| Project/Area Number |
05680267
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| Research Category |
Grant-in-Aid for General Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Research Field |
計算機科学
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| Research Institution | Tokyo University of Agriculture and Technology |
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Principal Investigator |
NAKAMORI Mario Tokyo University of Agriculture and Technology, Faculty of Technology, Professor, 工学部, 教授 (00111633)
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| Co-Investigator(Kenkyū-buntansha) |
UEMURA Shunsuke Advanced Institute of Science and Technology Nara, Department of Computer Scienc, 情報科学研究科, 教授 (00203480)
IWASAWA Kyoko Tokyo University of Agriculture and Technology, Faculty of Technology, Research, 工学部, 助手 (80251578)
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| Project Period (FY) |
1993 – 1994
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| Project Status |
Completed (Fiscal Year 1994)
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| Budget Amount *help |
¥1,700,000 (Direct Cost: ¥1,700,000)
Fiscal Year 1994: ¥300,000 (Direct Cost: ¥300,000)
Fiscal Year 1993: ¥1,400,000 (Direct Cost: ¥1,400,000)
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| Keywords | Parallel computing / Algorithm / Research supporting environment / Bilinear programmng / NP completeness / Graph theory / Computathional complesity / Problem complexity / 並列アルゴリズム / 組合せ問題 / 線形計画問題 / 双線形計画問題 / ネットワーク複雑度 / データベース |
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| Research Abstract |
The aim of this research is to make a database of parallel algorithms and to establish a systematic method of designing new parallel algorithms. In order to do this we considered how to represent algorithms. We found a similarity between algorithms for similar problems. Especially, we found homomorphism between problems and algorithms. Thus, we investigated relations between parallel algorithms. As a result, we showed that algorithms are usually described in a simple form if we define appropriately the algebraic structure and operations of the problem. For instance, algorithms on lists are described in a unified way and, thus, algorithms of sorting and summing numbers have the same structure except that only operations are different. This point of view is usefull for designing parallel algorithms. Also, we showed that many NP-complete problems can be described as a bilinear programming problems. For example, we described the well known satisfiability problem as a bilinear programming problem with variables and constraints of linear order in regard to the length of the original logical expression. We also described problems on graphs such as the chromatic number, the maximal clique, the Hamilton cycle, and the isomorphism as bilinear programming problems wigh variables and constraints of polynomial order. As a relating topic we investigated communication complexity in parallel algorithms. We investigated tradeoffs between space complexity and communication complexity in elctronic mail system.
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