Algorithms for speeding up execution in natural computing

2023 Fiscal Year Final Research Report

• Project/Area Number: 20K11681
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 60010:Theory of informatics-related
• Research Institution: Kyushu Institute of Technology
• Principal Investigator: Fujiwara Akihiro 九州工業大学, 大学院情報工学研究院, 教授 (10295008)
• Project Period (FY): 2020-04-01 – 2024-03-31
• Keywords: アルゴリズム / ナチュラルコンピューティング

Outline of Final Research Achievements

In natural computing, many results have been proposed for computational models, which are based on biological systems, as hardware for parallel and distributed processing. In this study, we focused on the execution speed of natural computing in the real world, which has not been considered in previous studies. We first verified the computational capability of proposed models from a practical view of the execution speed of algorithms, and also proposed algorithms for computationally hard problems using fast executable operations. We also developed a parallel simulator for the proposed computational model. We verified the validity and effectiveness of the proposed algorithm and evaluated the accuracy and computational speed of the proposed algorithms using the simulator.

Free Research Field

アルゴリズム

Academic Significance and Societal Importance of the Research Achievements

本研究では，生物の細胞の生命活動などの自然界のシステムを計算に用いるナチュラルコンピューティングにおいて，実行速度を考慮した計算モデルと効率のよいアルゴリズムの提案を行なった．これにより，従来の計算機では正確な解を求めることが非常に困難である問題に対して，実用的な時間で問題を解くナチュラルコンピューティングの実現に一歩近づくことができたことになる．また，提案モデルに対して高速に動作するシミュレータの開発を行っており，ナチュラルコンピューティングにおけるアルゴリズムの正確な評価や検証について貢献できているものと考えられる．