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Professor David Gregg

Professor (Computer Science)
OREILLY INSTITUTE

 David.Gregg@tcd.ie

 3531896 1786


Biography

I am a lecturer in the Department of Computer Science, Trinity College Dublin. Within the larger Computer Architecture Group, I lead my own small research group of six postgraduate research students, and one postdoctoral researcher. Before coming to Trinity College Dublin, I studied for a doctorate in Computer Science at the Technische Universitaet in Vienna, on the topic of compiling for advanced instruction level parallel architectures, such as VLIW and EPIC machines. In 2001 I was awarded my doctoral degree with distinction (mit augezeichnetem Erfolg).

Research Tags

  Computer Programming Languages   Computer Software   COMPUTER SYSTEMS   Parallel Computer Architecture

Representations

Details Date
VEE 2008 General chair 2008
CC 2008 Programme Committee 2008
PPPJ 2006 Programme Committee 2006
VEE 2005 & 2006 Steering Committee 2005-2006
IVME 2004 Programme Committee 2004
SCOPES 2003 Programme Committee 2003
SCOPES 2004 Programme Committee 2004
EI Proof of Concept Funding Panel Spring 2003-Summer 2004
IVME 2003 General Chair 2003
Euroforth 2003 Programme Committee 2003
Euroforth 2002 Programme Committee 2002

Languages

Language Skill Reading Skill Writing Skill Speaking
German Medium Medium Medium

Memberships

Membership of Professional Institutions, Associations, Societies

Details Date From Date To
Member of ACM 2003
Fellow of the Irish Computer Society 19.3.2013
Khalid Javeed, Ali El-Moursy, David Gregg, E2CSM: Efficient FPGA implementation of elliptic curve scalar multiplication over generic prime field GF(p), Journal of Supercomputing, 80, (1), 2024, p50 - 74, Journal Article, PUBLISHED  DOI  URL
Khalid Javeed, Ali El-Moursy, David Gregg, EC-Crypto: Highly Efficient Area-Delay Optimized Elliptic Curve Cryptography Processor, IEEE Access, 11, 2023, p56649 - 56662, Journal Article, PUBLISHED  DOI  URL
Building SSA in a Compiler for PHP in, editor(s)Fabrice Rastello, Florent Bouchez-Tichadou , SSA-based Compiler Design, Springer, 2022, pp347 - 357, [Paul Biggar, David Gregg], Book Chapter, PUBLISHED  URL
Barabasz, Barbara and Anderson, Andrew and Soodhalter, Kirk M. and Gregg, David, Error Analysis and Improving the Accuracy of Winograd Convolution for Deep Neural Networks, ACM Trans. Math. Softw., 46, (4), 2020, p33 , Journal Article, PUBLISHED  DOI
Hardware and software performance in deep learning in, editor(s)Bashir M. Al-Hashimi Geoff V. Merrett , Many-Core Computing: Hardware and Software, London, United Kingdom, The Institution of Engineering and Technology, 2019, pp141 - 164, [Andrew Anderson, James Garland, Yuan Wen, Barbara Barabasz, Kaveena Persand, Aravind Vasudevan, David Gregg], Book Chapter, PUBLISHED  URL
Andrew Anderson, Michael Doyle, David Gregg, Scalar Arithmetic Multiple Data: Customizable Precision for Deep Neural Networks, 26th IEEE Symposium on Computer Arithmetic (ARITH 2019), Kyoto, Japan, June 10-12, 2019, edited by Naofumi Takagi, Sylvie Boldo, Martin Langhammer , 2019, pp61 - 68, Notes: [10.1109/ARITH.2019.00018], Conference Paper, PUBLISHED  DOI
James Garland, David Gregg, Low Complexity Multiply-Accumulate Units for Convolutional Neural Networks with Weight-Sharing, ACM Transactions on Architecture and Code Optimization, High-performance Embedded Architecture and Compilation, Valencia, Spain, 21-23 January 2019, edited by Keon De Bosschere , 15, (3), ACM, 2019, pp31:1 - 31:24, Conference Paper, PUBLISHED  URL
Anderson, A. and Gregg, D., Optimal DNN primitive selection with partitioned boolean quadratic programming, Proceedings of the 2018 International Symposium on Code Generation and Optimization , February, 2018, pp340-351 , Notes: [cited By 0], Conference Paper, PUBLISHED  DOI
Garland, J. and Gregg, D., Low complexity multiply-accumulate units for convolutional neural networks with weight-sharing, ACM Transactions on Architecture and Code Optimization, 15, (3), 2018, Notes: [cited By 0], Journal Article, PUBLISHED  DOI
James Garland, David Gregg, Low Complexity Multiply-Accumulate Units for Convolutional Neural Networks with Weight-Sharing, ACM Transactions on Architecture and Code Optimization, 15, (3), 2018, p31:1 - 31:24, Journal Article, PUBLISHED  TARA - Full Text  URL
  

