Recent News

[08/26/2019] Congratulations on Ritchie Zhao's graduation!

[07/17/2019] Prof. Zhang chaired the IEEE ASAP 2019 conference at Cornell Tech, NYC.

[07/10/2019] Farewell John and Cunxi!

[06/21/2019] Ritchie and Jordan presented our new research results on efficient deep learning at ICML’19 and CVPR'19.

[06/07/2019] Zhang Group presented five papers at DAC’19 on design methodologies and automation for hardware specialization.

[05/27/2019] Nitish and Ecenur presented two papers at FCCM’19 on compilation for FPGAs.

[04/04/2019] Prof. Zhang received Google Faculty Research Award.

[03/04/2019] HeteroCL Paper Received the FPGA'19 Best Paper Award!

[02/04/2019] Steve Dai wins the 2019 ECE Outstanding Thesis Research Award.

[01/30/2019] Five papers accepted to DAC 2019 from our group!

[01/09/2019] Congratulations on Steve Dai's graduation!

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Research Projects

Algorithm-Hardware Co-Design for Machine Learning Acceleration

Our group is investigating various accelerator architectures for compute-intensive machine learning applications, where we employ an algorithm-hardware co-design approach to achieving both high performance and low energy.

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Multi-Paradigm Programming for Heterogeneous Platforms

we are developing HeteroCL, a highly productive multi-paradigm programming infrastructure that explicitly embraces heterogeneity to integrate a variety of programming models into a single, unified programming interface.

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High-Level Synthesis of Fast and Secure Accelerators

We are developing a new generation of HLS techniques that feature scalable cross-layer synthesis and exact optimization, complexity-effective dynamic scheduling, trace-based analysis, and information flow enforcement to enable a greatly simplified hardware design experience, while achieving a high performance and satisfying the ...

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Learning-Assisted IC Design Closure

We believe there is a great potential for employing ML across different stages of the design automation stack to expedite design closure by (1) minimizing human supervision in the overall design tuning process and (2) significantly reducing the time required to obtain accurate QoR estimation for a given design point....

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People

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Prof. Zhiru Zhang

Principle Investigator

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Yuan Zhou

MS/PhD, started F'15

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Nitish Srivastava

MS/PhD, started F'14, co-advised with Prof. David Albonesi

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Ecenur Ustun

MS/PhD, started F'16

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Yi-Hsiang (Sean) Lai

MS/PhD, started F'16

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Hanchen Jin

MS/PhD, started S'18

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Yuwei Hu

MS/PhD, started S'18

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Chenghui Deng

MS/PhD, started F'18

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Shaojie Xiang

MS/PhD, started F'18

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Yichi Zhang

MS/PhD, started F'18

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Jordan Dotzel

MS/PhD, started F'19

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Debjit Pal

PostDoc, started F'19

Alumni

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Ritchie Zhao

PhD, 2014-2019. Now at Microsoft, Seattle, WA.

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Dr. Cunxi Yu

PostDoc, 2018-2019. Now at University of Utah, Salt Lake city, UT.

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Dr. Zhenghong (John) Jiang

PostDoc, 2016-2019. Now at Cadence, San Jose, CA.

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Steve Dai

PhD, 2013-2018. Now at NVIDIA Research, Santa Clara, CA.

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Gai Liu

PhD, 2013-2018. Now at Xilinx, San Jose, CA.

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Qiang You

Visiting PhD, Tsinghua Univ., 2018. Now at Sinovation Ventures AI Institute, Beijing, China.

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Chang Xu

Visiting PhD, Peking Univ., 2015-2016. Now at IBM Research, Beijing, China.

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Mingxing Tan

PostDoc, 2013-2015. Now at Google Brain, Mountain View, CA.