I am a Ph.D. candidate at the Computer Systems Laboratory, Cornell University, supervised by Prof. Zhiru Zhang. I received my B.E. degree from the School of Computer Science and Engineering, Sun Yat-sen University in 2021.

My research interests broadly lie in domain-specific languages and compilers, efficient runtime systems, and accelerator architecture. In particular, I attempt to bridge the productivity and performance gap between emerging machine learning applications and heterogeneous hardware (CPU/GPU/FPGA).

Currently, I am working on compiler optimizations for (1) large-scale model training/inference in distributed environments and (2) scalable hardware accelerator design for deep learning and scientific applications. Feel free to drop me an email if you have aligned interests.

Education

Cornell University, US
Ph.D. in Computer Science
 Aug. 2021 - Present
Thesis: Composable Programming Models for Accelerated Computing
Accumulated GPA: 4.0/4.0
Cornell University, US
M.S. in Computer Science
 Aug. 2021 - Oct. 2024
Sun Yat-sen University, China
B.E. in Computer Science		 Aug. 2017 - Jun. 2021
Thesis: High-Performance Concurrent Graph Processing System
(Outstanding Undergraduate Thesis)
Overall GPA: 3.95/4.00 (Major GPA: 3.99/4.00)
Ranking: 1/188

Work Experience

NVIDIA , Redmond, WA, US
Research Intern, Deep Learning Compiler Technology Team
Mentors: Bin Fan and Vinod Grover		 May 2024 - Nov. 2024
Amazon Web Services (AWS) , Santa Clara, CA, US
Applied Scientist Intern, Deep Engine-Science Team
Mentors: Cody Hao Yu, Shuai Zheng, and Yida Wang		 Aug. 2022 - Apr. 2023
ByteDance AI Lab , Beijing, China
Research Intern, MLSys Team, Applied Machine Learning (AML)
Mentors: Jun He and Yibo Zhu		 Aug. 2020 - May 2021

News

  • [10/16/24] [Talk] I passed the Examination for Admission to Candidacy (A Exam) and became a PhD candidate! Thanks for all the support!
  • [10/01/24] [Talk] Niansong and I will attend the annual review of the SRC JUMP 2.0 ACE Center in Chicago from Oct 1 to Oct 3 and give a presentation on Allo. See you there!
  • [08/22/24] [Talk] I gave a final presentation for my internship project on Automatic Warp Specialization for Hopper Architecture at NVIDIA. I will continue working on it as a part-time intern until November.
  • [07/01/24] [Talk] I will be attending the 2024 MLSys Rising Star workshop at the NVIDIA Headquarter in Santa Clara, CA from July 15 to July 16. See you in the Bay Area!
  • [06/27/24] [Award] I received 3rd place in the ACM SIGPLAN PLDI Student Research Competition (SRC).
  • [06/10/24] [Talk] I will give a talk on Slapo for distributed model training at ByteDance on Jun 14. Thanks Youjie for inviting me!
  • [05/16/24] [Award] I am selected as one of the ML and Systems Rising Stars! Thanks for all the support!
  • [05/11/24] [Talk] Received the PLDI’24 Travel Grant. I will present our work on Allo in Copenhagen, Denmark at the end of June. Please come to find me if you are around!
  • [05/10/24] [Talk] I will give a talk on LLM acceleration with Allo at UW SAMPL group on May 31. Thanks Keisuke for inviting me!

