Name
Title | ||
|---|---|---|
Embedding algorithm of spined cube into grid structure and its wirelength computation |
Abstract | ||
|---|---|---|
In the field of data science, graph embedding is a vital tool to simulate, visualize and design a parallel architecture. The binary cube is one of the most desirable and reliable network-based architecture with high performance, yet many variations have been proposed on the links of the cube to enhance its computational power. The spined cube is a new efficient variant of the binary cube with a smaller diameter and preserves the advantageous properties of the original cube. Grid embedding is accustomed to study simulation capacity of a parallel and distributed computer system and conjointly designs its VLSI layout. In this paper, we propose an algorithm to embed the spined cube into a grid and compute the minimum wirelength over all possible embeddings using the edge congestion technique. (C) 2021 Elsevier B.V. All rights reserved. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.tcs.2021.12.016 | THEORETICAL COMPUTER SCIENCE |
Keywords | DocType | Volume |
Graph embedding, Congestion, Wirelength, Spined cube | Journal | 905 |
ISSN | Citations | PageRank |
0304-3975 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Micheal Arockiaraj | 1 | 0 | 1.35 |
| Arul Jeya Shalini | 2 | 0 | 0.34 |
| J. Nancy Delaila | 3 | 0 | 0.68 |