John Cavazos
John Cavazos
Assistant Professor
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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
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
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
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
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
Mitigating the compiler optimization phase-ordering problem using machine learning
S Kulkarni, J Cavazos
Proceedings of the ACM international conference on Object oriented …, 2012
Method-specific dynamic compilation using logistic regression
J Cavazos, MFP O'boyle
ACM SIGPLAN Notices 41 (10), 229-240, 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
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
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
Inducing heuristics to decide whether to schedule
J Cavazos, JEB Moss
ACM SIGPLAN Notices 39 (6), 183-194, 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
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
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
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
Automatic tuning of inlining heuristics
J Cavazos, MFP O'Boyle
SC'05: Proceedings of the 2005 ACM/IEEE Conference on Supercomputing, 14-14, 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
Software automatic tuning: from concepts to state-of-the-art results
K Naono, K Teranishi, J Cavazos, R Suda
Springer Science & Business Media, 2010
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
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
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