My complete and updated publication list can be found at Google Scholar or DBLP . The below publications are before 2021.
My complete and updated publication list can be found at Google Scholar or DBLP . The below publications are before 2021.
S. Zhang, Z. Wang, Q. Wang, J. Zhang, G. Wei, and X.-W. Chu, “EDNet: Efficient Disparity Estimation with Cost Volume Combination and Attention-based Spatial Residual,” CVPR 2021. [PrePrint]
Q. Wang, S. Zheng, Q. Yan, F. Deng, K. Zhao, and X.-W. Chu, “IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation,” ICME 2021. [PrePrint]
S. Shi, X.-W. Chu, and B. Li, “MG-WFBP: Merging Gradients Wisely for Efficient Communication in Distributed Deep Learning,” IEEE Transactions on Parallel and Distributed Systems, Vol. 32, No. 8, Pages 1903-917, Aug 2021.
W. Yang, Y. Qin, Z. Jiang, and X.-W. Chu, “Traffic Management for Distributed Machine Learning in RDMA-enabled Data Center Networks,” IEEE ICC 2021. [PrePrint]
S. Shi, X.-W. Chu, and B. Li, “Exploiting Simultaneous Communications to Accelerate Data Parallel Distributed Deep Learning,” IEEE INFOCOM 2021. [PrePrint] (Best Paper Award)
X. He, S. Wang, X.-W. Chu, S. Shi, J. Tang, X. Liu, C. Yan, J. Zhang, and G. Ding, “Automated Model Design and Benchmarking of Deep Learning Models for COVID-19 Detection with Chest CT Scans,” AAAI 2021. [PrePrint]
X. He, K. Zhao, and X.-W. Chu, “AutoML: A Survey of the State-of-the-Art,” Knowledge-Based Systems, Vol. 215, Jan 2021.
S. Shi, Z. Tang, X.-W. Chu, C. Liu, W. Wang, and B. Li, “A Quantitative Survey of Communication Optimizations in Distributed Deep Learning,” IEEE Network, to appear. [PrePrint]
Y. Wang, Q. Wang, and X.-W. Chu, “Energy-efficient Inference Service of Transformer-based Deep Learning Models on GPUs,” IEEE GreenCom 2020, Greece, 2020. (Best Paper Award)
R. Zeng, S. Zhang, J. Wang, and X.-W. Chu, “FMore: An Incentive Scheme of Multi-dimensional Auction for Federated Learning in MEC,” IEEE ICDCS 2020, Singapore, 2020. [PrePrint]
Z. Tang, S. Shi, and X.-W. Chu, “Communication-Efficient Decentralized Learning with Sparsification and Adaptive Peer Selection,” IEEE ICDCS 2020 (Poster), Singapore, 2020. [Long Version]
Y. Wang, Q. Wang, S. Shi, X. He, Z. Tang, K. Zhao, X.-W. Chu, “Benchmarking the Performance and Power of AI Accelerators for AI Training,” 3rd High Performance Machine Learning Workshop (HPML 2020), co-located with IEEE CCGrid 2020, Melbourne, Australia, 2020. [PrePrint]
S. Shi, Z. Tang, Q. Wang, K. Zhao, and X.-W. Chu, “Layer-wise Adaptive Gradient Sparsification for Distributed Deep Learning with Convergence Guarantees,” The 24th European Conference on Artificial Intelligence (ECAI), Santiago de Compostela, Spain, June 2020. [PrePrint]
Q. Wang, S. Shi, S. Zheng, K. Zhao, and X.-W. Chu, “FADNet: A Fast and Accurate Network for Disparity Estimation,” IEEE ICRA 2020, Paris, France, May-June 2020. [PrePrint]
D. Yan, W. Wang, and X.-W. Chu, “Demystifying Tensor Cores to Optimize Half-Precision Matrix Multiply,” IEEE IPDPS 2020, New Orleans, USA, May 2020. [PrePrint]
S. Shi, Q. Wang, X-W. Chu, B. Li, Y. Qin, R. Liu, and X. Zhao, “Communication-Efficient Distributed Deep Learning with Merged Gradient Sparsification on GPUs,” IEEE INFOCOM 2020, Beijing, China, May 2020. [PrePrint]
D. Yan, W. Wang, and X.-W. Chu, “Optimizing Batched Winograd Convolution on GPUs,” ACM PPoPP 2020, San Diego, USA, Feb 2020. [GitHub]
Z. Sun, X. Zhang, Y. Ye, X.-W. Chu, and Z. Liu, “A Probabilistic Approach towards an Unbiased Semi-supervised Cluster Tree,” Knowledge-Based Systems, Dec 2019.
