I'm an Assistant Professor in the Department of Computer Science at Illinois Institute of Technology. My research interest includes computer architecture, software-hardware co-design, emerging memory/storage technologies, machine learning acceleration, and privacy-preserving computing. You can find my CV here. Here is the list of my publications.
I am actively looking for self-motivated students at all levels for various research projects in the fields of computer architectures, systems, compilers, software-hardware co-design, privacy-preserving computing, and machine learning. The projects will involve active collaborations with UCSD, UIUC, ETH Zurich, UT Dallas, Intel Labs, IBM Research, and other groups at IIT. If you are interested in working with me, please send an email with a subject of "Potential Students" to mzhou26 at iit dot edu.
I am actively looking for self-motivated students at all levels for various research projects in the fields of computer architectures, systems, compilers, software-hardware co-design, privacy-preserving computing, and machine learning. The projects will involve active collaborations with UCSD, UIUC, ETH Zurich, UT Dallas, Intel Labs, IBM Research, and other groups at IIT. If you are interested in working with me, please send an email with a subject of "Potential Students" to mzhou26 at iit dot edu.
Publications (Google Scholar)
[MICRO'24] Minxuan Zhou, Yujin Nam, Xuan Wang, Youhak Lee, Chris Wilkerson, Raghavan Kumar, Sachin Taneja, Sanu Mathew, Rosario Cammarota, and Tajana Rosing, “UFC: A Unified Accelerator for Fully Homomorphic Encryption”, 57th IEEE/ACM International Symposium on Microarchitecture (MICRO), 2024 (to appear)
[ICCAD'24] Chien-Yi Yang, Minxuan Zhou, Flavio Ponzina, Suraj Sathya Prakash, Raid Ayoub, Pietro Mercati, Mahesh Subedar, and Tajana Rosing, “Multi-Objective Software-Hardware Co-Optimizationfor HD-PIM via Noise-Aware Bayesian Optimization”, ACM/IEEE International Conference on Computer-Aided Design (ICCAD), 2024 (to appear)
[TCAD'24] Xuan Wang*, Minxuan Zhou*,and Tajana Rosing. “Fast-OverlaPIM: A Fast Overlap-driven Mapping Framework for Processing In-Memory Neural Network Acceleration”. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2024
[DAC'24] Eunji Kwon, Minxuan Zhou, Weihong Xu, Tajana Rosing and Seokhyeong Kang, “RL-PTQ: RL-based Mixed Precision Quantization for Hybrid Vision Transformers”, Design Automation Conference (DAC), 2024
[DATE'24] Jaeyoung Kang, You Hak Lee, Minxuan Zhou, Weihong Xu and Tajana Rosing, “HygHD: Hyperdimensional Hypergraph Learning”, Design, Automation, and Test in Europe (DATE), 2024
[ASP-DAC'24] Yue Pan, Minxuan Zhou, Chonghan Lee, Zheyu Li, Rishika Kushwah, Vijaykrishnan Narayanan, and Tajana Rosing, “PRIMATE: Processing in Memory Acceleration for Dynamic Token-pruning Transformers”, 29th Asia and South Pacific Design Automation Conference (ASP-DAC), 2024
[Arxiv'23] Minxuan Zhou, Yujin Nam, Pranav Gangwar, Weihong Xu, Arpan Dutta, Kartikeyan Subramanyam, Chris Wilkerson, Rosario Cammarota, Saransh Gupta, and Tajana Rosing. "FHEmem: A Processing In-Memory Accelerator for Fully Homomorphic Encryption". arXiv:2311.16293
[TACO'23] Lingxi Wu*, Minxuan Zhou*, Weihong Xu, Ashish Venkat, Tajana Rosing, and Kevin Skadron. "Abakus: Accelerating k-mer Counting With Storage Technology". ACM Trans. Archit. Code Optim. https://doi.org/10.1145/3632952
[ISLPED'23] Yujin Nam, Minxuan Zhou, Saransh Gupta, Gabrielle De Micheli, Rosario Cammarota, Chris Wilkerson, Daniele Micciancio, and Tajana Rosing, “Efficient Machine Learning on Encrypted Data using Hyperdimensional Computing”, IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED), 2023
