MSc System Design (Microelectronic)
e: email@example.com t: 059 9175442
PhD Candidate and researcher in Machine Learning. Lecturer and supervisor in undergrad and postgrad Electronics. Twenty-two years of industrial experience in software, FPGA & IC Design Engineering with Digital SoC/IP ASIC, FPGA and PCB design and test, training and customer support experience in various industries. Project manager, team and technical leader. Three years of External Examiner experience, eleven years of lecturing and research supervision experience.
- ACADEMC AND RESEARCH EXPERIENCE
- Publications and outputs
- Research Supervision
- Engagement and Collaboration
Academic and Research Experience
Research assistant on a PhD project designing low power embedded hardware for the SeNDT project in Trinity College Dublin, 2003-2004.
PhD Research Candidate, researching Micro-architectural Optimisations of Machine Learning Algorithms in FPGAs, ASICs and Embedded Systems for Increased Performance and Power, Area Conservation, 2016-2020. The thesis was submitted in 2020.
Current research interests include Micro-architectural optimisations in hardware and low-level software of artificial intelligence and machine learning algorithms. These optimisations aim to reduce power and gate count in FPGA and ASIC devices and increase performance in embedded low power IoT Edge devices.
Publications and Outputs
Peer Reviewed Journal Articles
Garland, J. and Gregg D. (2018) ‘Low Complexity Multiply Accumulate Units for Convolutional Neural Networks with Weight-Sharing’, in ACM Transactions on Architecture and Code Optimisation (TACO), vol. 15, no. 3, August 2018, Article 31, pp. 1-24, DOI: 10.1145/3233300
Garland, J. and Gregg D. (2017) ‘Low Complexity Multiply Accumulate Unit for Weight-Sharing Convolutional Neural Networks’, in IEEE Computer Architecture Letters, vol. 16, no. 2, pp. 132-135, July-Dec. 1 2017, DOI: 10.1109/LCA.2017.2656880
Anderson, A; Garland, J; Wen, Y; Barabasz, B; Persand, K; Vasudevan, A; Gregg, D. (2019) Chapter 6, ‘Hardware and software performance in deep learning’ in ‘Many-Core Computing: Hardware and Software’, pp: 141-161, ISBN: 978-1-78561-582-5.
Garland, J. and Gregg D. (2017) ‘Low Complexity Multiply Accumulate Unit for Weight-Sharing Convolutional Neural Networks’, in ‘ACACES 2017 Poster Abstracts’, pp. 53-56, HiPEAC, the European Network of Excellence on High Performance and Embedded Architecture and Compilation.
Conference Proceedings and Papers
Garland, J. and Gregg D. (2019) ‘Low Complexity Multiply-Accumulate Units for Convolutional Neural Networks with Weight-Sharing’, talk at HiPEAC January 2019, Valencia, Spain.
Garland, J. and Gregg D. (2017) ‘Low Complexity Multiply Accumulate Unit for Weight-Sharing Convolutional Neural Networks’, Poster presentation, HiPEAC ACACES 2017, Fiuggi, Italy.
Current Research Students
2019-Present, Institute of Technology, Carlow-
- Bovenizer, Christopher (2020-2022), IRC Employment-Based Program M.Sc., “Live, On-site Automation of Harvesting Equipment using Artificial Intelligence, Vision and
- Sensor Systems”, Institute of Technology, Carlow and Tanco Autowrap Limited.
- Furlong, Ryan (2019-2021), President’s EngCore Research Fellowship M.Sc., “Development platform for Artificial Intelligence at the network edge”.
- Connolly, Luke (2019-2021), President’s EngCore Research Fellowship M.Sc., “UAV obstacle avoidance”, Institute of Technology, Carlow.
Past research students
2019, Institute of Technology Carlow-
- Brennan, Colm (2019), M.Sc. in Communications Technology Management, “How can Machine Learning be Applied to Maritime Data Information to Aid Targeted Patrolling by the Irish Naval Service?”
2006-2008, Trinity College Dublin-
- Kantas, Charalampos (2008), M.Sc. in Computer Science (Mobile and Ubiquitous Computing), “Design & Analysis of Power-Efficient Embedded FPGA Sensor Systems”
- Meehan, Eoin (2006), M.Sc. in Computer Science (Ubiquitous Computing), “Are you looking at me?”
- Carter, James (2006), M.Sc. in Computer Science (Ubiquitous Computing), “Study of power saving on Mica2 motes.”
- McKnight, Joseph (2006), M.Sc. in Computer Science (Ubiquitous Computing), “Investigating an Integrated Inertial Gesture Recognition System and Vibrotactile Display”
Areas of Interest as a Supervisor include
- Machine Learning
- ASIC and FPGA design
- Embedded Computing and Sensor systems
Engagement and Collaboration
- 2020: The tech journalist Timothy Prickett Morgan of The Next Platform web site and Youtube channel interviewed me on Monday 27th July 2020 about our HOBFLOPS CNN work.
- 2020: President’s Vote funding for the development of a Robotic & AI Course.
- 2019-Present: Research collaboration with Adjunct Professor Dr. Francisco Domínguez Mateos of Universidad Rey Juan Carlos.
- 2018-2020: Reviewer: IEEE Transactions on Very Large-Scale Integrated Circuits (TVLSI) Journal.
- 2019-2020: Reviewer: IEEE Access Journal.
- 2016-Present: Judge for the annual Xilinx Open Hardware Competition.
- 2018-Present: IT support for St Columba’s National School.
- 2020-2021: President’s EngCore Research Fellowship funding available for one student.
- 2020-2022: Irish Research Council Employment Based Program student was funded.
- 2019-2021: Two President’s EngCore Research Fellowship students were funded.
- 2019: Enterprise Ireland Innovation Voucher: EDR 775 Nmictech Ltd.
- 2016-2020: Held SFI Data-centric ultra-low power embedded computing PhD funding, Grant number 12/IA/1381.
- 2003-2004: Worked as a Research Assistant on a PhD research project, SeNDT, in Trinity College Dublin.