| Autor: |
Amol C. Adamuthe, Sandeep U. Mane, Rajshree R. Omane |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
EAI Endorsed Transactions on Scalable Information Systems, Vol 8, Iss 30 (2021) |
| ISSN: |
2032-9407 |
| DOI: |
10.4108/eai.26-5-2020.166292 |
| Popis: |
INTRODUCTION: The teaching-learning based optimization (TLBO) algorithm is a recently developed algorithm. The proposed work presents a design of a master-slave TLBO algorithm. OBJECTIVES: This research aims to design a master-slave TLBO algorithm to improve its performance and system utilization for CEC2006 single-objective benchmark functions. METHODS: The proposed approach implemented using OpenMP and CUDA C, a hybrid programming approach to enhance the utilization of the system’s computational resources. The device utilization and performance of the proposed approach evaluated using CEC2006 benchmark functions. RESULTS: The proposed approach obtains best results in significantly reduced time for CEC2006 benchmark functions. The maximum speed-up achieved is 30.14X. The average GPGPU utilization is 90% and the average utilization of logical processors is more than 90%. CONCLUSION: The master-slave TLBO algorithm improves the utilization of computational resources significantly and obtains the best results for CEC2006 benchmark functions. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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