[DATE'23] Minxuan Zhou*, Xuan Wang*, and Tajana Rosing, “OverlaPIM: Overlap Optimization for Processing In-Memory Neural Network Acceleration”, Design, Automation and Test in Europe Conference (DATE’23), 2023
[ICCD'22] Jaeyoung Kang, Minxuan Zhou, Abhinav Bhansali, Weihong Xu, Anthony Thomas and Tajana Rosing, “RelHD: A Lightweight Graph-based Learning with Hyperdimensional Computing”, The 40th IEEE International Conference on Computer Design (ICCD’22), 2022
[HPCA'22] Minxuan Zhou*, Weihong Xu*, Jaeyoung Kang, and Tajana Rosing, “TransPIM: A Memory-based Acceleration via Software-Hardware Co-Design for Transformers”, The 28th IEEE International Symposium on High-Performance Computer Architecture (HPCA’22), 2022
[DATE'22] Yizhou Wei, Minxuan Zhou, Sihang Liu, Korakit Seemakhupt, Tajana Rosing and Samira Khan. “PIMProf: An Automated Program Profiler for Processing-in-Memory Offloading Decisions”, Design, Automation and Test in Europe Conference (DATE’22), 2022
[PACT'21] Minxuan Zhou, Lingxi Wu, Muzhou Li, Niema Moshiri, Kevin Skadron, and Tajana Rosing, “Ultra Efficient Acceleration for De Novo Genome Assembly via Near-Memory Computing”, International Conference on Parallel Architectures and Compilation Techniques (PACT), 2021
[PACT'21] Minxuan Zhou, Guoyang Chen, Mohsen Imani, Saransh Gupta, Weifeng Zhang, and Tajana Rosing, “PIM-DL: Boosting DNN Inference on Digital Processing In-Memory Architectures via Data Layout Optimizations”, International Conference on Parallel Architectures and Compilation Techniques (PACT), 2021
[DAC'21] Minxuan Zhou, Yunhui Guo, Weihong Xu, Bin Li, Kevin Eliceiri, and Tajana Rosing, “MAT: Processing In-Memory Acceleration for Long-Sequence Attention”, Design Automation Conference (DAC), 2021
[DATE'21] Minxuan Zhou, Muzhou Li, Mohsen Imani, and Tajana Rosing, “HyGraph: Accelerating Graph Processing with Hybrid Memory-centric Computing”, Design, Automation and Test in Europe Conference (DATE), 2021
[ASP-DAC'21] Minxuan Zhou, Mohsen Imani, Yeseong Kim, Saransh Gupta, and Tajana Rosing, “DPSim: A Full-stack Simulation Infrastructure for Digital Processing In-Memory Architecture”, 26th Asia and South Pacific Design Automation Conference (ASP-DAC), 2021
[GLSVLSI'19] Mohsen Imani, Saransh Gupta, Yeseong Kim, Minxuan Zhou, and Tajana Rosing. DigitalPIM: Digital-based Processing In-Memory for Big Data Acceleration. ACM Proceedings of the 2019 on Great Lakes Symposium on VLSI
[TCAD'19] Minxuan Zhou, Andreas Prodromou, Rui Wang, Hailong Yang, Depei Qian, Dean Tullsen. “Temperature-Aware DRAM Cache Management -Relaxing Thermal Constraints in 3D Systems”. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2019
[ISLPED'19] Xiao Liu, Minxuan Zhou, Tajana Rosing, and Jishen Zhao. 2019. HR3AM: A Heat Resilient Design for RRAM-based Neuromorphic Computing. accepted in ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED), 2019
[DAC'19] Minxuan Zhou, Mohsen Imani, Saransh Gupta, and Tajana Rosing, “Thermal-Aware Design and Management for Search-based In-Memory Acceleration”, Design Automation Conference (DAC), 2019.
[ASP-DAC'19] Minxuan Zhou, Mohsen Imani, Saransh Gupta, Yeseong Kim, and Tajana Rosing, “GRAM: Graph Processing in a ReRAM-based Computational Memory”, 24th Asia and South Pacific Design Automation Conference (ASP-DAC), 2019
[ISLPED'18] Minxuan Zhou, Mohsen Imani, Saransh Gupta, and Tajana Rosing, “GAS: A Heterogeneous Memory Acceleration for Graph Processing”, IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED), 2018.
