| Revue: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560138 |
| ISSN: | 1405-5546 |
| Autores: | Ben Jmaa, Yomna1 Ben Atitallah, Rabie2 Duvivier, David2 Ben Jemaa, Maher1 |
| Instituciones: | 1University of Sfax, Sfax. Túnez 2Polytechnical University Hauts-de-France, Valenciennes. Francia |
| Año: | 2019 |
| Periodo: | Ene-Mar |
| Volumen: | 23 |
| Número: | 1 |
| Paginación: | 213-230 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Resumen en inglés | Nowadays, sorting is an important operation for several real-time embedded applications. It is one of the most commonly studied problems in computer science. It can be considered as an advantage for some applications such as avionic systems and decision support systems because these applications need a sorting algorithm for their implementation. However, sorting a big number of elements and/or real-time decision making need high processing speed. Therefore, accelerating sorting algorithms using FPGA can be an attractive solution. In this paper, we propose an efficient hardware implementation for different sorting algorithms (BubbleSort, InsertionSort, SelectionSort, QuickSort, HeapSort, ShellSort, MergeSort and TimSort) from high-level descriptions in the zynq-7000 platform. In addition, we compare the performance of different algorithms in terms of execution time, standard deviation and resource utilization. From the experimental results, we show that the SelectionSort is 1.01-1.23 times faster than other algorithms when N < 64; Otherwise, TimSort is the best algorithm. |
| Disciplinas: | Ciencias de la computación |
| Palabras clave: | Inteligencia artificial, Inteligencia artificial |
| Keyword: | FPGA, Sorting algorithms, Heterogeneous architecture CPU/FPGA, Zynq platform, Artificial intelligence |
| Texte intégral: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