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Syed Asad Alam, David Gregg, Giulio Gambardella, Thomas B. Preusser, Michaela Blott, On the RTL Implementation of FINN Matrix Vector Unit, ACM Transactions on Embedded Computing Systems, 22, (6), 2023, p94:1 - 94:27, Journal Article, PUBLISHED
Muslim Chochlov, Gul Aftab Ahmed, James Vincent Patten, Guoxian Lu, Wei Hou, David Gregg, Jim Buckley, Using a Nearest-Neighbour, BERT-Based Approach for Scalable Clone Detection, IEEE International Conference on Software Maintenance and Evolution, Limassol, Cyprus, October, 2022, 2022, pp582 - 591, Conference Paper, PUBLISHED
Khalid Javeed, Kamran Saeed, David Gregg, High-speed parallel reconfigurable Fp multipliers for elliptic curve cryptography applications, International Journal of Circuit Theory and Applications, 50, (4), 2022, p1160 - 1173, Journal Article, PUBLISHED
Syed Asad Alam, Andrew Anderson, Barbara Barabasz, David Gregg, Winograd Convolution for Deep Neural Networks: Efficient Point Selection, ACM Transactions on Embedded Computing Systems, 21, (6), 2022, p80:1 - 80:28, Journal Article, PUBLISHED
Kaveena Persand, Andrew Anderson, David Gregg, Domino Saliency Metrics: Improving Existing Channel Saliency Metrics with Structural Information, 20th International Conference of the Italian Association for Artificial Intelligence (AIxIA 2021), Italy, December 1-3 2021, 13196, Springer, 2021, pp447 - 461, Conference Paper, PUBLISHED
Kaveena Persand, Andrew Anderson, David Gregg, Taxonomy of Saliency Metrics for Channel Pruning, IEEE Access, 9, 2021, p120110 - 120126, Journal Article, PUBLISHED
Syed Asad Alam, James Garland, David Gregg, Low-precision Logarithmic Number Systems: Beyond Base-2, ACM Transactions on Architecture and Code Optimization, 18, (4), 2021, p47:1 - 47:25, Journal Article, PUBLISHED
David Gregg, Comparing Code Duplication and Compensation Code, Code Optimisation: Trends, Challenges and Perspectives Dagstuhl-Seminar-Report 286, September, 2000, Invited Talk, PUBLISHED
David Gregg, Global Software Pipelining with Iteration Preselection, INRIA-Rocquencourt research centre near Paris, October, 1999, Invited Talk, PUBLISHED
David Gregg, Software Pipelining with Iteration Preselection, Instruction-Level Parallelism and Parallelizing Compilation Dagstuhl-Seminar-Report 237, April, 1999, Invited Talk, PUBLISHED

  

Awards and Honours

Award Date
ACM Recognition of Service Award June 4th 2008

Research Interests

Description Of Research Interests

Software optimization Multicore computing Compiler optimization Domain Specific Languages Automatic program generation Algorithm design Low power computing