Zhuoran Zhao (赵卓然)

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I am a Research Scientist at Facebook, Menlo Park. Prior to joining Facebook, I received my Ph.D. degree in Electrical and Computer Engineering (ECE) from the University of Texas at Austin in 2019, where I worked in System-Level Architecture and Modeling (SLAM) research group under the supervision of Professor Andreas Gerstlauer. I received a B.S. in Electrical Engineering from Zhejiang University in 2012.

My research interest is in the area of electronic system-level (ESL) design and modeling, mainly including efficient runtime/middleware for distributed deep learning, system-level performance modeling and software/hardware co-design. In Facebook, I am currently doing research and development for distributed large-scale deep learning recommendation systems.

Phone: +1-512-751-1819
E-mail: zhuoran [@] utexas [DOT] edu

NEWS:

08/01/2020: Our paper Network-level Design Space Exploration of Resource-constrained Networks-of-Systems is published in ACM Transactions on Embedded Computing Systems (TECS). This is a very comprehensive paper concluding all my research stories in UT Austin!

10/07/2019: I joined Facebook as a Research Scientist in October 2019!

Research Interests

My research interests include

  • Large-Scale Deep Learning Recommendation System

  • Distributed Deep Learning

  • Distributed Computing

  • Mobile/Edge Computing

  • System-level Performance Modeling and Simulation

  • Operating System/Compiler

Research Projects

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Distributed Adaptive Deep Learning Inference Framework (DeepThings): DeepThings is a framework for locally distributed and adaptive CNN inference in resource-constrained IoT edge clusters, which mainly consists of:

  • A Fused Tile Partitioning (FTP) method for dividing convolutional layers into independently distributable tasks. FTP fuses layers and partitions them vertically in a grid fashion, which largely reduces communication and task migration overhead.

  • A distributed work stealing runtime system for IoT clusters to adaptively distribute FTP partitions in dynamic application scenarios.

Z. Zhao, K. Mirzazad and A. Gerstlauer, "DeepThings: Distributed Adaptive Deep Learning Inference on Resource-Constrained IoT Edge Clusters," CODES+ISSS, special issue of IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2018.

[PDF] [Code] [Slides] [Poster]

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Network-of-Systems Simulator (NoSSim): A source-level network/system co-simulation framework for rapid embedded/mobile system prototyping, which combines:

  • A Host-Compiled SystemC full system simulation platform with an abstract OS model.

  • A LLVM-based function-level profiling and instrumentation tool.

  • Network interaction emulation based on OMNeT++ network simulation framework and lwIP library.

Z. Zhao, V. Tsoutsouras, D. Soudris and A. Gerstlauer, "Network/System Co-Simulation for Design Space Exploration of IoT Applications," in Proceedings of the International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation (SAMOS), 2017.

[PDF][Code] [Slides]

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Retargetable Back-Annotator (RBA): A compile-time profiling and instrumentation tool for source-level system performance evaluation.

Z. Zhao, A. Gerstlauer and L. K. John, "Source-Level Performance, Energy, Reliability, Power and Thermal (PERPT) Simulation," in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2017.

[PDF][Code] [Slides] [Poster]

Selected Publications

  1. Zhuoran Zhao, Kamyar Mirzazad and Andreas Gerstlauer, "DeepThings: Distributed Adaptive Deep Learning Inference on Resource-Constrained IoT Edge Clusters," in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), Special Issue on Embedded Systems Week (ESWEEK) 2018, International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS), vol. 37, no. 11, pp. 2348-2359, October 2018.

  2. Zhuoran Zhao, Vasileios Tsoutsouras, Dimitrios Soudris and Andreas Gerstlauer, "Network/System Co-Simulation for Design Space Exploration of IoT Applications," in Proceedings of the International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation (SAMOS), Samos, Greece, July 2017.

  3. Zhuoran Zhao, Andreas Gerstlauer and Lizy K. John, "Source-Level Performance, Energy, Reliability, Power and Thermal (PERPT) Simulation," in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol. 36, no. 2, pp. 299-312, February 2017.