### Abstract

We argue that, in these cases, the field should take a leaf out of the practices of the SAT-solving community, and adopt systematic benchmarking, and benchmarking contests, as a way measuring (and stimulating) progress. This would involve a change of culture.

Original language | English |
---|---|

Title of host publication | Proceedings of the 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2018 |

Publisher | IEEE |

ISBN (Electronic) | 9781728106250 |

ISBN (Print) | 9781728106267 |

DOIs | |

Publication status | Published - 2018 |

### Keywords

- Computer algebra
- Benchmarking
- Performance

### Cite this

*Proceedings of the 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2018*IEEE. https://doi.org/10.1109/SYNASC.2018.00050

**The Role of Benchmarking in Symbolic Computation : (Position Paper).** / Davenport, James.

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

*Proceedings of the 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2018.*IEEE. https://doi.org/10.1109/SYNASC.2018.00050

}

TY - GEN

T1 - The Role of Benchmarking in Symbolic Computation

T2 - (Position Paper)

AU - Davenport, James

N1 - To be published, on past form, in 2019, but will display a 2018 publication date.

PY - 2018

Y1 - 2018

N2 - There is little doubt that, in the minds of most symbolic computation researchers, the ideal paper consists of a problem statement, a new algorithm, a complexity analysis and preferably a few validating examples. There are many such great papers. This paradigm has served computer algebra well for many years, and indeed continues to do so where it is applicable. However, it is much less applicable to sparse problems, where there are many NP-hardness results, or to many problems coming from algebraic geometry, where the worst-case complexity seems to be rare.We argue that, in these cases, the field should take a leaf out of the practices of the SAT-solving community, and adopt systematic benchmarking, and benchmarking contests, as a way measuring (and stimulating) progress. This would involve a change of culture.

AB - There is little doubt that, in the minds of most symbolic computation researchers, the ideal paper consists of a problem statement, a new algorithm, a complexity analysis and preferably a few validating examples. There are many such great papers. This paradigm has served computer algebra well for many years, and indeed continues to do so where it is applicable. However, it is much less applicable to sparse problems, where there are many NP-hardness results, or to many problems coming from algebraic geometry, where the worst-case complexity seems to be rare.We argue that, in these cases, the field should take a leaf out of the practices of the SAT-solving community, and adopt systematic benchmarking, and benchmarking contests, as a way measuring (and stimulating) progress. This would involve a change of culture.

KW - Computer algebra

KW - Benchmarking

KW - Performance

U2 - 10.1109/SYNASC.2018.00050

DO - 10.1109/SYNASC.2018.00050

M3 - Conference contribution

SN - 9781728106267

BT - Proceedings of the 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2018

PB - IEEE

ER -