| Project/Area Number |
13224050
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| Research Category |
Grant-in-Aid for Scientific Research on Priority Areas
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| Allocation Type | Single-year Grants |
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| Review Section |
Science and Engineering
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| Research Institution | Kyoto University |
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Principal Investigator |
YUASA Taiichi Kyoto University, Graduate School of Informatics, Professor, 情報学研究科, 教授 (60158326)
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| Co-Investigator(Kenkyū-buntansha) |
CHIKAYAMA Takashi The University of Tokyo, School of Frontier Sciences, Professor, 新領域創成科学研究科, 教授 (40272380)
UEDA Kazunori Waseda University, School of Science and Engineering, Professor, 理工学部, 教授 (10257206)
MORI Shinichiro Kyoto University, Graduate School of Informatics, Associate Professor, 情報学研究科, 助教授 (20243058)
YASUGI Masahiro Kyoto University, Graduate School of Informatics, Associate Professor, 情報学研究科, 助教授 (30273759)
KOMIYA Tsuneyasu Toyohashi University of Technology, Department of Information and Computer Sciences, Lecturer, 情報工学系, 講師 (80283638)
五島 正裕 京都大学, 情報学研究科, 助手 (90283639)
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| Project Period (FY) |
2001 – 2005
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| Project Status |
Completed (Fiscal Year 2005)
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| Budget Amount *help |
¥102,800,000 (Direct Cost: ¥102,800,000)
Fiscal Year 2005: ¥24,000,000 (Direct Cost: ¥24,000,000)
Fiscal Year 2004: ¥28,000,000 (Direct Cost: ¥28,000,000)
Fiscal Year 2003: ¥32,000,000 (Direct Cost: ¥32,000,000)
Fiscal Year 2002: ¥18,800,000 (Direct Cost: ¥18,800,000)
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| Keywords | Algorithm / Computer System / Information System / Efficient and Stable Software Development / Modeling / 計算量 / 局所性 / 並列分散処理 |
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| Research Abstract |
In order to make it possible to construct complexity analysis models and software systems that can cope with both extent and locality of computer systems, we have been working to revisit, unify and develop existing computation concepts from various points of view, based on the notion of Continuous Computing Resources. The major outcomes of this project are the following.
1. Complexity Analysis based on Continuous Computing Resource: We proposed a computation model that can uniformly and concisely express various concepts of computation from the memory hierarchy of a single computer to network delay among computers. We showed that complexity analysis results based on this model reflect real computation more precisely than previous models. In order to make it easier to understand the behavior of sophisticated parallel algorithms, we designed a virtual machine of the model and implemented language systems including simulators and visualizers.
2. Concurrent Language Model LMNtal: We designed
… More
LMNTal (pronounced as "elemental"), a scalable language model for concurrent computation based on hierarchical graph reduction. On this model, we have established techniques for process structure analysis and implemented this model as realistic and useful programming languages. Since hierarchical graph reduction includes a variety of computation models such as multi-set rewriting models and self-organizing models, it is expected that our results will be useful as a bridge between existing computation models.
3. Language Implementation based on Locality: We showed that runtime efficiency of programming language systems can be remarkably improved by focusing on locality. A typical example is the locality improvement by the use of copying garbage collection based on "hierarchical clustering of data objects". This technique is proposed by further improving the existing technique where live objects are copied in depth-first order, with a small stack area and additionally with a queue that is used in case of stack overflow. This technique improves not only the locality in the virtual memory, but also the locality in the CPU cache, and thus allows high performance implementations on real computer systems. Less
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