X. Zhou, Z. Tang, W. Xu, F. Meng, X.-W. Chu, K. Xin, and G. Fu, “Deep learning Identifies Burst Locations in Water Distribution Networks,” Water Research, Vol. 166, Dec 2019.
S. Shi, K. Zhao, Q. Wang, Z. Tang, and X.-W. Chu, “A Convergence Analysis of Distributed SGD with Communication-Efficient Gradient Sparsification,” IJCAI 2019, Macau, P.R.C., August 2019. [PDF]
Z. Tang, Y. Wang, Q. Wang, and X.-W. Chu, “The Impact of GPU DVFS on the Energy and Performance of Deep Learning: an Empirical Study,” ACM e-Energy 2019, Phoenix, AZ, USA, June 2019. (notes paper) [PrePrint]
S. Shi, Q. Wang, K. Zhao, Z. Tang, Y. Wang, X. Huang, and X.-W. Chu, “A Distributed Synchronous SGD Algorithm with Global Top-k Sparsification for Low Bandwidth Networks,” IEEE ICDCS 2019, Dallas, Texas, USA, July 2019. [arXiv:1901.04359].
S. Shi, X.-W. Chu, and B. Li, “MG-WFBP: Efficient Data Communication for Distributed Synchronous SGD Algorithms,” IEEE INFOCOM 2019, Paris, France, May 2019. [PrePrint]
X. Jia, S. Song, S. Shi, W. He, Y. Wang, H. Rong, F. Zhou, L. Xie, Z. Guo, Y. Yang, L. Yu, T. Chen, G. Hu, and X.-W. Chu, “Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes,” NeurIPS Workshop on Systems for ML and Open Source Software, Montreal, Canada, Dec 2018. [PDF]
S. Shi, Q. Wang, X.-W. Chu, and B. Li, “A DAG Model of Synchronous Stochastic Gradient Descent in Distributed Deep Learning,” IEEE International Conference on Parallel and Distributed Systems (ICPADS) 2018, Singapore, Dec 2018.
S. Shi, Q. Wang, and X.-W. Chu, “Performance Modeling and Evaluation of Distributed Deep Learning Frameworks on GPUs,” IEEE DataCom 2018, Athens, Greece, August 2018. (Best Paper Award)
S. Shi, P. Xu, and X.-W. Chu, “Supervised Learning Based Algorithm Selection for Deep Neural Networks,” IEEE ICPADS 2017, Shenzhen, China, Dec 2017.
P. Xu, S. Shi, and X.-W. Chu, “Performance Evaluation of Deep Learning Tools in Docker Containers,” the 3rd International Conference on Big Data Computing and Communications, Chengdu, China, Aug 2017.
S. Shi, Q. Wang, P. Xu, and X.-W. Chu, “Benchmarking State-of-the-Art Deep Learning Software Tools,” the 7th International Conference on Cloud Computing and Big Data (CCBD 2016), Macau, China, Nov 2016. [Long version at https://arxiv.org/abs/1608.07249]
L. Yu, Y.-W. Leung, X.-W. Chu, and J. Ng, “Multi-Fingerprint for Wireless Localization in Time-Varying Indoor Environment,” IEEE Globecom 2020, Dec 2020.
S. Qiu, X.-W. Chu, Y.-W. Leung, and J. Ng, “Joint Access Point Placement and Power-Channel-Resource-Unit Assignment for 802.11ax-Based Dense WiFi with QoS Requirements,” IEEE INFOCOM 2020, Beijing, China, May 2020. [PrePrint]
L. Yu, Y.-W. Leung, X.-W. Chu, and J. K. Y. Ng, “Minimal Discrepancy Placement of Sniffers and Calibrators for Wireless Indoor Localization,” IEEE PIMRC 2019, Istanbul, Turkey, Sept. 2019.
