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Towards High-Performance Graph Processing: From a Hardware/Software Co-Design Perspective

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Abstract

Graph processing has been widely used in many scenarios, from scientific computing to artificial intelligence. Graph processing exhibits irregular computational parallelism and random memory accesses, unlike traditional workloads. Therefore, running graph processing workloads on conventional architectures (e.g., CPUs and GPUs) often shows a significantly low compute-memory ratio with few performance benefits, which can be, in many cases, even slower than a specialized single-thread graph algorithm. While domain-specific hardware designs are essential for graph processing, it is still challenging to transform the hardware capability to performance boost without coupled software codesigns. This article presents a graph processing ecosystem from hardware to software. We start by introducing a series of hardware accelerators as the foundation of this ecosystem. Subsequently, the codesigned parallel graph systems and their distributed techniques are presented to support graph applications. Finally, we introduce our efforts on novel graph applications and hardware architectures. Extensive results show that various graph applications can be efficiently accelerated in this graph processing ecosystem.

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Acknowledgments

We thank the following students for their contributions, where Ke-Xin Li and Bing Zhu participated in the work on the graph accelerators design, Dan Chen, Zhao-Zeng An, Yu-Jian Liao, Qian-Ge Shen, Dong-Hao He, Shi-Jun Li, Xin Ning, and Zhi-Ying Huang participated in the work on the graph software environment, and Dan Chen, Chao-Qiang Liu, Hai-Feng Liu, Hai-Heng He, and Zhao-Zeng An participated in the work on the emerging hardware/software co-design.

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Authors and Affiliations

  1. National Engineering Research Center for Big Data Technology and System, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China

    Xiao-Fei Liao  (廖小飞), Wen-Ju Zhao  (赵文举), Hai Jin  (金　海), Peng-Cheng Yao  (姚鹏程), Yu Huang  (黄　禹), Qing-Gang Wang  (王庆刚), Jin Zhao  (赵　进), Long Zheng  (郑　龙), Yu Zhang  (张　宇) & Zhi-Yuan Shao  (邵志远)

  2. Services Computing Technology and System Laboratory, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China

    Xiao-Fei Liao  (廖小飞), Wen-Ju Zhao  (赵文举), Hai Jin  (金　海), Peng-Cheng Yao  (姚鹏程), Yu Huang  (黄　禹), Qing-Gang Wang  (王庆刚), Jin Zhao  (赵　进), Long Zheng  (郑　龙), Yu Zhang  (张　宇) & Zhi-Yuan Shao  (邵志远)

  3. Cluster and Grid Computing Laboratory, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China

    Xiao-Fei Liao  (廖小飞), Wen-Ju Zhao  (赵文举), Hai Jin  (金　海), Peng-Cheng Yao  (姚鹏程), Yu Huang  (黄　禹), Qing-Gang Wang  (王庆刚), Jin Zhao  (赵　进), Long Zheng  (郑　龙), Yu Zhang  (张　宇) & Zhi-Yuan Shao  (邵志远)

  4. Zhejiang Lab, Hangzhou, 311121, China

    Peng-Cheng Yao  (姚鹏程), Yu Huang  (黄　禹), Qing-Gang Wang  (王庆刚), Jin Zhao  (赵　进), Long Zheng  (郑　龙), Yu Zhang  (张　宇) & Zhi-Yuan Shao  (邵志远)

Authors
  1. Xiao-Fei Liao  (廖小飞)
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  2. Wen-Ju Zhao  (赵文举)
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  3. Hai Jin  (金　海)
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  4. Peng-Cheng Yao  (姚鹏程)
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  5. Yu Huang  (黄　禹)
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  6. Qing-Gang Wang  (王庆刚)
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  7. Jin Zhao  (赵　进)
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  8. Long Zheng  (郑　龙)
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  9. Yu Zhang  (张　宇)
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  10. Zhi-Yuan Shao  (邵志远)
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Correspondence to Hai Jin  (金　海).

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Conflict of Interest The authors declare that they have no conflict of interest.

Additional information

This work was supported by the National Key Research and Development Program of China under Grant No. 2023YFB-4502300.

Xiao-Fei Liao is a professor in the School of Computer Science and Technology at Huazhong University of Science and Technology (HUST), Wuhan. He received his Ph.D. degree in computer science and engineering from HUST, Wuhan, in 2005. He was awarded Excellent Youth Award from the National Science Foundation of China in 2018, and CCF-IEEE CS Young Computer Scientist Award in 2017. His research interests are in the areas of computer architecture, system software, and big data processing.

Wen-Ju Zhao is a Ph.D. candidate in the School of Computer Science and Technology at Huazhong University of Science and Technology (HUST), Wuhan. His research interests include computer architecture and graph neural networks.

Hai Jin is a chair professor of computer science and engineering at Huazhong University of Science and Technology (HUST), Wuhan. Jin received his Ph.D. degree in computer engineering from HUST, Wuhan, in 1994. In 1996, he was awarded a German Academic Exchange Service Fellowship to visit the Technical University of Chemnitz, Straße der Nationen. Jin worked at The University of Hong Kong, Hong Kong, between 1998 and 2000, and as a visiting scholar at the University of Southern California, Los Angeles, between 1999 and 2000. He was awarded Excellent Youth Award from the National Natural Science Foundation of China in 2001. He has co-authored 22 books and published over 900 research papers. His research interests include computer architecture, virtualization technology, distributed computing, big data processing, network storage, and network security.

Peng-Cheng Yao received his Ph.D. degree in computer science and technology from the Huazhong University of Science and Technology, Wuhan, in 2022. He is now a postdoctoral fellow at Zhejiang Lab, Hangzhou. His research interests include graph processing and domain specific accelerator.

Yu Huang received his Ph.D. degree in computer science and technology from the Huazhong University of Science and Technology (HUST), Wuhan, in 2022. He is now a postdoctoral fellow at Zhejiang Lab, Hangzhou. His research focuses on computer architecture, graph processing, and processing in memory.

Qing-Gang Wang received his Ph.D. degree in computer science and technology from the Huazhong University of Science and Technology (HUST), Wuhan, in 2023. He is now a postdoctoral fellow at Zhejiang Lab, Hangzhou. His current research interests include graph processing and reconfigurable computing.

Jin Zhao received his Ph.D. degree in computer science from the Huazhong University of Science and Technology (HUST), Wuhan, in 2022. He is now a postdoctoral fellow at Zhejiang Lab, Hangzhou. His research focuses on computer architecture, system software, runtime optimization, programming model, and big data processing.

Long Zheng received his Ph.D. degree in computer science and technology from the Huazhong University of Science and Technology (HUST), Wuhan, in 2016. He is currently an associate professor with the School of Computer Science and Technology, HUST, Wuhan. His current research interests include program analysis, runtime systems, and heterogeneous computing with a particular focus on graph processing.

Yu Zhang received his Ph.D. degree in computer science from the Huazhong University of Science and Technology (HUST), Wuhan, in 2016. His research focuses on computer architecture and system, runtime optimization, programming model, and big data processing.

Zhi-Yuan Shao received his Ph.D. degree in computer science and technology from Huazhong University of Science and Technology (HUST), Wuhan, in 2005. He is now a professor of computer science and engineering at HUST in Wuhan. His research interests are in the areas of graph computing, computing system, and big-data processing.

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Liao, XF., Zhao, WJ., Jin, H. et al. Towards High-Performance Graph Processing: From a Hardware/Software Co-Design Perspective. J. Comput. Sci. Technol. 39, 245–266 (2024). https://doi.org/10.1007/s11390-024-4150-0

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