Computer Science @ University of St Andrews

University of St Andrews crest

Dr John Thomson

Dr John Thomson

Director of Postgraduate Teaching

Position: Lecturer

Research profile

Email (@st-andrews.ac.uk): j.thomson

Office: JC1.24 - Jack Cole Building, North Haugh

Phone: +44 (0)1334 46 3335

Home page: https://jt.host.cs.st-andrews.ac.uk

Recent Publications

Lattice-based scheduling for multi-FPGA systems

Yu, T, Feng, B, Stillwell, M, Guo, L, Ma, Y & Thomson, JD 2018, Lattice-based scheduling for multi-FPGA systems. in Proceedings of the International Conference on Field-Programmable Technology 2018, Naha, Okinawa, Japan. IEEE Press, International Conference on Field-Programmable Technology (FPT'18), Naha, Okinawa, Japan, 10/12/18.

Large-scale hierarchical k-means for heterogeneous many-core supercomputers

Li, L, Yu, T, Zhao, W, Fu, H, Wang, C, Tan, L, Yang, G & Thomson, J 2018, Large-scale hierarchical k-means for heterogeneous many-core supercomputers. in Proceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC '18). IEEE Press, Piscataway, The International Conference for High Performance Computing, Networking, Storage, and Analysis, Dallas, United States, 11/11/18.

Predicting and optimizing image compression

Murashko, O, Thomson, JD & Leather, H 2016, Predicting and optimizing image compression. in Proceedings of the 24th ACM International Conference on Multimedia. ACM, pp. 665-669, 24th ACM International Conference on Multimedia (MM), Amsterdam, Netherlands, 15/10/16. DOI: 10.1145/2964284.2967305

Automatic OpenCL device characterization: guiding optimized kernel design

Thoman, P, Kofler, K, Studt, H, Thomson, JD & Fahringer, T 2011, Automatic OpenCL device characterization: guiding optimized kernel design. in Euro-Par 2011 Parallel Processing: 17th International Conference, Euro-Par 2011, Bordeaux, France, August 29 - September 2, 2011, Proceedings, Part II. Lecture Notes in Computer Science, vol. 6853/2011, Springer-Verlag, Berlin, Heidelberg, pp. 438-452. DOI: 10.1007/978-3-642-23397-5_43

Milepost GCC: Machine Learning Enabled Self-tuning Compiler

Fursin, G, Kashnikov, Y, Memon, A, Chamski, Z, Temam, O, Namolaru, M, Yom-Tov, E, Mendelson, B, Zaks, A, Courtois, E, Bodin, F, Barnard, P, Ashton, E, Bonilla, E, Thomson, JD, Williams, C & O'Boyle, M 2011, 'Milepost GCC: Machine Learning Enabled Self-tuning Compiler' International Journal of Parallel Programming, vol. 39, no. 3, pp. 296-327. DOI: 10.1007/s10766-010-0161-2

Reducing Training Time in a One-shot Machine Learning-based Compiler

Thomson, JD, O'Boyle, M, Fursin, G & Franke, B 2010, Reducing Training Time in a One-shot Machine Learning-based Compiler. in Languages and Compilers for Parallel Computing: 22nd International Workshop, LCPC 2009, Newark, DE, USA, October 8-10, 2009, Revised Selected Papers. Lecture Notes In Computer Science, vol. 5898, Springer-Verlag, pp. 399-407. DOI: 10.1007/978-3-642-13374-9_28

Workload characterization supporting the development of domain-specific compiler optimizations using decision trees for data mining

Fenacci, D, Franke, B & Thomson, J 2010, Workload characterization supporting the development of domain-specific compiler optimizations using decision trees for data mining. in Proceedings of the 13th International Workshop on Software 38; Compilers for Embedded Systems. SCOPES '10, ACM, New York, NY, USA, pp. 5:1-5:10. DOI: 10.1145/1811212.1811219

MILEPOST GCC: machine learning based research compiler

Fursin, G, Miranda, C, Temam, O, Namolaru, M, Yom-Tov, E, Zaks, A, Mendelson, B, Bonilla, E, Thomson, J, Leather, H, Williams, C, O'Boyle, M, Barnard, P, Ashton, E, Courtois, E & Bodin, F 2008, MILEPOST GCC: machine learning based research compiler. in GCC Summit.

Using Machine Learning to Focus Iterative Optimization

Agakov, F, Bonilla, E, Cavazos, J, Franke, B, Fursin, G, O'Boyle, MFP, Thomson, J, Toussaint, M & Williams, CKI 2006, Using Machine Learning to Focus Iterative Optimization. in Proceedings of the International Symposium on Code Generation and Optimization. CGO '06, IEEE Computer Society, Washington, DC, USA, pp. 295-305. DOI: 10.1109/CGO.2006.37

Predictive search distributions

Bonilla, EV, Williams, CKI, Agakov, FV, Cavazos, J, Thomson, J & O'Boyle, MFP 2006, Predictive search distributions. in Proceedings of the 23rd international conference on Machine learning. ICML '06, ACM, New York, NY, USA, pp. 121-128. DOI: 10.1145/1143844.1143860