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.
|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|
|出版物ステータス||Published - 2004 1 1|
|名前||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)