John Thomson
John Thomson
Head of AI Academy, appliedAI
Verified email at - Homepage
Cited by
Cited by
Using machine learning to focus iterative optimization
F Agakov, E Bonilla, J Cavazos, B Franke, G Fursin, MFP O'Boyle, ...
International Symposium on Code Generation and Optimization (CGO'06), 11 pp.-305, 2006
Milepost gcc: Machine learning enabled self-tuning compiler
G Fursin, Y Kashnikov, AW Memon, Z Chamski, O Temam, M Namolaru, ...
International journal of parallel programming 39 (3), 296-327, 2011
MILEPOST GCC: machine learning based research compiler
G Fursin, C Miranda, O Temam, M Namolaru, A Zaks, B Mendelson, ...
GCC summit, 2008
Probabilistic source-level optimisation of embedded programs
B Franke, M O'Boyle, J Thomson, G Fursin
Proceedings of the 2005 ACM SIGPLAN/SIGBED Conference on Languages …, 2005
Automatic OpenCL device characterization: Guiding optimized kernel design
P Thoman, K Kofler, H Studt, J Thomson, T Fahringer
European Conference on Parallel Processing, 438-452, 2011
Reducing training time in a one-shot machine learning-based compiler
J Thomson, M O’Boyle, G Fursin, B Franke
International workshop on languages and compilers for parallel computing …, 2009
Workload characterization supporting the development of domain-specific compiler optimizations using decision trees for data mining
D Fenacci, B Franke, J Thomson
Proceedings of the 13th international workshop on software & compilers for …, 2010
Large-scale hierarchical k-means for heterogeneous many-core supercomputers
L Li, T Yu, W Zhao, H Fu, C Wang, L Tan, G Yang, J Thomson
SC18: International Conference for High Performance Computing, Networking …, 2018
Predictive search distributions
EV Bonilla, CKI Williams, FV Agakov, J Cavazos, J Thomson, ...
Proceedings of the 23rd International Conference on Machine learning, 121-128, 2006
Colab: a collaborative multi-factor scheduler for asymmetric multicore processors
T Yu, P Petoumenos, V Janjic, H Leather, J Thomson
Proceedings of the 18th ACM/IEEE International Symposium on Code Generation …, 2020
Large-scale automatic K-means clustering for heterogeneous many-core supercomputer
T Yu, W Zhao, P Liu, V Janjic, X Yan, S Wang, H Fu, G Yang, J Thomson
IEEE Transactions on Parallel and Distributed Systems 31 (5), 997-1008, 2019
Predicting and optimizing image compression
O Murashko, J Thomson, H Leather
Proceedings of the 24th ACM international conference on Multimedia, 665-669, 2016
Collaborative heterogeneity-aware OS scheduler for asymmetric multicore processors
T Yu, R Zhong, V Janjic, P Petoumenos, J Zhai, H Leather, J Thomson
IEEE Transactions on Parallel and Distributed Systems 32 (5), 1224-1237, 2020
Using machine learning to automate compiler optimisation
JD Thomson
The University of Edinburgh, 2009
A hybrid approach to parallel pattern discovery in C++
C Brown, V Janjic, A Barwell, J Thomson, RC Lozano, M Cole, B Franke, ...
2020 28th Euromicro International Conference on Parallel, Distributed and …, 2020
Envisioning SLO-driven service selection in multi-cloud applications
A Elhabbash, Y Elkhatib, GS Blair, Y Lin, A Barker, J Thomson
Proceedings of the 12th IEEE/ACM International Conference on Utility and …, 2019
Lattice-based scheduling for multi-FPGA systems
T Yu, B Feng, M Stillwell, L Guo, Y Ma, J Thomson
2018 International Conference on Field-Programmable Technology (FPT), 318-321, 2018
Modelling VM Latent Characteristics and Predicting Application Performance using Semi-supervised Non-negative Matrix Factorization
Y Lin, A Barker, J Thomson
2020 IEEE 13th International Conference on Cloud Computing (CLOUD), 470-474, 2020
Automatic Player Identification in Dota 2
S Yuen, JD Thomson, O Don
arXiv preprint arXiv:2008.12401, 2020
Poster: A collaborative multi-factor scheduler for asymmetric multicore processors
T Yu, P Petoumenos, V Janjic, M Zhu, H Leather, J Thomson
2019 28th International Conference on Parallel Architectures and Compilation …, 2019
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