Bandwidth-Constrained Multi-Objective Segmented Brute-Force Algorithm for Efficient Mapping of Embedded Applications on NoC Architecture
- Authors
- Khan, Sarzamin; Anjum, Sheraz; Gulzari, Usman Ali; Umer, Tariq; Kim, Byung-Seo
- Issue Date
- 2018
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Algorithm; brute-force; communication; network-on-chip; topology
- Citation
- IEEE ACCESS, v.6, pp.11242 - 11254
- Journal Title
- IEEE ACCESS
- Volume
- 6
- Start Page
- 11242
- End Page
- 11254
- URI
- https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/4769
- DOI
- 10.1109/ACCESS.2017.2778340
- ISSN
- 2169-3536
- Abstract
- Network-on-chip (NoC) is an emerging alternative to address the communication problem in embedded system-on-chip designs. One of the key and major issues is the optimized mapping of the embedded applications on the underlined NoC platform. In this paper, we propose the bandwidth-constrained multi-objective segmented brute-force mapping (SBMAP) algorithm, which minimizes the communication energy consumption and reduces the computational complexity of the NoC designs. The algorithm generates efficient mapping of the embedded applications on the processing elements of the NoC system by segregating the application into multiple segments. It utilizes the property of modular systematic search, which produces high-performance results with optimized simulation time. We compared the SBMAP algorithm with the state-of-the-art mapping techniques, such as branch and bound (BB), near-optimal mapping (NMAP), and random mapping algorithms for mapping real-world application workloads. The experimental results validated the efficiency of the proposed algorithm against its competitors for most of the performance parameters of the NoC designs. The improvement in energy consumption of the SBMAP algorithm is up to 53% for 2-D mesh and 62% for torus topology as compared with the NMAP, BB, and random algorithms for video object plane decoder, picture in picture, Wi-Fi receiver, and multimedia system real-time application benchmarks.
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Collections - Graduate School > Software and Communications Engineering > 1. Journal Articles
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