Imperial College London

ProfessorWayneLuk

Faculty of EngineeringDepartment of Computing

Professor of Computer Engineering
 
 
 
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Contact

 

+44 (0)20 7594 8313w.luk Website

 
 
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Location

 

434Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
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606 results found

Fan X, Wu D, Cao W, Luk W, Wang Let al., 2018, Stream processing dual-track CGRA for object inference, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Vol: 26, Pages: 1098-1111, ISSN: 1063-8210

© 1993-2012 IEEE. With the development of machine learning technology, the exploration of energy-efficient and flexible architectures for object inference algorithms is of growing interest in recent years. However, not many publications concentrate on a coarse-grained reconfigurable architecture (CGRA) for object inference algorithms. This paper provides a stream processing, dual-track programming CGRA-based approach to address the inherent computing characteristics of algorithms in object inference. Based on the proposed approach, an architecture called stream dual-track CGRA (SDT-CGRA) is presented as an implementation prototype. To evaluate the performance, the SDT-CGRA is realized in Verilog HDL and implemented in Semiconductor Manufacturing International Corporation 55-nm process, with the footprint of 5.19 mm2at 450 MHz. Seven object inference algorithms, including convolutional neural network (CNN), k-means, principal component analysis (PCA), spatial pyramid matching (SPM), linear support vector machine (SVM), Softmax, and Joint Bayesian, are selected as benchmarks. The experimental results show that the SDT-CGRA can gain on average 343.8 times and 17.7 times higher energy efficiency for Softmax, PCA, and CNN, 621.0 times and 1261.8 times higher energy efficiency for k-means, SPM, linear-SVM, and Joint-Bayesian algorithms when compared with the Intel Xeon E5-2637 CPU and the Nvidia TitanX graphics processing unit. When compared with the state-of-the-art solutions of AlexNet on field-programmable gate array and CGRA, the proposed SDT-CGRA can achieve a 1.78 times increase in energy efficiency and a 13 times speedup, respectively.

JOURNAL ARTICLE

Funie A-I, Grigoras P, Burovskiy P, Luk W, Salmon Met al., 2018, Run-time Reconfigurable Acceleration for Genetic Programming Fitness Evaluation in Trading Strategies, JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY, Vol: 90, Pages: 39-52, ISSN: 1939-8018

JOURNAL ARTICLE

Lee K-H, Fu KCD, Guo Z, Dong Z, Leong MCW, Cheung C-L, Lee AP-W, Luk W, Kwok K-Wet al., 2018, MR Safe Robotic Manipulator for MRI-Guided Intracardiac Catheterization, IEEE-ASME TRANSACTIONS ON MECHATRONICS, Vol: 23, Pages: 586-595, ISSN: 1083-4435

JOURNAL ARTICLE

Liang S, Yin S, Liu L, Luk W, Wei Set al., 2018, FP-BNN: Binarized neural network on FPGA, NEUROCOMPUTING, Vol: 275, Pages: 1072-1086, ISSN: 0925-2312

JOURNAL ARTICLE

Ng H-C, Liu S, Luk W, 2018, ADAM: Automated Design Analysis and Merging for Speeding up FPGA Development., Publisher: ACM, Pages: 189-198

CONFERENCE PAPER

Zhao R, Niu X, Luk W, 2018, Automatic Optimising CNN with Depthwise Separable Convolution on FPGA: (Abstact Only)., Publisher: ACM, Pages: 285-285

CONFERENCE PAPER

Arram J, Kaplan T, Luk W, Jiang Pet al., 2017, Leveraging FPGAs for Accelerating Short Read Alignment, IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, Vol: 14, Pages: 668-677, ISSN: 1545-5963

JOURNAL ARTICLE

Burovskiy P, Grigoras P, Sherwin S, Luk Wet al., 2017, Efficient Assembly for High-Order Unstructured FEM Meshes (FPL 2015), ACM TRANSACTIONS ON RECONFIGURABLE TECHNOLOGY AND SYSTEMS, Vol: 10, ISSN: 1936-7406

JOURNAL ARTICLE

Chau T, Burovskiy P, Flynn M, Luk Wet al., 2017, Advances in Dataflow Systems, Editors: Hurson, Milutinovic, Publisher: ELSEVIER ACADEMIC PRESS INC, Pages: 21-62, ISBN: 978-0-12-812230-3

BOOK CHAPTER

Chau TCP, Burovskiy P, Flynn MJ, Luk Wet al., 2017, Chapter Two - Advances in Dataflow Systems., Advances in Computers, Vol: 105, Pages: 21-62

JOURNAL ARTICLE

Cooper B, Girdlestone S, Burovskiy P, Gaydadjiev G, Averbukh V, Knowles PJ, Luo Wet al., 2017, Quantum Chemistry in Dataflow: Density-Fitting MP2, JOURNAL OF CHEMICAL THEORY AND COMPUTATION, Vol: 13, Pages: 5265-5272, ISSN: 1549-9618

JOURNAL ARTICLE

Fan H, Niu X, Liu Q, Luk Wet al., 2017, F-C3D: FPGA-based 3-Dimensional Convolutional Neural Network, 27th International Conference on Field Programmable Logic and Applications (FPL), Publisher: IEEE, ISSN: 1946-1488

