Niansong Zhang

Hi there! I am an MS/PhD student at Cornell University. I am advised by Prof. Zhiru Zhang. I am interested in Electronic Design Automation, Domain-Specific Language for hardware design, and hardware accelerators.

Department: Electrical & Computer Engineering
Lab: Computer Systems Laboratory
Office: 471B Rhodes Hall

Email / GitHub / LinkedIn / Google Scholar

Blog Posts

News

🎊 Our journal paper RapidLayout won the Best Paper Award for ACM TRETS in 2023. [Award Plaque] (07/13/23)

Donated my hair to Locks of Love to support children suffering from hair loss. [Certificate of Appreciation] (07/04/23)

Our journal paper has been selected as the Featured Paper of IEEE Trans. on Computers. (05/11/23)

Our patent CN109658402B has been granted. [Certificate] [Google Patents] (04/18/23)

Selected as DAC Young Fellow [Certificate] (04/08/23)

Education
Cornell University M.S./Ph.D. in Electrical and Computer Engineering Advisor: Prof. Zhiru Zhang Aug 2021 — Present
Sun Yat-sen University B.Eng. in Telecommunication Engineering Advisor: Prof. Xiang Chen Outstanding thesis Aug 2016 — Jun 2020

Work Experience
Advanced Micro Devices Compiler Intern Advanced Compilers for Distribution and Computation (ACDC) Chief Technology Organization (CTO) Manager: Stephen Neuendorffer May 2023 — Aug 2023
Intel Labs Exempt Tech Employee Specification and Validation End-to-End (SAVE) Group, SCL/ADR/IL Manager: Jin Yang, Sunny Zhang Feb 2021 — Aug 2021
Tsinghua University Research Assistant Nanoscale Integrated Circuits and System Lab (NICS-EFC) Advisor: Prof. Yu Wang Nov 2019 — Aug 2021
The University of Waterloo MITACS Research Intern WatCAG Advisor: Prof. Nachiket Kapre Jul 2019 — Oct 2019

Research & Publication

My research interests include EDA (Electronic Design Automation) for FPGA, DSL (Domain-Specific Language), and efficient machine learning.

	Supporting a Virtual Vector Instruction Set on a Commercial Compute-in-SRAM Accelerator Courtney Golden, Dan Ilan, Caroline Huang, Niansong Zhang, Zhiru Zhang, Christopher Batten IEEE Computer Architecture Letters \| paper We implement a virtual vector instruction set on a commercial Compute-in-SRAM device, and perform detailed instruction microbenchmarking to identify performance benefits and overheads.
	Serving Multi-DNN Workloads on FPGAs: a Coordinated Architecture, Scheduling, and Mapping Perspective Shulin Zeng, Guohao Dai, Niansong Zhang, Xinhao Yang, Haoyu Zhang, Zhenhua Zhu, Huazhong Yang, Yu Wang IEEE Transactions on Computers \| paper Featured Paper in the May 2023 Issue This paper proposes a Design Space Exploration framework to jointly optimize heterogeneous multi-core architecture, layer scheduling, and compiler mapping for serving DNN workloads on cloud FPGAs.
	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 Invited Paper, DAC 2022, paper We show the advantages of the decoupled programming model and further discuss some of our recent efforts to enable a robust and viable verification solution in the future.
	CodedVTR: Codebook-Based Sparse Voxel Transformer with Geometric Guidance Tianchen Zhao, Niansong Zhang, Xuefei Ning, He Wang, Li Yi, Yu Wang CVPR 2022, paper \| website \| slides \| poster \| video We propose a flexible 3D Transformer on sparse voxels to address transformer's generalization issue. CodedVTR (Codebook-based Voxel TRansformer) decomposes attention space into linear combinations of learnable prototypes to regularize attention learning. We also propose geometry-aware self-attention to guide training with geometric pattern and voxel density.
	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, paper \| code We propose an FPGA accelerator programming model that decouples the algorithm specification from optimizations related to orchestrating the placement of data across a customized memory hierarchy.
	RapidLayout: Fast Hard Block Placement of FPGA-optimized Systolic Arrays using Evolutionary Algorithms Niansong Zhang, Xiang Chen, Nachiket Kapre ACM TRETS Best Paper Award Invited Paper, ACM Transactions on Reconfigurable Technology and Systems (TRETS) Volume 15, Issue 4, Article No.: 38, pp 1–23 We extend the previous work on RapidLayout with cross-SLR routing, placement transfer learning, and placement bootstrapping from a much smaller device to improve runtime and design quality.
	aw_nas: A Modularized and Extensible NAS Framework Xuefei Ning, Changcheng Tang, Wenshuo Li, Songyi Yang, Tianchen Zhao, Niansong Zhang, Tianyi Lu, Shuang Liang, Huazhong Yang, Yu Wang Arxiv Preprint, paper \| code We build an open-source Python framework implementing various NAS algorithms in a modularized and extensible manner.
	RapidLayout: Fast Hard Block Placement of FPGA-optimized Systolic Arrays using Evolutionary Algorithms Niansong Zhang, Xiang Chen, Nachiket Kapre FPL 2020, paper \| code Michal Servit Best Paper Award Nominee We build a fast and high-performance evolutionary placer for FPGA-optimized hard block designs that targets high clock frequency such as 650+MHz.

Workshops & Talks

An MLIR-based Intermediate Representation for Accelerator Design with Decoupled Customizations

Hongzheng Chen*, Niansong Zhang*, Shaojie Xiang, Zhiru Zhang

MLIR Open Design Meeting (08/11/2022) | video | slides | website

CRISP Liaison Meeting (09/28/2022) | news | slides | website

We decouple hardware customizations from the algorithm specifications at the IR level to: (1) provide a general platform for high-level DSLs, (2) boost performance and productivity, and (3) make customization verification scalable.

Enabling Fast Deployment and Efficient Scheduling for Multi-Node and Multi-Tenant DNN Accelerators in the Cloud

Shulin Zeng, Guohao Dai, Niansong Zhang, Yu Wang

MICRO 2021 ASCMD Workshop, paper | video

We propose a multi-node and multi-core accelerator architecture and a decoupled compiler for cloud-backed INFerence-as-a-Service (INFaaS).

Professional Services

Student Volunteer: FCCM’22

Reviewer: ICCAD 2022, 2023, TRETS, TCAS II

Teaching

[ECE 5775] High-Level Digital Design Automation

Part-time TA, Fall 2022

Awards and Honors

Best Paper Award for ACM TRETS in 2023

DAC Young Fellow 2021 & 2023

FPL 2020 Best Paper Nomination (Michal Servit Award)

Outstanding Bachelor Thesis Award | Sun Yat-sen University

Mitacs Globalink Research Internship Award | Mitacs, Canada

First-class Merit Scholarship x2 | Sun Yat-sen University

Lin and Liu Foundation Scholarship | SEIT, Sun Yat-sen University

Patents

Niansong Zhang, Songyi Yang, Shun Fu, Xiang Chen, "Industry Profile Geometric Dimension Automatic Measuring Method Based on Computer Vision Imaging." Chinese Patent CN201811539019.8A, filed December 17, 2018, and issued April 19, 2019.

Niansong Zhang (at Novauto Technology), "A Pruning Method and Device of Multi-task Neural Network Models", Chinese Patent 202010805327.1, filed August 12, 2020.

Last updated: Dec 2, 2023