Dr. Cheng Ling

Office Address

Room 402 ,Computer building, Beijng University of Chemical Technology

Mailing Address

Mail Box 4, No. 15 Beisanhuan East Road, Chaoyang District, Beijing 100029, P.R. China





Research Interests

1.High-performance computing on computational biology and bioinformatics
2.Deep learning on CUDA GPU

Working/Education Experience

2005 – 2007 Shenzhen University, undergraduate courses;
2007 – 2008 University of Central Lancashire, B.Eng;
2008 – 2012 Edinburgh University, Ph.D;
2013 – 2015 Postdoctoral Researcher, Department of Computer Science and Technology, Tsinghua University;

Teaching Courses

C programming;


Guangzhou Scientific Research Program (No. 2014J4100081)


1.Ling C., Hamada T., Gao J., et al. (2015)MrBayes tgMC3++: a High Performance and Resource-Efficient GPU-oriented Phylogenetic Analysis Method.
IEEE/ACM transactions on computational biology and bioinformatics, doi:10.1109/TCBB.2015.2495202.
2.Ling C., Hamada T., Zhao G., Zhu X., et al. (2015) Optimizing the Bayesian Inference of Phylogeny on Graphic Processors. In proceedings of the 15th IEEE/ACM symposium on Cluster, Cloud and Grid Computing (IEEE CCGrid), pp.333-342.
3.Zhao G., Ling C. (2015) SparkSW: Scalable Distributed Computing System for Large-Scale Biological Sequence Alignment. In proceedings of the 15th IEEE/ACM symposium on Cluster, Cloud and Grid Computing (IEEE CCGrid), pp.845-852.
4.Ling C., Hamada T., Bai J., et al. (2013)MrBayes tgMC3: a tight GPU implementation of MrBayes. PLoS ONE, 8(4): e60667.
5.Ling C., Benkrid K., Hamada T. (2012) High performance Phylogenetic Analysis on CUDA-compatible GPUs. Computer Archtecture News, 40(5):52-57.
6.Ling C., Benkrid K. (2011) High performance Intra-task parallelization of Multiple Sequence Alignments on CUDA-compatible GPUs. NASA/ESA Conference on Adaptive Hardware and Systems (AHS), pp.360-366.
7.Ling C., Benkrid K. (2010) Design and implementation of a CUDA-compatible GPU-based core for gapped BLAST algorithm. Procedia Computer Science, 1(1):495-504.
8.Ling C., Benkrid K. (2009) A parameterisable and scalable Smith-Waterman algorithm implementation on CUDA-compatible GPUs. In proceedings of the 7th IEEE Symposium on Application Specific Processor (IEEE SASP), pp.94-100.