Z. Lin, H. Liu, L. Yu, Y.-W. Leung, and X.-W. Chu, “ZOS: A Fast Rendezvous Algorithm Based on Set of Available Channels for Cognitive Radios,” IEEE PIMRC 2018, Bologna, Italy, Sept. 2018.
O. Oshiga, X.-W. Chu, Y.-W. Leung, and J. Ng, “Anchor Selection for Localization in Large Indoor Venue,” IEEE/ACM 26th International Symposium on Quality of Service (IWQoS), Banff, Canada, June 2018.
L. Yu, H. Liu, Y.-W. Leung, X.-W. Chu, and Z. Lin, “Cooperative Rendezvous Protocol for Multiple User-Pairs in Cognitive Radio Networks,” IEEE Wireless Communications and Networking Conference, Barcelona, Spain, April 2018.
F. Zhang, H. Liu, Y.-W. Leung, X.-W. Chu, and B. Jin, “CBS: Community-based Bus System as Routing Backbone for Vehicular Ad Hoc Networks,” IEEE Transactions on Mobile Computing, Vol. 16, No. 8, pages 2132-2146, August 2017.
F. Zhang, B. Jin, H. Liu, Y.-W. Leung, and X.-W. Chu, “Minimum-Cost Recruitment of Mobile Crowdsensing in Cellular Networks,” IEEE Globecom 2016, Washington, USA, 4-8 December, 2016.
L. Zhang, C. Zhang, J. Liu, X.-W. Chu, K. Xu, and H. Wang, “Power-Aware Wireless Transmission for Computation Offloading in Mobile Cloud,” IEEE ICCCN 2016, Hawaii, USA, 1-4 August, 2016.
Y. Lu, H. Liu, Y.-W. Leung, X.-W. Chu, and Z. Lin, “Adjustable Rendezvous in Multi-Radio Cognitive Radio Networks,” IEEE Globecom 2015, San Diego, CA, USA, 6-10 December, 2015.
Z. Lin, H. Liu, X.-W. Chu, Y.-W. Leung, and I. Stojmenovic, “Constructing Connected-Dominating-Set with Maximum Lifetime in Cognitive Radio Networks,” IEEE Transactions on Computers, to appear. [PDF]
L. Yu, H. Liu, Y.-W. Leung, X.-W. Chu, and Z. Lin, “Multiple Radios for Fast Rendezvous in Cognitive Radio Networks,” IEEE Transactions on Mobile Computing, Vol. 14, No. 9, pages 1917-1931, September 2015. [PDF]
F. Zhang, H. Liu, Y.-W. Leung, X.-W. Chu, and B. Jin, “Community-based Bus System as Routing Backbone for Vehicular Ad Hoc Networks,” IEEE ICDCS 2015, Hilton Downtown, Columbus, Ohio, USA, 29 Jun.-2 Jul., 2015. [PDF] (Acceptance rate = 12.9%)
L. Yu, H. Liu, Y.-W. Leung, X.-W. Chu, and Z. Lin, “Channel-Hopping Based on Available Channel Set for Rendezvous of Cognitive Radios,” IEEE ICC 2014, Sydney, Australia, 10-14 June, 2014. [PDF]
H. Liu, X.-W. Chu, Y.-W. Leung, and R. Du, “Minimum-Cost Sensor Placement for Required Lifetime in Wireless Sensor-Target Surveillance Networks,” IEEE Transactions on Parallel and Distributed Systems, Vol. 24, No. 9, pp.1783-1796, September 2013.
Z. Lin, H. Liu, X.-W. Chu, and Y.-W. Leung, “Enhanced Jump-Stay Rendezvous Algorithm for Cognitive Radio Networks,” IEEE Communications Letters, Vol. 17, No. 9, Page 1742-1745, September 2013.
Gary K.W. Wong, H. Liu, X.-W. Chu, Y.-W. Leung, and C. Xie, “Efficient Broadcasting in Multi-hop Wireless Networks with A Realistic Physical Layer,” Ad Hoc Networks, Vol. 11, No. 4, pages 1305-1318, June 2013.
