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2020 – today
- 2025
[i11]Ahmed F. AbouElhamayed, Jordan Dotzel, Yash Akhauri, Chi-Chih Chang, Sameh Gobriel, J. Pablo Muñoz, Vui Seng Chua, Nilesh Jain, Mohamed S. Abdelfattah:
SparAMX: Accelerating Compressed LLMs Token Generation on AMX-powered CPUs. CoRR abs/2502.12444 (2025)- 2024
- [c8]Jordan Dotzel, Gang Wu, Andrew Li, Muhammad Umar, Yun Ni, Mohamed S. Abdelfattah, Zhiru Zhang, Liqun Cheng, Martin G. Dixon, Norman P. Jouppi, Quoc V. Le, Sheng Li:
FLIQS: One-Shot Mixed-Precision Floating-Point and Integer Quantization Search. AutoML 2024: 6/1-26 - [c7]Yash Akhauri, Ahmed F. AbouElhamayed, Jordan Dotzel, Zhiru Zhang, Alexander M. Rush, Safeen Huda, Mohamed S. Abdelfattah:
ShadowLLM: Predictor-based Contextual Sparsity for Large Language Models. EMNLP 2024: 19154-19167 - [c6]Jordan Dotzel, Bahaa Kotb, James Dotzel, Mohamed S. Abdelfattah, Zhiru Zhang:
Exploring the Limits of Semantic Image Compression at Micro-bits per Pixel. Tiny Papers @ ICLR 2024 - [c5]Jordan Dotzel, Yuzong Chen, Bahaa Kotb, Sushma Prasad, Gang Wu, Sheng Li, Mohamed S. Abdelfattah, Zhiru Zhang:
Learning from Students: Applying t-Distributions to Explore Accurate and Efficient Formats for LLMs. ICML 2024 - [i10]Jordan Dotzel, Bahaa Kotb, James Dotzel, Mohamed S. Abdelfattah, Zhiru Zhang:
Exploring the Limits of Semantic Image Compression at Micro-bits per Pixel. CoRR abs/2402.13536 (2024) - [i9]Jordan Dotzel, Yash Akhauri, Ahmed S. AbouElhamayed, Carly Jiang, Mohamed S. Abdelfattah, Zhiru Zhang:
Radial Networks: Dynamic Layer Routing for High-Performance Large Language Models. CoRR abs/2404.04900 (2024) - [i8]Jordan Dotzel, Yuzong Chen, Bahaa Kotb, Sushma Prasad, Gang Wu, Sheng Li, Mohamed S. Abdelfattah, Zhiru Zhang:
Learning from Students: Applying t-Distributions to Explore Accurate and Efficient Formats for LLMs. CoRR abs/2405.03103 (2024) - [i7]Yash Akhauri, Ahmed F. AbouElhamayed, Jordan Dotzel, Zhiru Zhang, Alexander M. Rush, Safeen Huda, Mohamed S. Abdelfattah:
ShadowLLM: Predictor-based Contextual Sparsity for Large Language Models. CoRR abs/2406.16635 (2024) - 2023
- [c4]Yuzong Chen, Jordan Dotzel, Mohamed S. Abdelfattah:
M4BRAM: Mixed-Precision Matrix-Matrix Multiplication in FPGA Block RAMs. ICFPT 2023: 69-78 - [i6]Jordan Dotzel, Gang Wu, Andrew Li, Muhammad Umar
, Yun Ni, Mohamed S. Abdelfattah, Zhiru Zhang, Liqun Cheng, Martin G. Dixon, Norman P. Jouppi, Quoc V. Le, Sheng Li:
FLIQS: One-Shot Mixed-Precision Floating-Point and Integer Quantization Search. CoRR abs/2308.03290 (2023) - [i5]Yuzong Chen, Jordan Dotzel, Mohamed S. Abdelfattah:
M4BRAM: Mixed-Precision Matrix-Matrix Multiplication in FPGA Block RAMs. CoRR abs/2311.02758 (2023) - 2021
- [j1]Cong Hao, Jordan Dotzel, Jinjun Xiong, Luca Benini, Zhiru Zhang, Deming Chen:
