Folded fat H-Tree: An interconnection topology for dynamically reconfigurable processor array

Yutaka Yamada, Hideharu Amano, Michihiro Koibuchi, Akiya Jouraku, Kenichiro Anjo, Katsunobu Nishimura

研究成果: Chapter

3 引用 (Scopus)

抜粋

Fat H-Tree is a novel on-chip network topology for a dynamic reconfigurable processor array. It includes both fat tree and torus structure, and suitable to map tasks in a stream processing. For on-chip implementation, folding layout is also proposed. Evaluation results show that Fat H-Tree reduces the distance of H-Tree from 13% to 55%, and stretches the throughput almost three times.

元の言語English
ホスト出版物のタイトルLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
編集者Laurence T. Yang, Minyi Guo, Guang R. Gao, Niraj K. Jha
出版者Springer Verlag
ページ301-311
ページ数11
ISBN(印刷物)354022906X, 9783540229063
DOI
出版物ステータスPublished - 2004 1 1

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
3207
ISSN(印刷物)0302-9743
ISSN(電子版)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • これを引用

    Yamada, Y., Amano, H., Koibuchi, M., Jouraku, A., Anjo, K., & Nishimura, K. (2004). Folded fat H-Tree: An interconnection topology for dynamically reconfigurable processor array. : L. T. Yang, M. Guo, G. R. Gao, & N. K. Jha (版), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 301-311). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 3207). Springer Verlag. https://doi.org/10.1007/978-3-540-30121-9_29