Pregled bibliografske jedinice broj: 1054492
Using vectorized calculations in Scilab to improve performances of interpreted enivronment
Using vectorized calculations in Scilab to improve performances of interpreted enivronment // INTED2020 Proceedings / Gómez Chova, L ; López Martínez, A. ; Candel Torres, I. (ur.).
Valencia: International Academy of Technology, Education and Development (IATED), 2020. str. 2127-2136 doi:10.21125/inted.2020.0664 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
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Naslov
Using vectorized calculations in Scilab to improve
performances of interpreted enivronment
Autori
Mikac, Matija ; Horvatić, Miroslav ; Mikac, Vladimir
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
INTED2020 Proceedings
/ Gómez Chova, L ; López Martínez, A. ; Candel Torres, I. - Valencia : International Academy of Technology, Education and Development (IATED), 2020, 2127-2136
ISBN
978-84-09-17939-8
Skup
14th International Technology, Education and Development Conference (INTED 2020)
Mjesto i datum
Valencia, Španjolska, 02.03.2020. - 04.03.2020
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Scilab, vectorization, performance, source code, execution
Sažetak
Free and open-source software for numerical computations, Scilab, can be used as a good alternative to commercial tools such as Matlab in an education environment. Other tools, some of them also being completely free, are available - for example GNU Octave. This paper focuses on Scilab due to our experience in providing it as a valid alternative to Matlab to our STEM students - most of our lab exercises (basic matrix calculus, simple data transfer simulation (bit channel simulation and similar), basic signal generation and processing) were solved in both Matlab and Scilab giving proper results in "real- time". Of course, due to the completely different nature of execution of programming languages included in those tools, slower execution and lower calculation performance is expected in Scilab (which is interpreted, in contrast to JIT compilation in Matlab). In this paper, possible improvement in Scilab execution performances is described, using so called vectorization approach. The paper includes some examples of both, the simple (slow) source code and the vectorization-based alternatives. Results showing the measured execution times are given, including the description of the measurement methodology. The results show that huge performance improvements can be achieved in some test cases. Of course, that may vary based on the problem being solved - it cannot be concluded that vectorization can be used on each and every problem - therefore, there will still be cases in which the performances will be impacted by the slow nature of interpretation- based execution. Some initial thoughts and measurements related to problem scalability and possible impact to the performance are also included prior to final conclusions.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo, Interdisciplinarne tehničke znanosti, Informacijske i komunikacijske znanosti
Napomena
WOS:000558088802033
POVEZANOST RADA
Ustanove:
Sveučilište Sjever, Koprivnica
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Conference Proceedings Citation Index - Social Sciences & Humanities (CPCI-SSH)