Hugh Leather
Hugh Leather
Verified email at inf.ed.ac.uk
Title
Cited by
Cited by
Year
Automatic feature generation for machine learning based optimizing compilation
H Leather, E Bonilla, M O'Boyle
2009 International Symposium on Code Generation and Optimization, 81-91, 2009
1552009
MILEPOST GCC: machine learning based research compiler
G Fursin, C Miranda, O Temam, M Namolaru, E Yom-Tov, A Zaks, ...
GCC summit, 2008
1412008
Emergency evacuation using wireless sensor networks
M Barnes, H Leather, DK Arvind
32nd IEEE Conference on Local Computer Networks (LCN 2007), 851-857, 2007
1272007
End-to-end deep learning of optimization heuristics
C Cummins, P Petoumenos, Z Wang, H Leather
2017 26th International Conference on Parallel Architectures and Compilation …, 2017
972017
Synthesizing benchmarks for predictive modeling
C Cummins, P Petoumenos, Z Wang, H Leather
2017 IEEE/ACM International Symposium on Code Generation and Optimization …, 2017
572017
Compiler fuzzing through deep learning
C Cummins, P Petoumenos, A Murray, H Leather
Proceedings of the 27th ACM SIGSOFT International Symposium on Software …, 2018
532018
Minimizing the cost of iterative compilation with active learning
WF Ogilvie, P Petoumenos, Z Wang, H Leather
2017 IEEE/ACM International Symposium on Code Generation and Optimization …, 2017
462017
Fast automatic heuristic construction using active learning
WF Ogilvie, P Petoumenos, Z Wang, H Leather
International Workshop on Languages and Compilers for Parallel Computing …, 2014
342014
Raced profiles: efficient selection of competing compiler optimizations
H Leather, M O'Boyle, B Worton
Proceedings of the 2009 ACM SIGPLAN/SIGBED conference on Languages …, 2009
342009
Automatic feature generation for machine learning--based optimising compilation
H Leather, E Bonilla, M O'boyle
ACM Transactions on Architecture and Code Optimization (TACO) 11 (1), 1-32, 2014
292014
Power capping: What works, what does not
P Petoumenos, L Mukhanov, Z Wang, H Leather, DS Nikolopoulos
2015 IEEE 21st International Conference on Parallel and Distributed Systems …, 2015
242015
Autotuning OpenCL workgroup size for stencil patterns
C Cummins, P Petoumenos, M Steuwer, H Leather
arXiv preprint arXiv:1511.02490, 2015
242015
MaSiF: Machine learning guided auto-tuning of parallel skeletons
A Collins, C Fensch, H Leather, M Cole
20th Annual International Conference on High Performance Computing, 186-195, 2013
242013
On the inference of user paths from anonymized mobility data
G Tsoukaneri, G Theodorakopoulos, H Leather, MK Marina
2016 IEEE European Symposium on Security and Privacy (EuroS&P), 199-213, 2016
202016
Measuring qoe of interactive workloads and characterising frequency governors on mobile devices
V Seeker, P Petoumenos, H Leather, B Franke
2014 IEEE International Symposium on Workload Characterization (IISWC), 61-70, 2014
152014
Auto-tuning parallel skeletons
A Collins, C Fensch, H Leather
Parallel Processing Letters 22 (02), 1240005, 2012
142012
Programl: Graph-based deep learning for program optimization and analysis
C Cummins, ZV Fisches, T Ben-Nun, T Hoefler, H Leather
arXiv preprint arXiv:2003.10536, 2020
122020
Application of domain-aware binary fuzzing to aid Android virtual machine testing
S Kyle, H Leather, B Franke, D Butcher, S Monteith
ACM SIGPLAN Notices 50 (7), 121-132, 2015
122015
Efficiently parallelizing instruction set simulation of embedded multi-core processors using region-based just-in-time dynamic binary translation
S Kyle, I Böhm, B Franke, H Leather, N Topham
ACM SIGPLAN Notices 47 (5), 21-30, 2012
122012
ALEA: A fine-grained energy profiling tool
L Mukhanov, P Petoumenos, Z Wang, N Parasyris, DS Nikolopoulos, ...
ACM Transactions on Architecture and Code Optimization (TACO) 14 (1), 1-25, 2017
112017
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Articles 1–20