[JSS"16] Cheng, Kun, Yuebin Bai, Yongwang Zhao, Yao Ma, Duo Lu, Yuanfeng Peng, and Minxuan Zhou. “HV 2 M: A novel approach to boost inter-VM network performance for Xen-based HVMs.” Journal of Systems and Software 114 (2016): 54-68.
[MICRO'24] Minxuan Zhou, Yujin Nam, Xuan Wang, Youhak Lee, Chris Wilkerson, Raghavan Kumar, Sachin Taneja, Sanu Mathew, Rosario Cammarota, and Tajana Rosing, “UFC: A Unified Accelerator for Fully Homomorphic Encryption”, 57th IEEE/ACM International Symposium on Microarchitecture (MICRO), 2024 (to appear)
[ICCAD'24] Chien-Yi Yang, Minxuan Zhou, Flavio Ponzina, Suraj Sathya Prakash, Raid Ayoub, Pietro Mercati, Mahesh Subedar, and Tajana Rosing, “Multi-Objective Software-Hardware Co-Optimizationfor HD-PIM via Noise-Aware Bayesian Optimization”, ACM/IEEE International Conference on Computer-Aided Design (ICCAD), 2024 (to appear)
[TCAD'24] Xuan Wang*, Minxuan Zhou*,and Tajana Rosing. “Fast-OverlaPIM: A Fast Overlap-driven Mapping Framework for Processing In-Memory Neural Network Acceleration”. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2024
[DAC'24] Eunji Kwon, Minxuan Zhou, Weihong Xu, Tajana Rosing and Seokhyeong Kang, “RL-PTQ: RL-based Mixed Precision Quantization for Hybrid Vision Transformers”, Design Automation Conference (DAC), 2024
[DATE'24] Jaeyoung Kang, You Hak Lee, Minxuan Zhou, Weihong Xu and Tajana Rosing, “HygHD: Hyperdimensional Hypergraph Learning”, Design, Automation, and Test in Europe (DATE), 2024
[ASP-DAC'24] Yue Pan, Minxuan Zhou, Chonghan Lee, Zheyu Li, Rishika Kushwah, Vijaykrishnan Narayanan, and Tajana Rosing, “PRIMATE: Processing in Memory Acceleration for Dynamic Token-pruning Transformers”, 29th Asia and South Pacific Design Automation Conference (ASP-DAC), 2024
[Arxiv'23] Minxuan Zhou, Yujin Nam, Pranav Gangwar, Weihong Xu, Arpan Dutta, Kartikeyan Subramanyam, Chris Wilkerson, Rosario Cammarota, Saransh Gupta, and Tajana Rosing. "FHEmem: A Processing In-Memory Accelerator for Fully Homomorphic Encryption". arXiv:2311.16293
[TACO'23] Lingxi Wu*, Minxuan Zhou*, Weihong Xu, Ashish Venkat, Tajana Rosing, and Kevin Skadron. "Abakus: Accelerating k-mer Counting With Storage Technology". ACM Trans. Archit. Code Optim. https://doi.org/10.1145/3632952
[ISLPED'23] Yujin Nam, Minxuan Zhou, Saransh Gupta, Gabrielle De Micheli, Rosario Cammarota, Chris Wilkerson, Daniele Micciancio, and Tajana Rosing, “Efficient Machine Learning on Encrypted Data using Hyperdimensional Computing”, IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED), 2023
[DATE'23] Minxuan Zhou*, Xuan Wang*, and Tajana Rosing, “OverlaPIM: Overlap Optimization for Processing In-Memory Neural Network Acceleration”, Design, Automation and Test in Europe Conference (DATE’23), 2023
[ICCD'22] Jaeyoung Kang, Minxuan Zhou, Abhinav Bhansali, Weihong Xu, Anthony Thomas and Tajana Rosing, “RelHD: A Lightweight Graph-based Learning with Hyperdimensional Computing”, The 40th IEEE International Conference on Computer Design (ICCD’22), 2022
[HPCA'22] Minxuan Zhou*, Weihong Xu*, Jaeyoung Kang, and Tajana Rosing, “TransPIM: A Memory-based Acceleration via Software-Hardware Co-Design for Transformers”, The 28th IEEE International Symposium on High-Performance Computer Architecture (HPCA’22), 2022
