Publications

2022
Tianyu Jia, Paolo Mantovani, Maico Cassel dos santos, Davide Giri, Joseph Zuckerman, Erik Jens Loscalzo, Martin Cochet, Karthik V Swaminathan, Gabriele Tombesi, Jeff Zhang, Nandhini Chandramoorthy, John-David Wellman, Kevin Tien, Luca Carloni, Kenneth Shepard, David Brooks, Gu-Yeon Wei, and Pradip Bose. 2022. “A 12nm Agile-Designed SoC for Swarm-Based Perception with Heterogeneous IP Blocks, a Reconfigurable Memory Hierarchy, and an 800MHz Multi-Plane NoC.” In Proceedings of the 48th European Solid-State Circuits Conference (ESSCIRC 2022).
Cheng Tan, Thierry Tambe, Jeff Zhang, Bo Fang, Tong Geng, Gu-Yeon Wei, David Brooks, Antonino Tumeo, Ganesh Gopalakrishnan, and Ang Li. 2022. “ASAP: Automatic Synthesis of Area-Efficient and Precision-Aware CGRAs.” In ACM International Conference on Supercomputing (ICS 22).
Nicolas Bohm Agostini, Serena Curzel, Jeff Zhang, Ankur Limaye, Cheng Tan, Vinay Amatya, Marco Minutoli, Vito Giovanni Castellana, Joseph Manzano, David Brooks, Gu-Yeon Wei, and Antonino Tumeo. 2022. “Bridging Python to Silicon: The SODA Toolchain.” IEEE Micro.
Sizhe Zhang, Ruixuan Wang, Dongning Ma, Jeff Zhang, Xunzhao Yin, and Jiao Xun. 2022. “Energy-Efficient Brain-Inspired Hyperdimensional Computing Using Voltage Scaling.” In IEEE 25th Design, Automation and Test in Europe Conference (DATE 22, Best Paper Award Candidate).
Wen Zhang, Jeff Zhang, Tao Liu, Went Wang, and Chen Pan. 2022. “M2M-Routing: Environmental Adaptive Multi-agent Reinforcement Learning based Multi-hop Routing Policy for Self-Powered IoT Systems.” In IEEE 25th Design, Automation and Test in Europe Conference (DATE 22).
Mingsheng Yin, Akshaj Veldanda, Amee Trivedi, Jeff Zhang, Kai Pfeiffer, Yaqi Hu, Siddharth Garg, Elza Erkip, Ludovic Righetti, and Sundeep Rangan. 2022. “Millimeter Wave Wireless-Assisted Robotic Navigation with Link State Classification.” IEEE Open Journal of the Communications Society.
2021
Cheng Tan, Nicolas Bohm Agostini, Jeff Zhang, Marco Minutoli, Vito Giovanni Castellana, Chenhao Xie, Tong Geng, Ang Li, Kevin Barker, and Antonino Tumeo. 2021. “OpenCGRA: Democratizing Coarse-Grained Reconfigurable Arrays.” In IEEE 32nd International Conference on Application-specific Systems, Architectures and Processors (ASAP 21).
Udit Gupta, Samuel Hsia, Jeff Zhang, Mark Wilkening, Javin Pombra, Hsien-Hsin S Lee, Gu-Yeon Wei, Carole-Jean Wu, and David Brooks. 2021. “RecPipe: Co-designing Models and Hardware to Jointly Optimize Recommendation Quality and Performance.” In IEEE/ACM International Symposium on Microarchitecture (MICRO 21).
Muhammad Abdullah Hanif, Faiq Khalid, Rachmad Vidya Wicaksana Putra, Mohammad Taghi Teimoori, Florian Kriebel, Jeff Zhang, Kang Liu, Semeen Rehman, Theocharis Theocharides, Alessandro Artusi, Siddharth Garg, and Muhammad Shafique. 2021. “Robust Computing for Machine Learning-Based Systems.” In Dependable Embedded Systems, Pp. 479-503. Springer.
Jeff Zhang, Nicolas Bohm Agostini, Shihao Song, Cheng Tan, Ankur Limaye, Vinay Amatya, Joseph Manzano, Marco Minutoli, Vito Giovanni Castellana, Antonino Tumeo, Gu-Yeon Wei, and David Brooks. 2021. “Towards Automatic and Agile AI/ML Accelerator Design with End-to-End Synthesis.” In IEEE 32nd International Conference on Application-specific Systems, Architectures and Processors (ASAP 21).
2020
Shuayb M Zarar, Amol Ashok Ambardekar, and Jeff Zhang. 2020. “Compression-encoding scheduled inputs for matrix computations.” United States of America 10846363 (US).
Jeff Zhang, Sameh Elnikety, Shuayb Zarar, Atul Gupta, and Siddharth Garg. 2020. “Model-switching: Dealing with fluctuating workloads in machine-learning-as-a-service systems.” In 12th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud 20). Presentation [Paper] [Slides]
Amol Ashok Ambardekar, Shuayb M Zarar, and Jeff Zhang. 2020. “Selectively controlling memory power for scheduled computations.” United States of America 16355086 (US).
Jeff Zhang. 2020. “Towards Energy-Efficient and Reliable Deep Learning Inference.” New York University . [PhD Thesis]
Jeff Zhang. 2020. “What is Timing Speculative DNN Acceleration.” 'What is' Column, ACM SIGDA Electronic Newsletter. [Newsletter]
2019
Jeff Zhang, Kang Liu, Faiq Khalid, Muhammad Abdullah Hanif, Semeen Rehman, Theocharis Theocharides, Alessandro Artussi, Muhammad Shafique, and Siddharth Garg. 2019. “Building robust machine learning systems: Current progress, research challenges, and opportunities.” In Proceedings of the 56th Annual Design Automation Conference (DAC 19).
Jeff Zhang, Parul Raj, Shuayb Zarar, Amol Ambardekar, and Siddharth Garg. 2019. “CompAct: On-chip Compression of Activations for Low Power Systolic Array Based CNN Acceleration.” ACM Transactions on Embedded Computing Systems (TECS).
Jeff Zhang, Zahra Ghodsi, Siddharth Garg, and Kartheek Rangineni. 2019. “Enabling timing error resilience for low-power systolic-array based deep learning accelerators.” IEEE Design & Test.
Jeff Zhang, Kanad Basu, and Siddharth Garg. 2019. “Fault-tolerant systolic array based accelerators for deep neural network execution.” IEEE Design & Test.
Xiaotong Cui, Jeff Zhang, Kaijie Wu, Siddharth Garg, and Ramesh Karri. 2019. “Split manufacturing-based register transfer-level obfuscation.” ACM Journal on Emerging Technologies in Computing Systems (JETC).

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