Publications

Allo: A Programming Model for Composable Accelerator Design
Hongzheng Chen*, Niansong Zhang*, Shaojie Xiang, Zhichen Zeng, Mengjia Dai, Zhiru Zhang
PLDI, 2024 | Blog (Zhihu)

Understanding the Potential of FPGA-Based Spatial Acceleration for Large Language Model Inference
Hongzheng Chen, Jiahao Zhang, Yixiao Du, Shaojie Xiang, Zichao Yue, Niansong Zhang, Yaohui Cai, Zhiru Zhang
ACM Transactions on Reconfigurable Technology and Systems (TRETS), 2024 (FCCM’24 Journal Track) | Blog (Zhihu)

Slapo: A Schedule Language for Progressive Optimization of Large Deep Learning Model Training
Hongzheng Chen, Cody Hao Yu, Shuai Zheng, Zhen Zhang, Zhiru Zhang, Yida Wang
ASPLOS, 2024 | Amazon Science

Formal Verification of Source-to-Source Transformations for HLS
Louis-Noël Pouchet, Emily Tucker, Niansong Zhang, Hongzheng Chen, Debjit Pal, Gabriel Rodríguez, Zhiru Zhang
FPGA, 2024 (Best Paper Award) | Cornell ECE News

BGL: GPU-Efficient GNN Training by Optimizing Graph Data I/O and Preprocessing
Tianfeng Liu*, Yangrui Chen*, Dan Li, Chuan Wu, Yibo Zhu, Jun He, Yanghua Peng, Hongzheng Chen, Hongzhi Chen, Chuanxiong Guo
NSDI, 2023

Accelerator Design with Decoupled Hardware Customizations: Benefits and Challenges
Debjit Pal, Yi-Hsiang Lai, Shaojie Xiang, Niansong Zhang, Hongzheng Chen, Jeremy Casas, Pasquale Cocchini, Zhenkun Yang, Jin Yang, Louis-Noël Pouchet, Zhiru Zhang
DAC, 2022 (Invited Paper)

HeteroFlow: An Accelerator Programming Model with Decoupled Data Placement for Software-Defined FPGAs
Shaojie Xiang, Yi-Hsiang Lai, Yuan Zhou, Hongzheng Chen, Niansong Zhang, Debjit Pal, Zhiru Zhang
FPGA, 2022

Krill: A Compiler and Runtime System for Concurrent Graph Processing
Hongzheng Chen, Minghua Shen, Nong Xiao, Yutong Lu
SC, 2021

FracBNN: Accurate and FPGA-Efficient Binary Neural Networks with Fractional Activations
Yichi Zhang, Junhao Pan, Xinheng Liu, Hongzheng Chen, Deming Chen, Zhiru Zhang
FPGA, 2021 (Best Paper Nominee)

Entropy-Directed Scheduling for FPGA High-Level Synthesis
Minghua Shen, Hongzheng Chen (Corresponding author), Nong Xiao
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2020

A Deep-Reinforcement-Learning-Based Scheduler for FPGA HLS
Hongzheng Chen, Minghua Shen
ICCAD, 2019

Workshops / Preprints

Uncovering Magic with Magic: Schedule Reconstruction from High-Performance Kernel Libraries
Hongzheng Chen
PLDI Student Research Competition (SRC), 2024 (Bronze)

Structured Pruning is All You Need for Pruning CNNs at Initialization
Yaohui Cai, Weizhe Hua, Hongzheng Chen, G. Edward Suh, Christopher De Sa, Zhiru Zhang
arXiv:2203.02549, 2022

Teaching

Professional Service

Awards & Honors

Scholarship

  • SenseTime Scholarship (21 undergrads in China), SenseTime, 2020
  • Chinese National Scholarship $\times$ 2 (Top 1%), Ministry of Education of PRC, 2018-2020
  • First-Prize Scholarship $\times$ 3 (Top 5%), Sun Yat-sen University, 2017-2020
  • Samsung Scholarship (Top 1%), Samsung Electronics, 2017-2018

Travel Grants

  • Graduate School Conference Grant, Cornell University, 2024
  • SIGPLAN PLDI’24 Student Travel Grant, SIGPLAN, 2024
  • IEEE FCCM’24 Student Travel Grant, FCCM, 2024
  • SIGPLAN ASPLOS’24 Student Travel Grant, SIGPLAN, 2024
  • Graduate School Conference Grant, Cornell University, 2023
  • USENIX NSDI’23 Student Travel Grant, USENIX, 2023

Talks