Memory Utilization and Machine Learning Techniques for Compiler Optimization
Compiler optimization techniques allow developers to achieve peak performance with low-cost hardware and are of prime importance in the field of efficient computing strategies. The realm of compiler suites that possess and apply efficient optimization methods provide a wide array of beneficial attri...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2021-01-01
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| Series: | ITM Web of Conferences |
| Online Access: | https://www.itm-conferences.org/articles/itmconf/pdf/2021/02/itmconf_icitsd2021_01021.pdf |
| _version_ | 1818574232291901440 |
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| author | Shreyas Madhav A V Singaravel Siddarth Karmel A |
| author_facet | Shreyas Madhav A V Singaravel Siddarth Karmel A |
| author_sort | Shreyas Madhav A V |
| collection | DOAJ |
| description | Compiler optimization techniques allow developers to achieve peak performance with low-cost hardware and are of prime importance in the field of efficient computing strategies. The realm of compiler suites that possess and apply efficient optimization methods provide a wide array of beneficial attributes that help programs execute efficiently with low execution time and minimal memory utilization. Different compilers provide a certain degree of optimization possibilities and applying the appropriate optimization strategies to complex programs can have a significant impact on the overall performance of the system. This paper discusses methods of compiler optimization and covers significant advances in compiler optimization techniques that have been established over the years. This article aims to provide an overall survey of the cache optimization methods, multi memory allocation features and explore the scope of machine learning in compiler optimization to attain a sustainable computing experience for the developer and user. |
| first_indexed | 2024-12-15T00:23:50Z |
| format | Article |
| id | doaj.art-62b8a1d8651b49228a0111de7639fdbb |
| institution | Directory Open Access Journal |
| issn | 2271-2097 |
| language | English |
| last_indexed | 2024-12-15T00:23:50Z |
| publishDate | 2021-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | ITM Web of Conferences |
| spelling | doaj.art-62b8a1d8651b49228a0111de7639fdbb2022-12-21T22:42:13ZengEDP SciencesITM Web of Conferences2271-20972021-01-01370102110.1051/itmconf/20213701021itmconf_icitsd2021_01021Memory Utilization and Machine Learning Techniques for Compiler OptimizationShreyas Madhav A V0Singaravel Siddarth1Karmel A2School of Computer Science and Engineering, Vellore Institute of TechnologySchool of Computer Science and Engineering, Vellore Institute of TechnologySchool of Computer Science and Engineering, Vellore Institute of TechnologyCompiler optimization techniques allow developers to achieve peak performance with low-cost hardware and are of prime importance in the field of efficient computing strategies. The realm of compiler suites that possess and apply efficient optimization methods provide a wide array of beneficial attributes that help programs execute efficiently with low execution time and minimal memory utilization. Different compilers provide a certain degree of optimization possibilities and applying the appropriate optimization strategies to complex programs can have a significant impact on the overall performance of the system. This paper discusses methods of compiler optimization and covers significant advances in compiler optimization techniques that have been established over the years. This article aims to provide an overall survey of the cache optimization methods, multi memory allocation features and explore the scope of machine learning in compiler optimization to attain a sustainable computing experience for the developer and user.https://www.itm-conferences.org/articles/itmconf/pdf/2021/02/itmconf_icitsd2021_01021.pdf |
| spellingShingle | Shreyas Madhav A V Singaravel Siddarth Karmel A Memory Utilization and Machine Learning Techniques for Compiler Optimization ITM Web of Conferences |
| title | Memory Utilization and Machine Learning Techniques for Compiler Optimization |
| title_full | Memory Utilization and Machine Learning Techniques for Compiler Optimization |
| title_fullStr | Memory Utilization and Machine Learning Techniques for Compiler Optimization |
| title_full_unstemmed | Memory Utilization and Machine Learning Techniques for Compiler Optimization |
| title_short | Memory Utilization and Machine Learning Techniques for Compiler Optimization |
| title_sort | memory utilization and machine learning techniques for compiler optimization |
| url | https://www.itm-conferences.org/articles/itmconf/pdf/2021/02/itmconf_icitsd2021_01021.pdf |
| work_keys_str_mv | AT shreyasmadhavav memoryutilizationandmachinelearningtechniquesforcompileroptimization AT singaravelsiddarth memoryutilizationandmachinelearningtechniquesforcompileroptimization AT karmela memoryutilizationandmachinelearningtechniquesforcompileroptimization |