The Experts below are selected from a list of 49248 Experts worldwide ranked by ideXlab platform
Olivier Temam - One of the best experts on this subject based on the ideXlab platform.
-
CGO - Rapidly Selecting Good Compiler Optimizations using Performance Counters
International Symposium on Code Generation and Optimization (CGO'07), 2007Co-Authors: John Cavazos, Grigori Fursin, Felix Agakov, Edwin V. Bonilla, Michael O'boyle, Olivier TemamAbstract:Applying the right compiler optimizations to a particular program can have a significant impact on program Performance. Due to the non-linear interaction of compiler optimizations, however, determining the best setting is nontrivial. There have been several proposed techniques that search the space of compiler options to find good solutions; however such approaches can be expensive. This paper proposes a different approach using Performance Counters as a means of determining good compiler optimization settings. This is achieved by learning a model off-line which can then be used to determine good settings for any new program. We show that such an approach outperforms the state-ofthe- art and is two orders of magnitude faster on average. Furthermore, we show that our Performance Counter-based approach outperforms techniques based on static code features. Using our technique we achieve a 17% improvement over the highest optimization setting of the commercial PathScale EKOPath 2.3.1 optimizing compiler on the SPEC benchmark suite on a recent AMD Athlon 64 3700+ platform.
-
rapidly selecting good compiler optimizations using Performance Counters
Symposium on Code Generation and Optimization, 2007Co-Authors: John Cavazos, Grigori Fursin, Felix Agakov, Edwin V. Bonilla, Michael F P Oboyle, Olivier TemamAbstract:Applying the right compiler optimizations to a particular program can have a significant impact on program Performance. Due to the non-linear interaction of compiler optimizations, however, determining the best setting is nontrivial. There have been several proposed techniques that search the space of compiler options to find good solutions; however such approaches can be expensive. This paper proposes a different approach using Performance Counters as a means of determining good compiler optimization settings. This is achieved by learning a model off-line which can then be used to determine good settings for any new program. We show that such an approach outperforms the state-ofthe- art and is two orders of magnitude faster on average. Furthermore, we show that our Performance Counter-based approach outperforms techniques based on static code features. Using our technique we achieve a 17% improvement over the highest optimization setting of the commercial PathScale EKOPath 2.3.1 optimizing compiler on the SPEC benchmark suite on a recent AMD Athlon 64 3700+ platform.
John Cavazos - One of the best experts on this subject based on the ideXlab platform.
-
CGO - Rapidly Selecting Good Compiler Optimizations using Performance Counters
International Symposium on Code Generation and Optimization (CGO'07), 2007Co-Authors: John Cavazos, Grigori Fursin, Felix Agakov, Edwin V. Bonilla, Michael O'boyle, Olivier TemamAbstract:Applying the right compiler optimizations to a particular program can have a significant impact on program Performance. Due to the non-linear interaction of compiler optimizations, however, determining the best setting is nontrivial. There have been several proposed techniques that search the space of compiler options to find good solutions; however such approaches can be expensive. This paper proposes a different approach using Performance Counters as a means of determining good compiler optimization settings. This is achieved by learning a model off-line which can then be used to determine good settings for any new program. We show that such an approach outperforms the state-ofthe- art and is two orders of magnitude faster on average. Furthermore, we show that our Performance Counter-based approach outperforms techniques based on static code features. Using our technique we achieve a 17% improvement over the highest optimization setting of the commercial PathScale EKOPath 2.3.1 optimizing compiler on the SPEC benchmark suite on a recent AMD Athlon 64 3700+ platform.
-
rapidly selecting good compiler optimizations using Performance Counters
Symposium on Code Generation and Optimization, 2007Co-Authors: John Cavazos, Grigori Fursin, Felix Agakov, Edwin V. Bonilla, Michael F P Oboyle, Olivier TemamAbstract:Applying the right compiler optimizations to a particular program can have a significant impact on program Performance. Due to the non-linear interaction of compiler optimizations, however, determining the best setting is nontrivial. There have been several proposed techniques that search the space of compiler options to find good solutions; however such approaches can be expensive. This paper proposes a different approach using Performance Counters as a means of determining good compiler optimization settings. This is achieved by learning a model off-line which can then be used to determine good settings for any new program. We show that such an approach outperforms the state-ofthe- art and is two orders of magnitude faster on average. Furthermore, we show that our Performance Counter-based approach outperforms techniques based on static code features. Using our technique we achieve a 17% improvement over the highest optimization setting of the commercial PathScale EKOPath 2.3.1 optimizing compiler on the SPEC benchmark suite on a recent AMD Athlon 64 3700+ platform.
Grigori Fursin - One of the best experts on this subject based on the ideXlab platform.
-
CGO - Rapidly Selecting Good Compiler Optimizations using Performance Counters
International Symposium on Code Generation and Optimization (CGO'07), 2007Co-Authors: John Cavazos, Grigori Fursin, Felix Agakov, Edwin V. Bonilla, Michael O'boyle, Olivier TemamAbstract:Applying the right compiler optimizations to a particular program can have a significant impact on program Performance. Due to the non-linear interaction of compiler optimizations, however, determining the best setting is nontrivial. There have been several proposed techniques that search the space of compiler options to find good solutions; however such approaches can be expensive. This paper proposes a different approach using Performance Counters as a means of determining good compiler optimization settings. This is achieved by learning a model off-line which can then be used to determine good settings for any new program. We show that such an approach outperforms the state-ofthe- art and is two orders of magnitude faster on average. Furthermore, we show that our Performance Counter-based approach outperforms techniques based on static code features. Using our technique we achieve a 17% improvement over the highest optimization setting of the commercial PathScale EKOPath 2.3.1 optimizing compiler on the SPEC benchmark suite on a recent AMD Athlon 64 3700+ platform.
