Dai Hattori
Panasonic
8 Papers
82 Citations
Dai Hattori is an academic researcher from Panasonic. The author has contributed to research in topics: Variable (computer science) & High-level synthesis. The author has an hindex of 5, co-authored 8 publications.
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Papers
Patent
High level synthesis method for semiconductor integrated circuit
Osamu Ogawa,Dai Hattori,Keiichi Kurokawa,Masahiko Toyonaga +3 more
- 23 Jun 2005
TL;DR: In this paper, a CDFG which is a graph representing calculations and a data flow included in the design specifications of a circuit is generated, a clock cycle required for the processing is obtained and thus an allocated resource connection graph is generated S 102.
35
Patent
High level synthesis method and high level synthesis apparatus
Dai Hattori,Osamu Ogawa,Keiichi Kurokawa +2 more
- 16 Nov 2004
TL;DR: In this article, the number of referencing of a variable described in a behavior level circuit is calculated, and a bit width of the variable is extracted and a plurality of memories capable of data transferring of the extracted bit width are selected.
15
Patent
High-level synthesis method
Osamu Ogawa,Dai Hattori,Keiichi Kurokawa +2 more
- 21 Oct 2003
TL;DR: In this paper, the authors present a high-level synthesis method for generating a CDFG (Control Data Flow Graph) based on an input file describing a behavior of a digital circuit, and allocating each node of the CDFG generated in the generation, expressing contents of processing, to a time synchronized with a clock called a Step.
12
Patent
Program optimization device and program optimization method
Dai Hattori,Tomoo Hamada +1 more
- 08 Oct 2008
TL;DR: A program optimization device which, when optimizing a program, performs optimization depending on characteristics of data to be processed by the program without having to execute the program before the optimization as discussed by the authors.
8
Patent
Program conversion method using hint information that indicates association between variables
Tomoo Hamada,Dai Hattori +1 more
- 05 Feb 2009
TL;DR: A program conversion method that can increase variations of applicable optimizations and effects of the optimization, by being provided with characteristics of a variable or an association between two or more variables as hint information for optimization by a programmer or profiler, is presented in this paper.
6