Scheduling Motif Finding Problem Across Heterogeneous CPU Architectures
Elsawwaf, A., Aly, G., Faheem, H., Fayez, M. (2025). Scheduling Motif Finding Problem Across Heterogeneous CPU Architectures. EKB Journal Management System, 25(1), 1-17. doi: 10.21608/ijicis.2025.358362.1375
Ali Mohammed Elsawwaf; Gamal Eldin Mohammed Aly; Hossam Faheem; Mahmoud Fayez. "Scheduling Motif Finding Problem Across Heterogeneous CPU Architectures". EKB Journal Management System, 25, 1, 2025, 1-17. doi: 10.21608/ijicis.2025.358362.1375
Elsawwaf, A., Aly, G., Faheem, H., Fayez, M. (2025). 'Scheduling Motif Finding Problem Across Heterogeneous CPU Architectures', EKB Journal Management System, 25(1), pp. 1-17. doi: 10.21608/ijicis.2025.358362.1375
Elsawwaf, A., Aly, G., Faheem, H., Fayez, M. Scheduling Motif Finding Problem Across Heterogeneous CPU Architectures. EKB Journal Management System, 2025; 25(1): 1-17. doi: 10.21608/ijicis.2025.358362.1375

Scheduling Motif Finding Problem Across Heterogeneous CPU Architectures

International Journal of Intelligent Computing and Information Sciences
Volume 25, Issue 1, March 2025, Page 1-17  XML PDF (814.07 K)
Document Type: Original Article
DOI: 10.21608/ijicis.2025.358362.1375
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Authors
Ali Mohammed Elsawwaf email 1; Gamal Eldin Mohammed Aly1; Hossam Faheem2; Mahmoud Fayezorcid 3
1Computers and Systems Engineering Department, Faculty of Engineering, Ain Shams University, Cairo, Egypt
2Professor of Computer Systems, Computer Systems Department, Faculty of Computer and Information Sciences, Ain Shams University
3Computer systems Department Faculty of Computer and Information Sciences, Ain Shams University
Abstract
The Motif finding problem is important in bioinformatics, aiming to find recurring sequences in biological data. These motifs, are important for understanding how genes work, how proteins function, and how cells operate. Accurately detecting these patterns is essential for understanding of biology, aiding in scientific research, and developing treatments for diseases. Addressing the motif finding problem efficiently across heterogeneous CPU architectures presents significant challenges in computational efficiency and resource utilization. The variation in the number and speed of cores across CPUs requires developing scheduling strategies to efficiently distribute workloads among these architectures. This paper presents an efficient strategy for optimizing task distribution across heterogeneous CPU architectures. The proposed approach makes performance enhancement with 9 % solving Motif finding problem in CPU heterogeneous architectures. This improvement significantly speed up the process of identifying important biological patterns, making bioinformatics research quicker and more cost-effective. In addition, it has a significant impact on enhancing computational efficiency and reducing costs in high-performance computing environments.
Keywords
Motif finding; Heterogeneous CPU architectures; Task distribution strategy
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