CONFERENCE PAPER

Fu H, He C, Luk W, Li W, Yang Get al., 2017, A Nanosecond-level Hybrid Table Design for Financial Market Data Generators, 25th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), Publisher: IEEE, Pages: 227-234

CONFERENCE PAPER

Fu H, He C, Ruan H, Greenspon I, Luk W, Zheng Y, Liao J, Zhang Q, Yang Get al., 2017, Accelerating Financial Market Server through Hybrid List Design (Abstract Only)., Publisher: ACM, Pages: 289-290

CONFERENCE PAPER

Funie A-I, Guo L, Niu X, Luk W, Salmon Met al., 2017, Custom Framework for Run-Time Trading Strategies, 13th International Symposium on Applied Reconfigurable Computing (ARC), Publisher: SPRINGER INTERNATIONAL PUBLISHING AG, Pages: 154-167, ISSN: 0302-9743

CONFERENCE PAPER

Gan L, Fu H, Luk W, Yang C, Xue W, Yang Get al., 2017, Solving Mesoscale Atmospheric Dynamics Using a Reconfigurable Dataflow Architecture, IEEE MICRO, Vol: 37, Pages: 40-50, ISSN: 0272-1732

JOURNAL ARTICLE

Gan L, Fu H, Mencer O, Luk W, Yang Get al., 2017, Data Flow Computing in Geoscience Applications, Editors: Hurson, Milutinovic, Publisher: ELSEVIER ACADEMIC PRESS INC, Pages: 125-158, ISBN: 978-0-12-811955-6

BOOK CHAPTER

Gan L, Fu H, Mencer O, Luk W, Yang Get al., 2017, Chapter Four - Data Flow Computing in Geoscience Applications., Advances in Computers, Vol: 104, Pages: 125-158

JOURNAL ARTICLE

Grigoras P, Burovskiy P, Arram J, Niu X, Cheung K, Xie J, Luk Wet al., 2017, dfesnippets: An Open-Source Library for Dataflow Acceleration on FPGAs, 13th International Symposium on Applied Reconfigurable Computing (ARC), Publisher: SPRINGER INTERNATIONAL PUBLISHING AG, Pages: 299-310, ISSN: 0302-9743

CONFERENCE PAPER

He C, Fu H, Guo C, Luk W, Yang Get al., 2017, A Fully-Pipelined Hardware Design for Gaussian Mixture Models, IEEE TRANSACTIONS ON COMPUTERS, Vol: 66, Pages: 1837-1850, ISSN: 0018-9340

JOURNAL ARTICLE

He C, Fu H, Luk W, Li W, Yang Get al., 2017, Exploring the Potential of Reconfigurable Platforms for Order Book Update, 27th International Conference on Field Programmable Logic and Applications (FPL), Publisher: IEEE, ISSN: 1946-1488

CONFERENCE PAPER

Hung E, Todman T, Luk W, 2017, Transparent In-Circuit Assertions for FPGAs, IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, Vol: 36, Pages: 1193-1202, ISSN: 0278-0070

JOURNAL ARTICLE

Inggs G, Thomas DB, Luk W, 2017, A Domain Specific Approach to High Performance Heterogeneous Computing, IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, Vol: 28, Pages: 2-15, ISSN: 1045-9219

JOURNAL ARTICLE

Lee K-H, Leong MCW, Chow MCK, Fu H-C, Luk W, Sze K-Y, Yeung C-K, Kwok K-Wet al., 2017, FEM-based Soft Robotic Control Framework for Intracavitary Navigation, IEEE International Conference on Real-time Computing and Robotics (RCAR), Publisher: IEEE, Pages: 11-16

CONFERENCE PAPER

Leong PHW, Amano H, Anderson J, Bertels K, Cardoso JMP, Diessel O, Gogniat G, Hutton M, Lee J, Luk W, Lysaght P, Platzner M, Prasanna VK, Rissa T, Silvano C, So HK-H, Wang Yet al., 2017, The First 25 Years of the FPL Conference: Significant Papers, ACM TRANSACTIONS ON RECONFIGURABLE TECHNOLOGY AND SYSTEMS, Vol: 10, ISSN: 1936-7406

JOURNAL ARTICLE

Li T, Heinis T, Luk W, 2017, ADvaNCE - Efficient and Scalable Approximate Density-Based Clustering Based on Hashing, INFORMATICA, Vol: 28, Pages: 105-130, ISSN: 0868-4952

JOURNAL ARTICLE

Li W, He C, Fu H, Luk Wet al., 2017, An FPGA-based tree crown detection approach for remote sensing images, 16th IEEE International Conference on Field-Programmable Technology (ICFPT), Publisher: IEEE, Pages: 231-234

CONFERENCE PAPER

Ng H-C, Liu S, Luk W, 2017, Reconfigurable Acceleration of Genetic Sequence Alignment: A Survey of Two Decades of Efforts, 27th International Conference on Field Programmable Logic and Applications (FPL), Publisher: IEEE, ISSN: 1946-1488

CONFERENCE PAPER

Russell FP, Duben PD, Niu X, Luk W, Palmer TNet al., 2017, Exploiting the chaotic behaviour of atmospheric models with reconfigurable architectures, COMPUTER PHYSICS COMMUNICATIONS, Vol: 221, Pages: 160-173, ISSN: 0010-4655

JOURNAL ARTICLE

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