Jianyu Huang

Research Scientist
Facebook, Inc.
1 Hacker Way, Menlo Park, CA 94025
Email: hjyahead [AT] gmail [DOT] com

I am a Research Scientist at Facebook. My interests lie in improving the performance of machine learning applications and simplifying the programming model for parallel computing. Before joining Facebook, I got my CS PhD from UT Austin (Advisor: Prof. Robert van de Geijn).

If you want to know more about the performance optimizations for matrix multiplication (one of the most important building blocks for deep learning), you might be interested in how to optimize GEMM and BLISlab. If you want to learn about the practical implementations of the fast matrix multiplication algorithms like Strassen's algorithm, you might be interested in my thesis.

What's New


Publications


    Deep Learning Recommendation Model for Personalization and Recommendation Systems [PDF] [BibTex]
    Maxim Naumov, Dheevatsa Mudigere, Hao-Jun Michael Shi, Jianyu Huang, Narayanan Sundaraman, Jongsoo Park, Xiaodong Wang, Udit Gupta, Carole-Jean Wu, Alisson G. Azzolini, Dmytro Dzhulgakov, Andrey Mallevich, Ilia Cherniavskii, Yinghai Lu, Raghuraman Krishnamoorthi, Ansha Yu, Volodymyr Kondratenko, Stephanie Pereira, Xianjie Chen, Wenlin Chen, Vijay Rao, Bill Jia, Liang Xiong, Misha Smelyanskiy
    submitted to NeurIPS 2019.

    A Study of BFLOAT16 for Deep Learning Training [PDF] [BibTex]
    Dhiraj Kalamkar, Dheevatsa Mudigere, Naveen Mellempudi, Dipankar Das, Kunal Banerjee, Sasikanth Avancha, Dharma Teja Vooturi, Nataraj Jammalamadaka, Jianyu Huang, Hector Yuen, Jiyan Yang, Jongsoo Park, Alexander Heinecke, Evangelos Georganas, Sudarshan Srinivasan, Abhisek Kundu, Misha Smelyanskiy, Bharat Kaul, Pradeep Dubey
    submitted to NeurIPS 2019.

    FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference [PDF] [BibTex]
    Daya Khudia, Jianyu Huang, Protonu Basu, Summer Deng, Haixin Liu, Jongsoo Park, Mikhail Smelyanskiy
    in HPCaML 2019.

    Practical Fast Matrix Multiplication Algorithms [PDF] [BibTex]
    Jianyu Huang
    PhD thesis, The University of Texas at Austin, 2018.

    Implementing Strassen’s Algorithm with CUTLASS on NVIDIA Volta GPUs [PDF] [BibTex]
    Jianyu Huang, Chenhan D. Yu, Robert A. van de Geijn
    FLAME Working Note #88, The University of Texas at Austin, Department of Computer Science. Technical Report TR-18-08. August 23, 2018.

    Learning from Optimizing Matrix-Matrix Multiplication [PDF] [BibTex]
    Devangi N. Parikh, Jianyu Huang, Margaret E. Myers, Robert A. van de Geijn
    in 8th NSF/TCPP Workshop on Parallel and Distributed Computing Education (EduPar-18), co-located with IPDPS18, Vancouver, British Columbia, Canada, 2018.

    Strassen's Algorithm for Tensor Contraction [PDF] [BibTex]
    Jianyu Huang, Devin A. Matthews, Robert A. van de Geijn
    in SIAM Journal on Scientific Computing (SISC), 40(3):C305-C326, 2018.

    Lowering Barriers into HPC through Open Education [PDF] [BibTex]
    Robert A. van de Geijn, Jianyu Huang, Margaret E. Myers, Devangi N. Parikh, Tyler M. Smith
    in Workshop on Education for High Performance Computing (EduHPC), co-located with SC17, Denver, CO, November 2017.

    Generating Families of Practical Fast Matrix Multiplication Algorithms [PDF] [BibTex] [Code] [Artifact] [PPTX]
    Jianyu Huang, Leslie Rice, Devin A. Matthews, Robert A. van de Geijn
    in 31st IEEE International Parallel and Distributed Processing Symposium (IPDPS17), Orlando, FL, May 29-June 2, 2017.

    Strassen's Algorithm Reloaded [PDF] [BibTex] [Code] [PPTX]
    Jianyu Huang, Tyler M. Smith, Greg M. Henry, Robert A. van de Geijn
    in The International Conference for High Performance Computing, Networking, Storage and Analysis (SC16), Salt Lake City, UT, November 2016.

    BLISlab: A Sandbox for Optimizing GEMM [PDF] [BibTex] [Code]
    Jianyu Huang, Robert A. van de Geijn
    FLAME Working Note #80, The University of Texas at Austin, Department of Computer Science. Technical Report TR-16-13. August 31, 2016.

    Performance Optimization for the K-Nearest Neighbors Kernel on x86 Architectures [PDF] [BibTex] [Code]
    Chenhan D. Yu, Jianyu Huang, Woody Austin, Bo Xiao, George Biros
    in The International Conference for High Performance Computing, Networking, Storage and Analysis (SC15), Austin, TX, November 2015.

Posters


    Strassen's Algorithm for Tensor Contraction [PDF] (with Devin A. Matthews and Robert A. van de Geijn)
    in The International Conference for High Performance Computing, Networking, Storage and Analysis (SC17), Denver, CO, November 2017.

    High-performance Primitives for Machine Learning Targeting Mobile Platforms (with Chenhan D. Yu)
    in Qualcomm Fellowship Finalist Presentation, San Diego, CA, March 2016.

Presentations


    Strassen's Algorithm for Tensor Contraction [PPTX,PDF]
    in BLIS Retreat 2017, Austin, TX, September 2017.

    Strassen's Algorithm for Tensor Contraction [PPTX,PDF]
    in Tensor Computation Workshop, New York City, NY, September 2017.

    Generating Families of Practical Fast Matrix Multiplication Algorithms [PPTX,PDF]
    in IPDPS17, Orlando, FL, May 31st, 2017.

    Strassen's Algorithm Reloaded [PPTX,PDF]
    in SC16, Salt Lake City, UT, November 16th, 2016.

    Implementing Strassen-like Fast Matrix Multiplication Algorithms with BLIS [PPTX,PDF] (with Leslie Rice)
    in BLIS Retreat 2016, Austin, TX, September 2016.

    High-performance Primitives for Machine Learning Targeting Mobile Platforms (with Chenhan D. Yu)
    in Qualcomm Fellowship Finalist Presentation, San Diego, CA, March 2016.

    Adding Efficient Scheduling Policy into SuperMatrix on Heterogeneous Platforms [PPTX,PDF]
    in BLIS Retreat 2015, Austin, TX, September 2015.

Teaching

Internships

Services

I have served as the reviewer for IEEE Transactions on Parallel and Distributed Systems (TPDS), ACM Transactions on Parallel Computing, Elsevier Parallel Computing, Elsevier Future Generation Computer Systems (FGCS), and SIAM Journal on Scientific Computing (SISC).

Interests

I like bicycling, swimming, jogging, reading and traveling. There is a famous Chinese proverb: Walk ten thousand miles; Read ten thousand books.

Last updated 11/28/2016