Cong (Callie) Hao

Cong (Callie) Hao

Georgia Institute of Technology

H-index: 19

North America-United States

About Cong (Callie) Hao

Cong (Callie) Hao, With an exceptional h-index of 19 and a recent h-index of 19 (since 2020), a distinguished researcher at Georgia Institute of Technology, specializes in the field of FPGA, High Level Synthesis, Machine Learning, EDA.

His recent articles reflect a diverse array of research interests and contributions to the field:

Programmable analog system benchmarks leading to efficient analog computation synthesis

AutoAI2C: An Automated Hardware Generator for DNN Acceleration On Both FPGA and ASIC

LightningSimV2: Faster and Scalable Simulation for High-Level Synthesis via Graph Compilation and Optimization

Dgnn-booster: A generic fpga accelerator framework for dynamic graph neural network inference

Data-model-circuit tri-design for ultra-light video intelligence on edge devices

Gnnbuilder: An automated framework for generic graph neural network accelerator generation, simulation, and optimization

INR-Arch: A Dataflow Architecture and Compiler for Arbitrary-Order Gradient Computations in Implicit Neural Representation Processing

Cask HLS: A Better Development Tool for Vitis HLS

Cong (Callie) Hao Information

University

Position

___

Citations(all)

1349

Citations(since 2020)

1309

Cited By

265

hIndex(all)

19

hIndex(since 2020)

19

i10Index(all)

32

i10Index(since 2020)

32

Email

University Profile Page

Georgia Institute of Technology

Google Scholar

View Google Scholar Profile

Cong (Callie) Hao Skills & Research Interests

FPGA

High Level Synthesis

Machine Learning

EDA

Top articles of Cong (Callie) Hao

Title

Journal

Author(s)

Publication Date

Programmable analog system benchmarks leading to efficient analog computation synthesis

ACM Transactions on Reconfigurable Technology and Systems

Jennifer Hasler

Cong Hao

2024/1/27

AutoAI2C: An Automated Hardware Generator for DNN Acceleration On Both FPGA and ASIC

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems

Yongan Zhang

Xiaofan Zhang

Pengfei Xu

Yang Zhao

Cong Hao

...

2024/4/24

LightningSimV2: Faster and Scalable Simulation for High-Level Synthesis via Graph Compilation and Optimization

arXiv preprint arXiv:2404.09471

Rishov Sarkar

Rachel Paul

Cong Hao

2024/4/15

Dgnn-booster: A generic fpga accelerator framework for dynamic graph neural network inference

Hanqiu Chen

Cong Hao

2023/5/8

Data-model-circuit tri-design for ultra-light video intelligence on edge devices

Yimeng Zhang

Akshay Karkal Kamath

Qiucheng Wu

Zhiwen Fan

Wuyang Chen

...

2023/1/16

Gnnbuilder: An automated framework for generic graph neural network accelerator generation, simulation, and optimization

arXiv preprint arXiv:2303.16459

Stefan Abi-Karam

Cong Hao

2023/3/29

INR-Arch: A Dataflow Architecture and Compiler for Arbitrary-Order Gradient Computations in Implicit Neural Representation Processing

Stefan Abi-Karam

Rishov Sarkar

Dejia Xu

Zhiwen Fan

Zhangyang Wang

...

2023/10/28

Cask HLS: A Better Development Tool for Vitis HLS

Andrew Nazareth

Bernardo Perez

Rachel Paul

James Root

Ritarka Samanta

...

2023/4/23

Extensible and efficient proxy for neural architecture search

Yuhong Li

Jiajie Li

Cong Hao

Pan Li

Jinjun Xiong

...

2023

Gamora: Graph learning based symbolic reasoning for large-scale boolean networks

Nan Wu

Yingjie Li

Cong Hao

Steve Dai

Cunxi Yu

...

2023/7/9

M5: Multi-modal Multi-task Model Mapping on Multi-FPGA with Accelerator Configuration Search

Akshay Karkal Kamath

Stefan Abi-Karam

Ashwin Bhat

Cong Hao

2023/4/17

From Acceleration to Accelerating Acceleration: Modernizing the Accelerator Landscape using High-Level Synthesis

Rishov Sarkar

Cong Hao

2023/5/8

Edge-moe: Memory-efficient multi-task vision transformer architecture with task-level sparsity via mixture-of-experts

Rishov Sarkar

Hanxue Liang

Zhiwen Fan

Zhangyang Wang

Cong Hao

2023/10/28

Hardware/Software Co-design for Machine Learning Accelerators

Hanqiu Chen

Cong Hao

2023/5/8

PreAxC: Error Distribution Prediction for Approximate Computing Quality Control using Graph Neural Networks

Lakshmi Sathidevi

Abhinav Sharma

Nan Wu

Xun Jiao

Cong Hao

2023/4/5

Analog System High-Level Synthesis for Energy-Efficient Reconfigurable Computing

Journal of Low Power Electronics and Applications

Afolabi Ige

Linhao Yang

Hang Yang

Jennifer Hasler

Cong Hao

2023/10/26

FlowGNN: A dataflow architecture for real-time workload-agnostic graph neural network inference

Rishov Sarkar

Stefan Abi-Karam

Yuqi He

Lakshmi Sathidevi

Cong Hao

2023/2/25

LightningSim: Fast and accurate trace-based simulation for High-Level Synthesis

Rishov Sarkar

Cong Hao

2023/5/8

Compilation and Optimizations for Efficient Machine Learning on Embedded Systems

Xiaofan Zhang

Yao Chen

Cong Hao

Sitao Huang

Yuhong Li

...

2023/10/10

Ai-assisted synthesis in next generation eda: Promises, challenges, and prospects

Nan Wu

Yuan Xie

Cong Hao

2022/10/23

See List of Professors in Cong (Callie) Hao University(Georgia Institute of Technology)

Co-Authors

H-index: 183
Thomas S. Huang

Thomas S. Huang

University of Illinois at Urbana-Champaign

H-index: 57
Deming Chen

Deming Chen

University of Illinois at Urbana-Champaign

H-index: 47
Min-You Wu

Min-You Wu

Shanghai Jiao Tong University

H-index: 44
Humphrey Shi

Humphrey Shi

University of Oregon

H-index: 30
Yuchen Fan

Yuchen Fan

University of Illinois at Urbana-Champaign

H-index: 19
Xiaofan Zhang

Xiaofan Zhang

University of Illinois at Urbana-Champaign

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