| 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 | 533 | 2006 |
| Auto-tuning a high-level language targeted to GPU codes S Grauer-Gray, L Xu, R Searles, S Ayalasomayajula, J Cavazos 2012 innovative parallel computing (InPar), 1-10, 2012 | 530 | 2012 |
| Rapidly selecting good compiler optimizations using performance counters J Cavazos, G Fursin, F Agakov, E Bonilla, MFP O'Boyle, O Temam International Symposium on Code Generation and Optimization (CGO'07), 185-197, 2007 | 353 | 2007 |
| A survey on compiler autotuning using machine learning AH Ashouri, W Killian, J Cavazos, G Palermo, C Silvano ACM Computing Surveys (CSUR) 51 (5), 1-42, 2018 | 267 | 2018 |
| Iterative optimization in the polyhedral model: Part II, multidimensional time LN Pouchet, C Bastoul, A Cohen, J Cavazos ACM SIGPLAN Notices 43 (6), 90-100, 2008 | 223 | 2008 |
| Mitigating the compiler optimization phase-ordering problem using machine learning S Kulkarni, J Cavazos Proceedings of the ACM international conference on Object oriented …, 2012 | 162 | 2012 |
| Method-specific dynamic compilation using logistic regression J Cavazos, MFP O'boyle ACM SIGPLAN Notices 41 (10), 229-240, 2006 | 140 | 2006 |
| Predictive modeling in a polyhedral optimization space E Park, J Cavazos, LN Pouchet, C Bastoul, A Cohen, P Sadayappan International journal of parallel programming 41 (5), 704-750, 2013 | 136 | 2013 |
| Fast compiler optimisation evaluation using code-feature based performance prediction C Dubach, J Cavazos, B Franke, G Fursin, MFP O'Boyle, O Temam Proceedings of the 4th international conference on Computing frontiers, 131-142, 2007 | 129 | 2007 |
| Using graph-based program characterization for predictive modeling E Park, J Cavazos, MA Alvarez Proceedings of the Tenth International Symposium on Code Generation and …, 2012 | 117 | 2012 |
| Inducing heuristics to decide whether to schedule J Cavazos, JEB Moss ACM SIGPLAN Notices 39 (6), 183-194, 2004 | 115 | 2004 |
| Hadm: Hybrid analysis for detection of malware L Xu, D Zhang, N Jayasena, J Cavazos Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016: Volume …, 2018 | 114 | 2018 |
| Cobayn: Compiler autotuning framework using bayesian networks AH Ashouri, G Mariani, G Palermo, E Park, J Cavazos, C Silvano ACM Transactions on Architecture and Code Optimization (TACO) 13 (2), 1-25, 2016 | 112 | 2016 |
| Micomp: Mitigating the compiler phase-ordering problem using optimization sub-sequences and machine learning AH Ashouri, A Bignoli, G Palermo, C Silvano, S Kulkarni, J Cavazos ACM Transactions on Architecture and Code Optimization (TACO) 14 (3), 1-28, 2017 | 111 | 2017 |
| Automatic performance model construction for the fast software exploration of new hardware designs J Cavazos, C Dubach, F Agakov, E Bonilla, MFP O'Boyle, G Fursin, ... Proceedings of the 2006 international conference on Compilers, architecture …, 2006 | 100 | 2006 |
| Automatic tuning of inlining heuristics J Cavazos, MFP O'Boyle SC'05: Proceedings of the 2005 ACM/IEEE Conference on Supercomputing, 14-14, 2005 | 99 | 2005 |
| Using predictivemodeling for cross-program design space exploration in multicore systems S Khan, P Xekalakis, J Cavazos, M Cintra 16th International Conference on Parallel Architecture and Compilation …, 2007 | 96 | 2007 |
| An evaluation of different modeling techniques for iterative compilation E Park, S Kulkarni, J Cavazos Proceedings of the 14th international conference on Compilers, architectures …, 2011 | 84 | 2011 |
| Software automatic tuning: from concepts to state-of-the-art results K Naono, K Teranishi, J Cavazos, R Suda Springer Science & Business Media, 2010 | 84 | 2010 |
| Learning to schedule straight-line code J Moss, P Utgoff, J Cavazos, D Precup, D Stefanovic, C Brodley, ... Advances in Neural Information Processing Systems 10, 1997 | 79 | 1997 |