L. Yu, H. Liu, Y.-W. Leung, X.-W. Chu, and Z. Lin, “Multiple Radios for Effective Rendezvous in Cognitive Radio Networks,” IEEE ICC 2013, Budapest, Hungary, 9-13 June, 2013. [PDF]
H. Liu, Z. Lin, X.-W. Chu, and Y.-W. Leung, “Jump-Stay Rendezvous Algorithm for Cognitive Radio Networks,” IEEE Transactions on Parallel and Distributed Systems, Vol. 23, No. 10, pages 1867-1881, Oct 2012. (Spotlight Paper of the issue)
Z. Lin, H. Liu, X.-W. Chu, and Y.-W. Leung, “Ring-Walk Rendezvous Algorithms for Cognitive Radio Networks,” Ad Hoc & Sensor Wireless Networks, Vol. 16, No. 4, pages 243-271, 2012.
H. Liu, Y. Zhou, X.-W. Chu, Y.-W. Leung, and Z. Hao, “Generalized-Bi-Connectivity for Fault Tolerant Cognitive Radio Networks,” IEEE ICCCN 2012, Munich, Germany, July-August 2012.
Z. Lin, H. Liu, X.-W. Chu, Y.-W. Leung, and I. Stojmenovic, “Maximizing Lifetime of Connected-Dominating-Set in Cognitive Radio Networks,” IFIP Networking 2012, Prague, Czech Republic, 21-25 May. 2012.
H. Liu, Z. Lin, X.-W. Chu, and Y.-W. Leung, “Taxonomy and Challenges of Rendezvous Algorithms in Cognitive Radio Networks,” The International Conference on Computing, Networking and Communications (ICNC 2012), Maui, Hawaii, USA, 30 Jan.-2 Feb. 2012. (Invited Position Paper)
H. Liu, X.-W. Chu, Y.-W. Leung, X. Jia, and P.-J. Wan, “General Maximal Lifetime Sensor-Target Surveillance Problem and Its Solution,” IEEE Transactions on Parallel and Distributed Systems, Vol. 22, No. 10, pages 1757-1765, Oct. 2011.
Z. Lin, H. Liu, X.-W. Chu, and Y-W. Leung, “Jump-Stay Based Channel-Hopping Algorithm with Guaranteed Rendezvous for Cognitive Radio Networks,” IEEE INFOCOM 2011, Shanghai, China, 10-15 Apr. 2011. (Acceptance rate = 15.9%)
H. Liu, Z. Lin, X.-W. Chu, and Y-W. Leung, “Ring-Walk Based Channel-Hopping Algorithms with Guaranteed Rendezvous for Cognitive Radio Networks,” The 2nd IEEE International Workshop on Wireless Sensor, Actuator and Robot Networks (WiSARN2010-FALL), in conjunction with IEEE/ACM CPSCom, Hangzhou, China, 18-20 Dec. 2010. (Invited Paper)
H. Liu, X.-W. Chu, Y.-W. Leung, and R. Du, “Simple Movement Control Algorithm for Bi-Connectivity in Robotic Sensor Networks,” IEEE Journal on Selected Areas in Communications, Vol. 28, No. 7, pages. 994-1005, Sept 2010.
H. Liu, X.-W. Chu, Y. W. Leung, X. Jia, and P. J. Wan, “Maximizing Lifetime of Sensor-Target Surveillance in Wireless Sensor Networks,” IEEE Globecom 2009, Dec. 2009.
X.-Y. Li, Y. Wu, H. Chen, X.-W. Chu, Y. Wu, and Y. Qi, “Reliable and Energy Efficient Routing for Static Wireless Ad Hoc Networks with Unreliable Links,” IEEE Transactions on Parallel and Distributed Systems, Vol. 20, no. 10, pp. 1408-1421, Oct. 2009.
X.-Y. Li, A. Nusairat, Y. Wu, Y. Qi, J. Zhao, X.-W. Chu, and Y. Liu, “Joint Throughput Optimization for Next Generation Wireless Mesh Networks,” IEEE Transactions on Mobile Computing, Vol. 8, No. 7, pages 895-909, July 2009.
