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Designing a Distributed Multi-agent System for Compiler Optimization
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- Sari, Alparslan (author)
- University of Delaware
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- Sahin, Cagri (author)
- Gazi Universitesi,Gazi University
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- Butun, Ismail, 1981 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
- (creator_code:org_t)
- 2021
- 2021
- English.
- In: 2021 Zooming Innovation in Consumer Technologies Conference, ZINC 2021. ; , s. 269-274
- Conference paper (peer-reviewed)
Abstract
Subject headings
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- This paper explores the run time performance improvements using different GCC optimization flags in program compilation. As multi-core microprocessor systems replacing legacy single-core ones, tremendous effort is needed to address to optimize the associated compilers for newly designed architectures in order to suit them for running parallel programming on multiple cores. Therefore, the aim of this paper is to address this challenge by designing an optimum distributed multi-agent system to perform compiler optimization. A multi-agent framework is adopted to utilize random and genetic algorithm-based search algorithm to find the best GCC optimization flags for a given program. The framework is highly scalable and can be extended with distributed system concept to perform code compilation in parallel to find the best-optimized code sequence in a short amount of time. The initial performance results have promising indicators which clearly show that the performance improvement is achieved.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorteknik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Engineering (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Inbäddad systemteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Embedded Systems (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)
Keyword
- genetic algorithms
- performance
- multi-core systems
- random search
- Jadex
- GCC
Publication and Content Type
- kon (subject category)
- ref (subject category)
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