(PhD, HKUST, 2003)
ProfessorDepartment of Computer Science Hong Kong Baptist University
Kowloon Tong, Kowloon, HONG KONG Tel: +852 3411 5998 FAX: +852 3411 7892 E-mail: firstname.lastname@example.org, or email@example.com Homepage: http://www.comp.hkbu.edu.hk/~chxw/index.htm
Chu received his B.Eng. degree in the Computer Science from Tsinghua University, Beijing, P. R.
China, in 1999, and the Ph.D. degree in the Computer Science from the Hong Kong University of Science and Technology
in 2003. He is a professor in the Department
of Computer Science, Hong Kong Baptist
University. He is serving as the Director of the High Performance Cluster Computing
Centre of HKBU. He is a senior member of IEEE.
Post-doctoral Research Fellow in High Performance Deep Learning
A Postdoctoral position is immediately available in the Department of Computer Science at Hong Kong Baptist University, Hong Kong. Applicants should possess a PhD Degree in computer science, computer engineering, or a related field, and sufficiently demonstrate abilities to conduct high-quality research in the area of high performance deep learning. Initial duration of this position is 12 months, and is renewable subject to satisfactory performance and mutual agreement. We offer a competitive salary and benefits package. Hong Kong practises a . Interested applicants are invited to send a CV to Dr. Xiaowen Chu by email (firstname.lastname@example.org). The position remains open until it is filled.
Research Assistant / Senior Research Assistant in High Performance Deep Learning
Research assistant positions are immediately available in the Department of Computer Science at Hong Kong Baptist University, Hong Kong. Applicants should possess a Bachelor Degree (or equivalent) in computer science, computer engineering, or a related field. R&D experience in any of the following areas is considered as a plus: (i) GPU computing, (ii) Deep learning, (iii) Network performance modelling. Initial duration of this position is 12 months, and is renewable subject to satisfactory performance and mutual agreement. We offer a competitive salary and benefits package. Interested applicants are invited to send a CV to Dr. Xiaowen Chu by email (email@example.com). The position remains open until it is filled.
[10 May 2019] The paper “A Convergence Analysis of Distributed SGD with Communication-Efficient Gradient Sparsification” has been accepted by IJCAI 2019. Congratulations to SHI Shaohuai, ZHAO Kaiyong, WANG Qiang, and TANG Zhenheng!
[12 April 2019] The notes paper “The Impact of GPU DVFS on the Energy and Performance of Deep Learning: an Empirical Study” has been accepted by ACM e-Energy 2019. Congratulations to TANG Zhenheng, WANG Yuxin, and WANG Qiang!
[29 March 2019] The paper “A Distributed Synchronous SGD Algorithm with Global Top-k Sparsification for Low Bandwidth Networks” has been accepted by IEEE ICDCS 2019 workshop program. Congratulations to SHI Shaohuai and all team members!
[30 November 2018] The paper “MG-WFBP: Efficient Data Communication for Distributed Synchronous SGD Algorithms” has been accepted by IEEE INFOCOM 2019. Congratulations to SHI Shaohuai!
[12 August 2018] The paper “Performance Modeling and Evaluation of Distributed Deep Learning Frameworks on GPUs” has received the Best Paper Award of IEEE DataCom 2018. Congratulations to SHI Shaohuai and WANG Qiang!
[May 2018] HKBU ASC18 team won the First Class Award in the Student Supercomputer Challenge 2018. Congratulations to our students Ni Ronghao, Wang Shihao, Feng Zijin, Wang Haixin and Wong Tsz Shing! [Report by HPCWire].
[23 Dec 2017] The paper “G-CRS: GPU Accelerated Cauchy Reed-Solomon Coding” has been accepted by IEEE TPDS. Our source code and data sets can be found here. Congratulations to LIU Chengjian!
[Sept 2017] The paper “GPGPU Power Estimation with Core and Memory Frequency Scaling” has been published by ACM SIGMETRICS Performance Evaluation Review. Congratulations to WANG Qiang!
[18 May 2017] We have two papers accepted by ACM e-Energy 2017. The paper “EPPMiner: An Extended Benchmark Suite for Energy, Power and Performance Characterization of Heterogeneous Architecture” is one of the Best Paper Candidates. Congratulations to WANG Qiang!
[28 April 2017] HKBU ASC17 team won the First Class Award. Congratulations to our undergraduate students Wang Shihao (Year 2), Zou Xueyan and Cheong Chin-wang (Year 3), Wei Wenzhou and Ho Chun-san (Year 4)! [Report by HPCWire and Report by HKBU].
[24 February 2017] We have received an NVIDIA GPU Grant.
[26 November 2016] The paper “Energy Efficient Real-time Task Scheduling on CPU-GPU Hybrid Clusters” has been accepted by IEEE INFOCOM 2017. Congratulations to MEI Xinxin! My presentation at INFOCOM 2017 received the "Best-in-Session-Presentation" award.
[September 2016] We have launched the project of “Benchmarking State-of-the-art Deep Learning Software Tools”.
[22 August 2016] Our work about an autonomous vehicle public transportation system has been reported by IEEE Xplore Innovation Spotlight.
[18 June 2016] HKUST CSE Alumni Homecoming Workshop 2016 on Big Data and Deep Learning was successfully held. I gave a presentation of A tale of two cities: GPU computing and machine learning, and you can download the PowerPoint slides here.
[18-22 April 2016] HKBU ASC16 team won the First Class Award and Most Popular Team Award. Congratulations to our students Xu Pengfei, Ting Hoshing, Cheng Guanlun, Du Jiangyang and Ho Chun-san! [Report by HPCWire and Report by HKBU].
[26 March 2016] The paper "Dissecting GPU Memory Hierarchy through Microbenchmarking" has been accepted by IEEE TPDS. Our source code and data sets can be found here. Congratulations to Mei Xinxin!
[1 August 2015] The paper "R-Memcached: a Reliable In-Memory Cache System for Big Key-Value Stores" has received the Best Paper Award of BigCom 2015. Congratulations to Liu Chengjian!
[24 March 2015] The paper "Community-based Bus System as Routing Backbone for Vehicular Ad Hoc Networks" has been accepted by ICDCS 2015.
[17 Nov 2014] The paper "Online Procurement Auctions for Resource Pooling in Client-Assisted Cloud Storage Systems" has been accepted by IEEE INFOCOM 2015.
[23 April 2014] The paper "Accelerating the Scoring Module of Mass Spectrometry-Based Protein Identification Using GPUs" has been accepted by BMC Bioinformatics. Congratulations to Li You!
[23 Feb 2014] The paper "Dissecting Darknets: Measurement and Performance Analysis" has been accepted by ACM Transactions on Internet Technology. Congratulations to Chen Xiaowei!
[25 Jan 2014] The paper "G-BLASTN: Accelerating Nucleotide Alignment by Graphics Processors" has been published online in Bioinformatics. Congratulations to Zhao Kaiyong!
[22 Aug 2013] G-BLASTN 1.0 Released!
G-BLASTN is a GPU-accelerated nucleotide alignment tool based on the widely used NCBI-BLAST. It can produce exactly the same results as NCBI-BLAST. In comparison to the multithreaded NCBI-BLAST on Intel Core i7-3820 (quad-core, 3.6GHz), G-BLASTN can achieve an average of 7X speedup for masked human and mouse genome databases using a single NVIDIA GTX780 card.