X.-W. Chu, Y. Sun, K. Xu, Z. Sakendar, and J. Liu, “Quadratic Residue Based Address Allocation for Mobile Ad Hoc Networks,” IEEE ICC’08, Beijing, China, May 2008. [PDF]
Y. Yan and X.-W. Chu, “An Analytical Model for IEEE 802.11 Point-to-Point Link,” IEEE ICC’08, Beijing, China, May 2008. [PDF]
X.-W. Chu, “Provisioning of Parameterized Quality of Service in 802.11e Based Wireless Mesh Networks,” ACM/Springer MONET, Vol. 13, No.1-2, pages 6-18, April 2008. [PDF]
Y. Jiang, C. Lin, M. Shi, X. Shen, and X.-W. Chu , “A DoS and Fault Tolerant Authentication Protocol for Group Communications in Ad Hoc Networks,” Computer Communications, Vol. 30, Nos. 11/12, pp. 2428-2441, September 2007.
X.-Y. Li, Y. Shu, H. Chen, X.-W. Chu, and Y. Wu, “Energy Efficient Routing with Unreliable Links in Wireless Networks,” The Third IEEE International Conference on Mobile Ad-hoc and Sensor Systems (MASS 2006), 2006.
Z. Peng, C. Xu, H. Wang, J. Huang, J. Xu, and X.-W. Chu, “P2B-Trace: Privacy-Preserving Blockchain-based Contact Tracing to Combat Pandemics,” SIGMOD 2021.
Z. Peng, J. Xu, X.-W. Chu, S. Gao, Y. Yao, and R. Gu, “VFChain: Enabling Verifiable and Auditable Federated Learning via Blockchain Systems,” IEEE Transactions on Network Science and Engineering, to appear.
C. Liu, Q. Wang, X.-W. Chu, Y.-W. Leung, and H. Liu, “ESetStore: An Erasure-Coded Storage System with Fast Data Recovery,” IEEE Transactions on Parallel and Distributed Systems, Vol. 31, No. 19, pages 2001-2016, September 2020.
H. Zhao, H. Liu, Y.-W. Leung, and X.-W. Chu, “Self-Adaptive Collective Motion of Swarm Robots,” IEEE Transactions on Automation Science and Engineering, Vol. 15, No. 4, pages 1533-1545, October 2018.
L. Ma, H. Liu, Y.-W. Leung, and X.-W. Chu, “Joint VM-Switch Consolidation for Energy Efficiency in Data Centers,” IEEE Globecom 2016, Washington, USA, 4-8 December, 2016.
Albert Y.S. Lam, Y.-W. Leung, and X.-W. Chu, “Autonomous Vehicle Public Transportation System: Scheduling and Admission Control,” IEEE Transactions on Intelligent Transportation Systems, Vol. 17, No. 5, pages 1210-1226, May 2016.
S. Fu, J. Liu, X.-W. Chu, and Y. Hu, “Toward a Standard Interface for Cloud Providers: The Container as the Narrow Waist,” IEEE Internet Computing, Vol. 20, No. 2, pages 66-71, March-April 2016.
C. Liu, K. Ouyang, X.-W. Chu, H. Liu, and Y.-W. Leung, “R-Memcached: a Reliable In-Memory Cache System for Big Key-Value Stores,” Tsinghua Science and Technology, Vol. 20, No. 6, pages 560-573, December 2015.
J. Zhao, X.-W. Chu, H. Liu, Y.-W. Leung, and Z. Li, “Online Procurement Auctions for Resource Pooling in Client-Assisted Cloud Storage Systems,” IEEE INFOCOM 2015, Hong Kong, April-May, 2015.
Albert Y.S. Lam, Y.-W. Leung, and X.-W. Chu, “Electric Vehicle Charging Station Placement: Formulation, Complexity, and Solutions,” IEEE Transactions on Smart Grid, Vol. 5, No. 6, pages 2846–2856, Nov. 2014.
