Towards Highly Optimized Cartesian Genetic Programming: From Sequential via SIMD and Thread to Massive Parallel Implementation
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F14%3APU111926" target="_blank" >RIV/00216305:26230/14:PU111926 - isvavai.cz</a>
Výsledek na webu
<a href="http://dl.acm.org/citation.cfm?id=2576768.2598343" target="_blank" >http://dl.acm.org/citation.cfm?id=2576768.2598343</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/2576768.2598343" target="_blank" >10.1145/2576768.2598343</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Towards Highly Optimized Cartesian Genetic Programming: From Sequential via SIMD and Thread to Massive Parallel Implementation
Popis výsledku v původním jazyce
Most implementations of Cartesian genetic programming (CGP) which can be found in the literature are sequential. However, solving complex design problems by means of genetic programming requires parallel implementations of search methods and fitness functions. This paper deals with the design of highly optimized implementations of CGP and their detailed evaluation in the task of evolutionary circuit design. Several sequential implementations of CGP have been analyzed and the effect of various additional optimizations has been investigated. Furthermore, the parallelism at the instruction, data, thread and process level has been applied in order to take advantage of modern processor architectures and computer clusters. Combinational adders and multipliers have been chosen to give a performance comparison with state of the art methods.
Název v anglickém jazyce
Towards Highly Optimized Cartesian Genetic Programming: From Sequential via SIMD and Thread to Massive Parallel Implementation
Popis výsledku anglicky
Most implementations of Cartesian genetic programming (CGP) which can be found in the literature are sequential. However, solving complex design problems by means of genetic programming requires parallel implementations of search methods and fitness functions. This paper deals with the design of highly optimized implementations of CGP and their detailed evaluation in the task of evolutionary circuit design. Several sequential implementations of CGP have been analyzed and the effect of various additional optimizations has been investigated. Furthermore, the parallelism at the instruction, data, thread and process level has been applied in order to take advantage of modern processor architectures and computer clusters. Combinational adders and multipliers have been chosen to give a performance comparison with state of the art methods.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
<a href="/cs/project/GA14-04197S" target="_blank" >GA14-04197S: Pokročilé metody evolučního návrhu složitých číslicových obvodů</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2014
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
GECCO '14 Proceedings of the 2014 conference on Genetic and evolutionary computation
ISBN
978-1-4503-2662-9
ISSN
—
e-ISSN
—
Počet stran výsledku
8
Strana od-do
1015-1022
Název nakladatele
Association for Computing Machinery
Místo vydání
New York
Místo konání akce
Sheraton Wall Centre Vancouver
Datum konání akce
12. 7. 2014
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
000364333000127