2007 Fiscal Year Final Research Report Summary
Study on Auto-tuning Method for Numerical Computation and Embedded Systems
| Project/Area Number |
18500018
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Software
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| Research Institution | The University of Tokyo (2007)
The University of Electro-Communications (2006) |
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Principal Investigator |
KATAGIRI Takahiro The University of Tokyo, Information Rchnology Center, Associate Professor (40345434)
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| Co-Investigator(Kenkyū-buntansha) |
IMAMAMURA Toshiyuki The University of Electro Communications, Electro-Communication, Associate Professor (60361838)
NAONO Ken HITACHI Limited, Central Research Laboratory, Chief Researcher (20421935)
YUBA Toshitsugu The University of Electro Communications, Information Systems, Professor Emeritus (50251723)
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| Project Period (FY) |
2006 – 2007
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| Keywords | Software Engineering / Software Development Efficiency & Stabilization / High Speed Information Processin / High Performance Computing / Auto Tuning / Embedded Systems / ABCLibScriot / Auto-tuning Software Engineering |
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| Research Abstract |
In this research, we extend conventional auto-tuning method for numerical computation libraries to more widely-covered method for numerical software and to show possibility of auto-tuning for the development process of embedded systems.
The results of this research are summarized as the following four points :
(1) Results on Auto-tuning Algorithm : (a) It is crucial that how to set the sampling points on auto-tuning system for N, which is problem size, for numerical libraries. In this research, we develop new auto-tuning method that auto-tuning system can change the sampling points at run-time. The effectiveness of the proposed method was evaluated on dense and sparse matrix libraries. (b) A new method for computing symmetric dense eigenvalues and eigenvector computation are recently proposed at UC. Berkeley. The method is named MRRR We proposed an auto-tuning method at run-time for the routine of bi-section on the library using MRRR.
(2) Results on Auto-tuning Language: For the proposed auto-tuning language of ABCLibScript, we discussed the possibility of extension for ABCLibScript functions to embedded systems. We showed the solution and implementation cues for the extension when we apply the auto-tuning method for current ABCLibScript technologies.
(3) Towards to Extension of Auto-Tuning Method on Embedded Systems : We verified the preliminary performance on auto-tuning for embedded systems. The application was used a numerical computation benchmark, like signal processing, for embedded systems. As a result, we obtained 6.4x speedups using a benchmark.
(4) Establishment of a Mini Workshop for Auto-tuning and Embedded Systems : We took a place mini workshop by inviting a researcher for research and development division on a company, to show and discuss the real problems on the development process of embedded systems. The impact of this workshop must affect new requirements of auto-tuning study.
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