-
rapidly selecting good compiler optimizations using Performance Counters
Symposium on Code Generation and Optimization, 2007Co-Authors: John Cavazos, Grigori Fursin, Felix Agakov, Edwin V. Bonilla, Michael F P Oboyle, Olivier TemamAbstract:Applying the right compiler optimizations to a particular program can have a significant impact on program Performance. Due to the non-linear interaction of compiler optimizations, however, determining the best setting is nontrivial. There have been several proposed techniques that search the space of compiler options to find good solutions; however such approaches can be expensive. This paper proposes a different approach using Performance Counters as a means of determining good compiler optimization settings. This is achieved by learning a model off-line which can then be used to determine good settings for any new program. We show that such an approach outperforms the state-ofthe- art and is two orders of magnitude faster on average. Furthermore, we show that our Performance Counter-based approach outperforms techniques based on static code features. Using our technique we achieve a 17% improvement over the highest optimization setting of the commercial PathScale EKOPath 2.3.1 optimizing compiler on the SPEC benchmark suite on a recent AMD Athlon 64 3700+ platform.
Felix Agakov - One of the best experts on this subject based on the ideXlab platform.
-
CGO - Rapidly Selecting Good Compiler Optimizations using Performance Counters
International Symposium on Code Generation and Optimization (CGO'07), 2007Co-Authors: John Cavazos, Grigori Fursin, Felix Agakov, Edwin V. Bonilla, Michael O'boyle, Olivier TemamAbstract:Applying the right compiler optimizations to a particular program can have a significant impact on program Performance. Due to the non-linear interaction of compiler optimizations, however, determining the best setting is nontrivial. There have been several proposed techniques that search the space of compiler options to find good solutions; however such approaches can be expensive. This paper proposes a different approach using Performance Counters as a means of determining good compiler optimization settings. This is achieved by learning a model off-line which can then be used to determine good settings for any new program. We show that such an approach outperforms the state-ofthe- art and is two orders of magnitude faster on average. Furthermore, we show that our Performance Counter-based approach outperforms techniques based on static code features. Using our technique we achieve a 17% improvement over the highest optimization setting of the commercial PathScale EKOPath 2.3.1 optimizing compiler on the SPEC benchmark suite on a recent AMD Athlon 64 3700+ platform.
-
rapidly selecting good compiler optimizations using Performance Counters
Symposium on Code Generation and Optimization, 2007Co-Authors: John Cavazos, Grigori Fursin, Felix Agakov, Edwin V. Bonilla, Michael F P Oboyle, Olivier TemamAbstract:Applying the right compiler optimizations to a particular program can have a significant impact on program Performance. Due to the non-linear interaction of compiler optimizations, however, determining the best setting is nontrivial. There have been several proposed techniques that search the space of compiler options to find good solutions; however such approaches can be expensive. This paper proposes a different approach using Performance Counters as a means of determining good compiler optimization settings. This is achieved by learning a model off-line which can then be used to determine good settings for any new program. We show that such an approach outperforms the state-ofthe- art and is two orders of magnitude faster on average. Furthermore, we show that our Performance Counter-based approach outperforms techniques based on static code features. Using our technique we achieve a 17% improvement over the highest optimization setting of the commercial PathScale EKOPath 2.3.1 optimizing compiler on the SPEC benchmark suite on a recent AMD Athlon 64 3700+ platform.
Edwin V. Bonilla - One of the best experts on this subject based on the ideXlab platform.
-
CGO - Rapidly Selecting Good Compiler Optimizations using Performance Counters
International Symposium on Code Generation and Optimization (CGO'07), 2007Co-Authors: John Cavazos, Grigori Fursin, Felix Agakov, Edwin V. Bonilla, Michael O'boyle, Olivier TemamAbstract:Applying the right compiler optimizations to a particular program can have a significant impact on program Performance. Due to the non-linear interaction of compiler optimizations, however, determining the best setting is nontrivial. There have been several proposed techniques that search the space of compiler options to find good solutions; however such approaches can be expensive. This paper proposes a different approach using Performance Counters as a means of determining good compiler optimization settings. This is achieved by learning a model off-line which can then be used to determine good settings for any new program. We show that such an approach outperforms the state-ofthe- art and is two orders of magnitude faster on average. Furthermore, we show that our Performance Counter-based approach outperforms techniques based on static code features. Using our technique we achieve a 17% improvement over the highest optimization setting of the commercial PathScale EKOPath 2.3.1 optimizing compiler on the SPEC benchmark suite on a recent AMD Athlon 64 3700+ platform.
-
rapidly selecting good compiler optimizations using Performance Counters
Symposium on Code Generation and Optimization, 2007Co-Authors: John Cavazos, Grigori Fursin, Felix Agakov, Edwin V. Bonilla, Michael F P Oboyle, Olivier TemamAbstract:Applying the right compiler optimizations to a particular program can have a significant impact on program Performance. Due to the non-linear interaction of compiler optimizations, however, determining the best setting is nontrivial. There have been several proposed techniques that search the space of compiler options to find good solutions; however such approaches can be expensive. This paper proposes a different approach using Performance Counters as a means of determining good compiler optimization settings. This is achieved by learning a model off-line which can then be used to determine good settings for any new program. We show that such an approach outperforms the state-ofthe- art and is two orders of magnitude faster on average. Furthermore, we show that our Performance Counter-based approach outperforms techniques based on static code features. Using our technique we achieve a 17% improvement over the highest optimization setting of the commercial PathScale EKOPath 2.3.1 optimizing compiler on the SPEC benchmark suite on a recent AMD Athlon 64 3700+ platform.
