### Abstract

1ome frequently employed algorithms in engineering, are parallel by nature (embarrasingly parallel algorithms) and some others can be parallelized via data parallelization. Algorithms like probability analysis, linear homotopy continuation method, Gauss-Jacobi combinatorial technique are belonging to the first group, while others like algorithms for digital image processing as well as reduced Groenber basis application to solving systems of polynomial equations fall into the other category. In this case study we illustrate how Mathematica can manage to evaluate such algorithms parallel on a multicore machine. The analysis of the efficiency of the computation and the net reduction of the execution time are presented by three examples as well as some useful tips are given to avoid pitfalls and utilize the advantages of parallel processing.

Original language | English |
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Title of host publication | 10th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2009 |

Pages | 449-460 |

Number of pages | 12 |

Publication status | Published - 2009 |

Event | 10th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2009 - Budapest, Hungary Duration: Nov 12 2009 → Nov 14 2009 |

### Other

Other | 10th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2009 |
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Country | Hungary |

City | Budapest |

Period | 11/12/09 → 11/14/09 |

### Fingerprint

### Keywords

- Color quantization
- Gauss-jacobi algorithm
- Monte-carlo method
- Multicore processor
- Parallel computation

### ASJC Scopus subject areas

- Artificial Intelligence
- Information Systems

### Cite this

*10th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2009*(pp. 449-460)

**Mathematica parallel computing. Some timing results on a intel nehalem multicore processor.** / Paláncz, Béla; Kovács, L.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*10th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2009.*pp. 449-460, 10th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2009, Budapest, Hungary, 11/12/09.

}

TY - GEN

T1 - Mathematica parallel computing. Some timing results on a intel nehalem multicore processor

AU - Paláncz, Béla

AU - Kovács, L.

PY - 2009

Y1 - 2009

N2 - 1ome frequently employed algorithms in engineering, are parallel by nature (embarrasingly parallel algorithms) and some others can be parallelized via data parallelization. Algorithms like probability analysis, linear homotopy continuation method, Gauss-Jacobi combinatorial technique are belonging to the first group, while others like algorithms for digital image processing as well as reduced Groenber basis application to solving systems of polynomial equations fall into the other category. In this case study we illustrate how Mathematica can manage to evaluate such algorithms parallel on a multicore machine. The analysis of the efficiency of the computation and the net reduction of the execution time are presented by three examples as well as some useful tips are given to avoid pitfalls and utilize the advantages of parallel processing.

AB - 1ome frequently employed algorithms in engineering, are parallel by nature (embarrasingly parallel algorithms) and some others can be parallelized via data parallelization. Algorithms like probability analysis, linear homotopy continuation method, Gauss-Jacobi combinatorial technique are belonging to the first group, while others like algorithms for digital image processing as well as reduced Groenber basis application to solving systems of polynomial equations fall into the other category. In this case study we illustrate how Mathematica can manage to evaluate such algorithms parallel on a multicore machine. The analysis of the efficiency of the computation and the net reduction of the execution time are presented by three examples as well as some useful tips are given to avoid pitfalls and utilize the advantages of parallel processing.

KW - Color quantization

KW - Gauss-jacobi algorithm

KW - Monte-carlo method

KW - Multicore processor

KW - Parallel computation

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M3 - Conference contribution

AN - SCOPUS:84883075450

SP - 449

EP - 460

BT - 10th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2009

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