Acceleration of Particle Swarm Optimization with AVX Instructions
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F23%3A10251367" target="_blank" >RIV/61989100:27240/23:10251367 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/23:10251367
Result on the web
<a href="https://www.mdpi.com/2076-3417/13/2/734" target="_blank" >https://www.mdpi.com/2076-3417/13/2/734</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/app13020734" target="_blank" >10.3390/app13020734</a>
Alternative languages
Result language
angličtina
Original language name
Acceleration of Particle Swarm Optimization with AVX Instructions
Original language description
Parallel implementations of algorithms are usually compared with single-core CPU performance. The advantage of multicore vector processors decreases the performance gap between GPU and CPU computation, as shown in many recent pieces of research. With the AVX-512 instruction set, there will be another performance boost for CPU computations. The availability of parallel code running on CPUs made them much easier and more accessible than GPUs. This article compares the performances of parallel implementations of the particle swarm optimization algorithm. The code was written in C++, and we used various techniques to obtain parallel execution through Advanced Vector Extensions. We present the performance on various benchmark functions and different problem configurations. The article describes and compares the performance boost gained from parallel execution on CPU, along with advantages and disadvantages of parallelization techniques.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF15_003%2F0000466" target="_blank" >EF15_003/0000466: Artificial Intelligence and Reasoning</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Applied Sciences
ISSN
2076-3417
e-ISSN
2076-3417
Volume of the periodical
13
Issue of the periodical within the volume
2
Country of publishing house
CH - SWITZERLAND
Number of pages
10
Pages from-to
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UT code for WoS article
000916667400001
EID of the result in the Scopus database
2-s2.0-85146721500