X.-W. Chu, X. Chen, A. L. Jia, J. A. Pouwelse, and D. H. J. Epema, “Dissecting Darknets: Measurement and Performance Analysis,” ACM Transactions on Internet Technology, Vol. 13, No. 3, May 2014.
Z. Li and X.-W. Chu, “On Achieving Group-Strategyproof Multicast,” IEEE Transactions on Parallel and Distributed Systems, Vol. 23, No. 5, pages 913-923, May 2012.
X. Kong, C. Lin, Y. Jiang, W. Yan, and X.-W. Chu, “Efficient Dynamic Task Scheduling in Virtualized Data Centers with Fuzzy Prediction,” Journal of Network and Computer Applications, Elsevier, Vol. 34, No. 4, July 2011, ISSN 1084-8045.
X.-W. Chu and Y. Jiang, “Random Linear Network Coding for Peer-to-Peer Applications,” IEEE Network, Vol. 24, No. 4, pages 35-39, July-August 2010.
X.-W. Chu, K. Zhao, Z. Li, and A. Mahanti, “Auction Based On-Demand P2P Media Streaming with Minimum Cost,” IEEE Transactions on Parallel and Distributed Systems, Vol. 20, No. 12, pages 1816-1829, Dec 2009.
X.-W. Chu, H. Yin, and X.-Y. Li, “Lightpath Rerouting in Wavelength-Routed WDM Networks,” OSA Journal of Optical Networking, Vol. 7, Issue 8, pages 721-735, July 2008.
J. Liu, J. Xu, and X.-W. Chu, “Fine-Grained Scalable Video Caching for Heterogeneous Clients,” IEEE Transactions on Multimedia, Vol. 8, No. 5, pages 1011-1020, October 2006.
X.-W. Chu and B. Li, “Dynamic Routing and Wavelength Assignment in the Presence of Wavelength Conversion for All-Optical Networks,” IEEE/ACM Transactions on Networking, Vol. 12, No. 3, pages 704-715, June 2005.
X.-W. Chu and J. Liu, “DLCR: A New Adaptive Routing Scheme in WDM Mesh Networks,” IEEE International Conference on Communications (ICC'05), pp. 1797-1801, Seoul, Korea, May 2005.
X.-W. Chu, J. Liu, B. Li, and Z. Zhang, “Analytical Model of Sparse-Partial Wavelength Conversion in Wavelength-Routed WDM Networks,” IEEE Communications Letters, Vol. 9, No. 1, pages 69-71, January 2005.
X.-W. Chu, J. Liu, and Z. Zhang, “Analysis of Sparse-Partial Wavelength Conversion in Wavelength-Routed WDM Networks,” IEEE INFOCOM'04, Hong Kong, March 2004.
J. Liu, X.-W. Chu, and J. Xu, “Proxy Cache Management for Fine-Grained Scalable Video Streaming,” IEEE INFOCOM'04, Hong Kong, March 2004.
K. Sohraby, Z. Zhang, X.-W. Chu, and B. Li, “Resource Management in Integrated Optical Networks,” IEEE Journal on Selected Areas in Communications, Vol. 21, No. 7, pages 1052-1062, September 2003.
B. Li, X.-W. Chu, and K. Sohraby, “Routing and Wavelength Assignment vs. Wavelength Converter Placement in All-Optical Networks,” IEEE Communications Magazine, Vol. 41, No. 8, pages S22-S28, August 2003.
X.-W. Chu, B. Li, and I. Chlamtac, “Wavelength Converter Placement under Different RWA Algorithms in Wavelength-Routed All-Optical Networks,” IEEE Transactions on Communications, Vol. 51, No. 4, pages 607-617, April 2003.
X.-W. Chu, B. Li, and Z. Zhang, “A Dynamic RWA Algorithm in a Wavelength-Routed All-Optical Network with Wavelength Converters,” IEEE INFOCOM'03, pages 1795-1804, March 2003.
D. Yan, W. Wang, and X.-W. Chu, “Simplifying Low-Level GPU Programming with GAS,” ACM PPoPP 2021 (Poster), Virtual Conference, Feb-March 2021.
Q. Wang and X.-W. Chu, “GPGPU Performance Estimation with Core and Memory Frequency Scaling,” IEEE Transactions on Parallel and Distributed Systems, Vol. 31, No. 12, pages 2865-2881, Dec 2020.
