Center for High Performance Computing


Center for High Performance Computing Technology focuses on High performance data processing technology which carries out technical research on urban computing, multimedia computing, biological computing, figure calculation and other aspects. The results of the research have been widely applied in the fields of intelligence meteorology, intelligent transportation, new media, biological medicine, and so on. We have cooperated with Shenzhen Meteorological Bureau, Skyworth, BGI and other enterprises and institutions. 

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Main Research Projects

Research direction 

High performance data processing technology 

multimedia computing  

urban computing, , 

biological computing,  

graph computing 


Technical Achievements 

Development and Application of State Assessment System for Urban Power Network based on the Big Data analysis 

According to the power grid, equipment and environmental information, this project is aiming at the research on dynamic evaluation of urban power grid transmission capacity, state evaluation, failure prediction, operation risk assessment, aid decision-making and related key technologies with the basis of big data analysis. At the meantime, this research is applied in the construction of the state evaluation system for the large urban power grid equipment, to improve the safety operation level of the power grid and equipment.  


Large-scale meteorological data processing and weather nowcast system: 

We have provided real-time meteorological data assimilation, severe weather nowcast, and customized service for Shenzhen Meteorology Bureau (SZMB). The research work of quantitative wind and rainfall estimation due to tropical cyclones has been incorporated into the Tropical Cyclones Integrated Operational Platform of SZMB, and has been frequently used in the meteorological information bulletin and weather consultation during typhoon season.  


3D video technology, Virtual Reality 

3D video processing and compression research has been conducted based on high-performance computing platform and optimization theory, with the goal to solve processing, storage, transmission, video quality assessment and other 3D video related issues. Video coding and visual perception are combined to extract human visual redundancy effectively, thus having improved the efficiency of video compression and enhanced the compression efficiency by 30%. In terms of application, An ultra-high-definition 3D live video and on-demand system have been developed.  And until now we have cooperated with enterprises in video, such as Skyworth, Phoenix Media and TEMOBI. 


Highly efficient analysis of genomic data at TB - PB scale  

A highly scalable genome assembly algorithm SWAP-Assembler was developed based on an asynchronous graph computing framework. Compared with the state-of-the-art tools such as Abyss, the analysis speed of is the fastest. The software is open sourced and has been downloaded about 500 times worldwide. 

Spatial-temporal Analysis Based On Large-scale Data  

Based on the spatiotemporal data collected by increasingly emerging sensors such as mobile phones, social media, and Internet of things as well as the high-performance computing technology, we focus on analyzing human spatiotemporal activity patterns in the information age, modeling spatiotemporal phenomena, and simulating spatiotemporal processes. Our research can help breakthrough the limitation of lacking large-scale human activity data sources for decades, and can offer critical methods and technologies for various application areas such as smart transportation, urban planning, public health, mobile Internet service, and big data service in a more general word. 


Online Algorithm 

Online Merchandise Sale: 

A high performance on-line algorithm is proposed for On-line Merchandise Sale, we also prove the lower bounds of performance that any algorithm cannot achieve 

Online code allocation:
A high performance on-line algorithm is proposed for code allocation. 

Online bin packing: 

A high performance on-line algorithm is proposed for two-dimensional bin packing problem. 

A Tensor Learning and DTI based CAD system 

Presenting a tensor-based classification for DTI data, which can realize the maximum separability of the target images and can largely reduce the algorithm computation complexity as well as can improve the robustness of algorithm. Consequently, it supports DTI based Intelligent CAD theory evidence and core algorithm.   

Intelligence and Automation car parking management system 

Research an Intelligence and Automation car parking management system based on the technology of Internet of Things. This system can effectively capture the temporary parking information on the roadside, and manage the parking behavior effectively. We carry out technical research and demonstration application of occupancy detection, data transmission, systems operation, data management and analysis platform.


  • FAN Jianping

    Areas of Interest:supercomputers

  • FENG Shengzhong

    Areas of Interest:high performance computing

  • WANG Shuqiang

    Title:Associate Professor
    Areas of Interest:

  • LING Yin

    Title:Associate Professor
    Areas of Interest:

  • ZHANG Yong

    Title:Associate Professor
    Areas of Interest:

  • ZHANG Yun

    Title:Associate Professor
    Areas of Interest:

  • LI Qinglan

    Areas of Interest:climate change

  • WEI Yanjie

    Areas of Interest:BMC Bioinformatics