Wu-chun Feng

Wu-chun Feng (a.k.a. "Wu")

SyNeRGy Laboratory

Dept. of CS
Dept. of ECE
Health Sciences

Other Affiliations
Wireless @ VT

Google Scholar


Torgersen Hall 2050
620 Drillfield Drive (Alumni Mall)
Blacksburg, VA.
24061. [map]
(540) 231-1192
(540) 231-9218
feng [at] cs.vt.edu

Virginia Tech


For electronic version of publications please visit the Synergy Lab. web site.

  • IterML: Iterative Machine Learning for Intelligent Parameter Pruning and Tuning in Graphics Processing Units.
    Xuewen Cui, Wu-chun Feng.
    In Journal of Signal Processing Systems, 93 (1): 391-403, April 2021.
  • MetaCL: Automated 'Meta' OpenCL Code Generation for High-Level Synthesis on FPGA.
    Paul Sathre, Atharva Gondhalekar, Mohamed Hassan, Wu-chun Feng.
    In Proceedings of the IEEE High Performance Extreme Computing Conference (HPEC), Waltham, MA, September 2020.
  • Exploring FPGA Optimizations in OpenCL for Breadth-First Search on Sparse Graph Datasets.
    Atharva Gondhalekar, Wu-chun Feng.
    In Proceedings of the 30th International Conference on Field-Programmable Logic and Applications, Gothenburg, Sweden, September 2020.
  • A Deep-Learning Neural Network Based Reconstruction Algorithm for Sparse-View CT.
    Isaiah Herrera, Prathamesh Mandke, Wu-chun Feng, Guohua Cao.
    In Joint American Association of Physicists in Medicine | Canadian Organization of Medical Physicists Annual Scientific Meeting, Vancouver, British Columbia, Canada, July 2020.
  • ETH: An Architecture for Exploring the Design Space of In-situ Scientific Visualization.
    Gregory Abram, Vignesh Adhinarayanan, Wu-chun Feng, David Rogers, James Ahrens.
    In Proceedings of the 34th IEEE International Parallel and Distributed Processing Symposium, New Orleans, Louisiana USA, May 2020.
  • SparkLeBLAST: Scalable Parallelization of BLAST Sequence Alignment Using Spark.
    Karim Youssef, Wu-chun Feng.
    In Proceedings of the 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid), Melbourne, Victoria, Australia, May 2020.
  • Alleviating Load Imbalance in Data Processing for Large-Scale Deep Learning.
    Sarunya Pumma, Daniele Buono, Fabio Checconi, Xinyu Que, Wu-chun Feng.
    In Proceedings of the 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, Melbourne, Australia, May 2020.

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