D. Yan, W. Wang, and X.-W. Chu, “Demystifying Tensor Cores to Optimize Half-Precision Matrix Multiply,” IEEE IPDPS 2020, New Orleans, USA, May 2020. [PrePrint]
D. Yan, W. Wang, and X.-W. Chu, “Optimizing Batched Winograd Convolution on GPUs,” ACM PPoPP 2020, San Diego, USA, Feb 2020. [PDF]
Z. Tang, Y. Wang, Q. Wang, and X.-W. Chu, “The Impact of GPU DVFS on the Energy and Performance of Deep Learning: an Empirical Study,” ACM e-Energy 2019, Phoenix, AZ, USA, June 2019. (notes paper) [PrePrint]
Q. Wang and X.-W. Chu, “GPGPU Performance Estimation with Core and Memory Frequency Scaling,” IEEE International Conference on Parallel and Distributed Systems (ICPADS) 2018, Singapore, Dec 2018. [A poster of this work has been presented at The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC18), Dallas, USA, Nov 2018.]
C. Liu, Q. Wang, X.-W. Chu, and Y.-W. Leung, “G-CRS: GPU Accelerated Cauchy Reed-Solomon Coding,” IEEE Transactions on Parallel and Distributed Systems, Vol. 29, No. 7, pages 1482-1498, July 2018. [PrePrint] [Source Code]
Q. Wang and X.-W. Chu, “GPGPU Power Estimation with Core and Memory Frequency Scaling,” GreenMetrics 2017, in conjunction with ACM Sigmetrics 2017, Urbana-Champaign, IL, USA June 2017. [PDF]
Q. Wang, P. Xu, Y. Zhang, and X.-W. Chu, “EPPMiner: An Extended Benchmark Suite for Energy, Power and Performance Characterization of Heterogeneous Architecture,” ACM e-Energy 2017, Hong Kong, May 2017. [PDF]
V. Chau, X.-W. Chu, H. Liu, and Y.-W. Leung, “Energy Efficient Job Scheduling with DVFS for CPU-GPU Heterogeneous Systems,” ACM e-Energy 2017, Hong Kong, May 2017. [PDF]
X. Mei, X.-W. Chu, H. Liu, Y.-W. Leung, and Z. Li, “Energy Efficient Real-time Task Scheduling on CPU-GPU Hybrid Clusters,” IEEE INFOCOM 2017, GA, USA, May 2017. (Acceptance rate = 20.93%) [PDF]
X. Mei and X.-W. Chu, “Dissecting GPU Memory Hierarchy through Microbenchmarking,” IEEE Transactions on Parallel and Distributed Systems, Vol. 28. No. 1, pages 72-86, Jan 2017. [Source Code][Preprint]
X. Mei, Q. Wang, and X.-W. Chu, “A Survey and Measurement Study of GPU DVFS on Energy Conservation,” Digital Communications and Networks, 2017 [Preprint]
X.-W. Chu, C. Liu, K. Ouyang, L. S. Yung, H. Liu, and Y.-W. Leung, “PErasure: a Parallel Cauchy Reed-Solomon Coding Library for GPUs,” IEEE ICC 2015, London, UK, June 2015. [PDF] [Demo Code]
X. Mei, K. Zhao, C. Liu, and X.-W. Chu, “Benchmarking the Memory Hierarchy of Modern GPUs,” the 11th IFIP International Conference on Network and Parallel Computing (NPC 2014), Taiwan, September 2014. [PDF]
K. Zhao and X.-W. Chu, “G-BLASTN: Accelerating Nucleotide Alignment by Graphics Processors,” Bioinformatics, 30(10):1384-91, May 2014. [Preprint] [To get the final version, please access through Bioinformatics] [Website of G-BLASTN]
Y. Li, H. Chi, L. Xia, and X.-W. Chu, “Accelerating the Scoring Module of Mass Spectrometry-Based Protein Identification Using GPUs,” BMC Bioinformatics, 15:121, April 2014. [Open Access]
