Dr. John Thomson


Lecturer, School of Computer Science, University of St Andrews.


About me:


I’m a lecturer in Computer Science, here in sunny St. Andrews. My research interests include optimising compilers, HPC, embedded systems, applied machine learning, parallelisation techniques, software power-saving techniques, runtime systems and GPGPU optimisation.


I arrived in St. Andrews in 2011, having lectured for almost two years at the University of Innsbruck, in the Austrian Alps. I still can’t ski though. I completed my PhD in 2008 on ‘Using Machine Learning to Automate Compiler Optimisation’ under the supervision of Professor Mike O’Boyle at the University of Edinburgh.


Hello to former PhD students, Klaus Kofler and Ivan Grasso, still working hard in Innsbruck.




Publications


  1. •Automatic OpenCL Device Characterization: Guiding Optimized Kernel Design
    Peter Thoman, Klaus Kofler and John Thomson, In the proceedings the 17th International Conference on Parallel and Distributed Computing, Euro-Par 2011 -     PDF

  2. •Milepost GCC: A machine learning enabled self-tuning compiler
    Grigori Fursin, John Thomson (and 10 others). International Journal of Parallel Processing, Volume 39, Number 3 / June 2011, pp. 296--327 -     PDF

  3. •Workload Characterization Supporting the Development of Domain-Specific Compiler Optimizations Using Decision Trees for Data Mining
    Damon Fenacci, Björn Franke and John Thomson, 13th International Workshop on Software and Compilers for Embedded Systems (SCOPES), June 28-29 2010, Schloss Rheinfels, St. Goar, Germany -     PDF

  4. •Reducing Training Time and Confidence Calculation using Clustering in a Machine Learning Compiler
    John Thomson, Michael O’Boyle, Björn Franke and Grigori Fursin
    In Proceedings of Languages and Compilers for Parallel Computing LCPC 09) -     PDF

  5. •MILEPOST GCC: machine learning based research compiler.
    Grigori Fursin, Cupertino Miranda, Olivier Temam, Mircea Namolaru, Elad Yom-Tov, Ayal Zaks, Bilha Mendelson, Phil Barnard, Elton Ashton, Eric Courtois, Francois Bodin, Edwin Bonilla, John Thomson, Chris Williams, Michael O'Boyle.
    In Proceedings of the GCC Developers' Summit, Ottawa, Canada, June 2008. - PDF

  6. •Using Machine Learning to Focus Iterative Optimization
    Felix Agakov, Edwin Bonilla, John Cavazos, Björn Franke, Michael O’Boyle, John Thomson, and Chris Williams.
    Proceedings of the 4th Annual International Symposium on Code Generation and Optimization (CGO), New York, NY, March 2006 (acceptance rate 29%) - PDF
    Best presentation award. Primary author.

  7. •Predictive Search Distributions
    Edwin Bonilla, Christopher K.I. Williams, Felix Agakov, John Cavazos, John Thomson and Michael F.P. O'Boyle
    In Proceedings of the 23rd International Conference on Machine Learning: ICML'06, Pittsburgh, PA, June 2006. (acceptance rate 19%) - PDF

  8. •Probabilistic Source-Level Optimisation of Embedded Programs
    Björn Franke, Michael O’Boyle and John Thomson
    Proceedings of the 2005 Conference on Languages, Compilers and Tools for Embedded Systems (LCTES'05), Chicago, IL, June 2005, (acceptance rate 25%) - PDF

  9. •Using Machine Learning to Automate Compiler Optimisation
    PhD Thesis. University of Edinburgh, 2008. -     PDF

Contact:

Room 1.24
Jack Cole Building

North Haugh

ST ANDREWS

KY16 9SX


Tel: +44 1334 463335

Email:j.thomson at st-andrews.ac.uk

Twitter:@john_d_thomson


Grants Awarded


  1. •Automatic Portable Performance for Heterogeneous Architectures using Predictive Modelling
    From Fonds zur Förderung der wissenschaftlichen Forschung, Austria
    FWF Grant No. TRP220
    2011-2014 - ~€ 350,000
    University of Innsbruck

  2. •A Predictive Modelling based Approach to Portable Parallel Compilation for Heterogeneous Multi-cores
    EPSRC Grant - EP/H051988/1
    2010-2014. £494,120
    University of Edinburgh