[DATE'22] Yizhou Wei, Minxuan Zhou, Sihang Liu, Korakit Seemakhupt, Tajana Rosing and Samira Khan. “PIMProf: An Automated Program Profiler for Processing-in-Memory Offloading Decisions”, Design, Automation and Test in Europe Conference (DATE’22), 2022
[PACT'21] Minxuan Zhou, Lingxi Wu, Muzhou Li, Niema Moshiri, Kevin Skadron, and Tajana Rosing, “Ultra Efficient Acceleration for De Novo Genome Assembly via Near-Memory Computing”, International Conference on Parallel Architectures and Compilation Techniques (PACT), 2021
[PACT'21] Minxuan Zhou, Guoyang Chen, Mohsen Imani, Saransh Gupta, Weifeng Zhang, and Tajana Rosing, “PIM-DL: Boosting DNN Inference on Digital Processing In-Memory Architectures via Data Layout Optimizations”, International Conference on Parallel Architectures and Compilation Techniques (PACT), 2021
[DAC'21] Minxuan Zhou, Yunhui Guo, Weihong Xu, Bin Li, Kevin Eliceiri, and Tajana Rosing, “MAT: Processing In-Memory Acceleration for Long-Sequence Attention”, Design Automation Conference (DAC), 2021
[DATE'21] Minxuan Zhou, Muzhou Li, Mohsen Imani, and Tajana Rosing, “HyGraph: Accelerating Graph Processing with Hybrid Memory-centric Computing”, Design, Automation and Test in Europe Conference (DATE), 2021
[ASP-DAC'21] Minxuan Zhou, Mohsen Imani, Yeseong Kim, Saransh Gupta, and Tajana Rosing, “DPSim: A Full-stack Simulation Infrastructure for Digital Processing In-Memory Architecture”, 26th Asia and South Pacific Design Automation Conference (ASP-DAC), 2021
[GLSVLSI'19] Mohsen Imani, Saransh Gupta, Yeseong Kim, Minxuan Zhou, and Tajana Rosing. DigitalPIM: Digital-based Processing In-Memory for Big Data Acceleration. ACM Proceedings of the 2019 on Great Lakes Symposium on VLSI
[TCAD'19] Minxuan Zhou, Andreas Prodromou, Rui Wang, Hailong Yang, Depei Qian, Dean Tullsen. “Temperature-Aware DRAM Cache Management -Relaxing Thermal Constraints in 3D Systems”. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2019
[ISLPED'19] Xiao Liu, Minxuan Zhou, Tajana Rosing, and Jishen Zhao. 2019. HR3AM: A Heat Resilient Design for RRAM-based Neuromorphic Computing. accepted in ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED), 2019
[DAC'19] Minxuan Zhou, Mohsen Imani, Saransh Gupta, and Tajana Rosing, “Thermal-Aware Design and Management for Search-based In-Memory Acceleration”, Design Automation Conference (DAC), 2019.
[ASP-DAC'19] Minxuan Zhou, Mohsen Imani, Saransh Gupta, Yeseong Kim, and Tajana Rosing, “GRAM: Graph Processing in a ReRAM-based Computational Memory”, 24th Asia and South Pacific Design Automation Conference (ASP-DAC), 2019
[ISLPED'18] Minxuan Zhou, Mohsen Imani, Saransh Gupta, and Tajana Rosing, “GAS: A Heterogeneous Memory Acceleration for Graph Processing”, IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED), 2018.
[JSS"16] Cheng, Kun, Yuebin Bai, Yongwang Zhao, Yao Ma, Duo Lu, Yuanfeng Peng, and Minxuan Zhou. “HV 2 M: A novel approach to boost inter-VM network performance for Xen-based HVMs.” Journal of Systems and Software 114 (2016): 54-68.