Q. Li, C. Zhong, K. Li, G. Zhang, X. Lu, Q. Zhang, K. Zhao and X.-W. Chu, “A Parallel Lattice Boltzmann Method for Large Eddy Simulation on Multiple GPUs,” Springer Computing Journal, Vol. 96, No. 6, Page 479-501, 2014. [PDF]
X. Mei, L. Yung, K. Zhao, and X.-W. Chu, “A Measurement Study of GPU DVFS on Energy Conservation,” USENIX HotPower’13, co-located with the 24th ACM Symposium on Operating Systems Principles (SOSP), Pennsylvania, USA, November 2013. [PDF]
Y. Li, K. Zhao, X.-W. Chu, and Jiming Liu, “Speeding up K-Means Algorithm by GPUs,” Journal of Computer and System Science, Vol. 79, No. 2, pages 216-229, March 2013. [PDF]
Y. Li, L. Xia, H. Chi, and X.-W. Chu, “Accelerating Mass Spectrometry-Based Protein Identification Using GPUs,” Poster, RECOMB 2013, Beijing, China. [PDF]
K. Zhao and X.-W. Chu, “GPU-BLASTN: Accelerating Nucleotide Sequence Alignment by GPUs,” Poster, RECOMB 2013, Beijing, China. [PDF]
X.-W. Chu, K. Zhao, and Z. Li, “Tsunami: Massively Parallel Homomorphic Hashing on Many-core GPUs,” Concurrency and Computation: Practice & Experience, Vol. 24, No. 7, pages 2028-2039, Dec 2012. (online). [PDF]
Q. Li, C. Zhong, K. Li, G. Zhang, X. Lu, Q. Zhang, K. Zhao and X.-W. Chu, “Implementation of a Lattice Boltzmann Method for Large Eddy Simulation on Multiple GPUs,” The third International Workshop on Frontier of GPU Computing, Liverpool, UK, June 2012. [PDF]
Q. Li, C. Zhong, K. Zhao, X. Mei and X.-W. Chu, “Implementation and Analysis of AES Encryption on GPU,” The third International Workshop on Frontier of GPU Computing, Liverpool, UK, June 2012. [PDF]
Y. Li and X.-W. Chu, “Speeding up Scoring Module of Mass Spectrometry Based Protein Identification by GPU,” The Fifth International Symposium on Advances of High Performance Computing and Networking, Liverpool, UK, June 2012. [PDF]
C.-M. Liu, T. Wong, E. Wu, R. Luo, S.-M. Yiu, Y. Li, B. Wang, C. Yu, X.-W. Chu, K. Zhao, R. Li, T.-W. Lam, “SOAP3: Ultra-fast GPU-based parallel alignment tool for short reads,” Applications Note, Bioinformatics, January 2012. [PDF] [SOAP3]
Y. Li, K. Zhao, X.-W. Chu, and Jiming Liu, “Speeding up K-Means Algorithm by GPUs,” IEEE CIT 2010, July 2010, Bradford, UK. (Best Paper Award. 2 out of 485 submissions.) [PDF]
K. Zhao and X.-W. Chu, “GPUMP: a Multiple-Precision Integer Library for GPUs,” The 1st International Workshop on Frontier of GPU Computing, Bradford, UK, June-July 2010. [PDF]
X.-W. Chu, K. Zhao, and M. Wang, “Accelerating Network Coding on Many-core GPUs and Multi-core CPUs,” Journal of Communications, Special Issue on Network Coding and Applications, Vol 4, No 11 (2009), pages 902-909, Dec 2009. [OPEN ACCESS]
K. Zhao, X.-W. Chu, M. Wang, and Y. Jiang, “Speeding Up Homomorphic Hashing Using GPUs,” IEEE ICC’09, Dresden, Germany, June 2009.
X.-W. Chu, K. Zhao, and M. Wang, “Practical Random Linear Network Coding on GPUs”, IFIP Networking’09, Archen, Germany, May 2009. (Acceptance rate = 21.5%) [PDF]
X.-W. Chu, K. Zhao, and M. Wang, “Massively Parallel Network Coding on GPUs,” IEEE IPCCC’08, Austin, Texas, USA, Dec 2008. [PDF]