, Joseph Hassoun:
SaiT: Sparse Vision Transformers through Adaptive Token Pruning. CoRR abs/2210.05832 (2022) - 2021
- [c6]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, Dongwoo Lee
Sparsity-Aware and Re-configurable NPU Architecture for Samsung Flagship Mobile SoC. ISCA 2021: 15-28 - [c5]Hamzah Abdel-Aziz, Ali Shafiee, Jong Hoon Shin, Ardavan Pedram, Joseph Hassoun:
Rethinking Floating Point Overheads for Mixed Precision DNN Accelerators. MLSys 2021 - [i4]Hamzah Abdel-Aziz, Ali Shafiee, Jong Hoon Shin, Ardavan Pedram, Joseph H. Hassoun:
Rethinking Floating Point Overheads for Mixed Precision DNN Accelerators. CoRR abs/2101.11748 (2021) - [i3]Sehoon Kim, Sheng Shen, David Thorsley, Amir Gholami, Joseph Hassoun, Kurt Keutzer:
Learned Token Pruning for Transformers. CoRR abs/2107.00910 (2021) - [i2]Jong Hoon Shin, Ali Shafiee, Ardavan Pedram, Hamzah Abdel-Aziz, Ling Li, Joseph Hassoun:
Design Space Exploration of Sparse Accelerators for Deep Neural Networks. CoRR abs/2107.12922 (2021) - 2020
- [c4]Jun Fang, Ali Shafiee, Hamzah Abdel-Aziz, David Thorsley, Georgios Georgiadis, Joseph Hassoun:
Post-training Piecewise Linear Quantization for Deep Neural Networks. ECCV (2) 2020: 69-86 - [i1]Jun Fang, Ali Shafiee, Hamzah Abdel-Aziz, David Thorsley, Georgios Georgiadis, Joseph Hassoun:
Near-Lossless Post-Training Quantization of Deep Neural Networks via a Piecewise Linear Approximation. CoRR abs/2002.00104 (2020)
2000 – 2009
- 2009
- [c3]Joseph Hassoun:
Resiliency in Elemental Computing. ARC 2009: 2 - 2008
- [c2]John Watson, Steven H. Kelem, Brian Box, Joseph Hassoun, Stephen Wasson, Bob Plunkett, Chris Phillips:
A New Tact in Reconfigurable Computing Research. ERSA 2008: 76-78 - [c1]Joseph Hassoun, Steve Kelemjoseph, Brian Box, Stephen Wasson, Bob Plunkett, Chris Phillips:
Elemental Computing for High Reliability. ERSA 2008: 129-135
Coauthor Index
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