Enabling Design Methodologies and Future Trends for Edge AI: Specialization and Codesign. IEEE Des. Test 38(4): 7-26 (2021) - [c3]Shubham Rai, Walter Lau Neto, Yukio Miyasaka, Xinpei Zhang, Mingfei Yu, Qingyang Yi, Masahiro Fujita, Guilherme B. Manske, Matheus F. Pontes, Leomar S. da Rosa, Marilton S. de Aguiar, Paulo F. Butzen, Po-Chun Chien, Yu-Shan Huang, Hoa-Ren Wang, Jie-Hong R. Jiang, Jiaqi Gu, Zheng Zhao, Zixuan Jiang, David Z. Pan, Brunno A. Abreu, Isac de Souza Campos, Augusto Andre Souza Berndt, Cristina Meinhardt, Jônata Tyska Carvalho, Mateus Grellert, Sergio Bampi, Aditya Lohana, Akash Kumar, Wei Zeng, Azadeh Davoodi, Rasit Onur Topaloglu, Yuan Zhou, Jordan Dotzel, Yichi Zhang, Hanyu Wang, Zhiru Zhang, Valerio Tenace, Pierre-Emmanuel Gaillardon, Alan Mishchenko, Satrajit Chatterjee:
Logic Synthesis Meets Machine Learning: Trading Exactness for Generalization. DATE 2021: 1026-1031 - [i4]Cong Hao, Jordan Dotzel, Jinjun Xiong, Luca Benini, Zhiru Zhang, Deming Chen:
Enabling Design Methodologies and Future Trends for Edge AI: Specialization and Co-design. CoRR abs/2103.15750 (2021) - 2020
- [i3]Shubham Rai, Walter Lau Neto, Yukio Miyasaka, Xinpei Zhang, Mingfei Yu, Qingyang Yi, Masahiro Fujita, Guilherme B. Manske, Matheus F. Pontes, Leomar S. da Rosa Jr., Marilton S. de Aguiar, Paulo F. Butzen, Po-Chun Chien, Yu-Shan Huang, Hoa-Ren Wang, Jie-Hong R. Jiang, Jiaqi Gu, Zheng Zhao, Zixuan Jiang, David Z. Pan, Brunno A. Abreu, Isac de Souza Campos, Augusto Andre Souza Berndt, Cristina Meinhardt, Jônata Tyska Carvalho, Mateus Grellert, Sergio Bampi, Aditya Lohana, Akash Kumar, Wei Zeng, Azadeh Davoodi, Rasit Onur Topaloglu, Yuan Zhou, Jordan Dotzel, Yichi Zhang, Hanyu Wang, Zhiru Zhang, Valerio Tenace, Pierre-Emmanuel Gaillardon, Alan Mishchenko, Satrajit Chatterjee:
Logic Synthesis Meets Machine Learning: Trading Exactness for Generalization. CoRR abs/2012.02530 (2020)
2010 – 2019
- 2019
- [c2]Ritchie Zhao, Yuwei Hu, Jordan Dotzel, Christopher De Sa, Zhiru Zhang:
Building Efficient Deep Neural Networks With Unitary Group Convolutions. CVPR 2019: 11303-11312 - [c1]Ritchie Zhao, Yuwei Hu, Jordan Dotzel, Christopher De Sa, Zhiru Zhang:
Improving Neural Network Quantization without Retraining using Outlier Channel Splitting. ICML 2019: 7543-7552 - [i2]Ritchie Zhao, Yuwei Hu, Jordan Dotzel, Christopher De Sa, Zhiru Zhang:
Improving Neural Network Quantization without Retraining using Outlier Channel Splitting. CoRR abs/1901.09504 (2019) - 2018
- [i1]Ritchie Zhao, Yuwei Hu, Jordan Dotzel, Christopher De Sa, Zhiru Zhang:
Building Efficient Deep Neural Networks with Unitary Group Convolutions. CoRR abs/1811.07755 (2018)
Coauthor Index
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