首页|New Findings on Machine Learning from Department of Computer Sciences Summarized (Machine Learning-driven Energy-efficient Load Balancing for Real-time Heterogeneous Systems)
New Findings on Machine Learning from Department of Computer Sciences Summarized (Machine Learning-driven Energy-efficient Load Balancing for Real-time Heterogeneous Systems)
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NETL
NSTL
Springer Nature
Current study results on Machine Learning have been published. According to news reporting out of Oran, Algeria, by NewsRx editors, research stated, “Load balancing plays a critical role in ensuring system stability and optimal performance, and as such, it has been a subject of extensive research across diverse computing domains, particularly in heterogeneous systems. Such systems integrate various computing devices with distinct architectures and computational power, each designed to execute a particular type of workload having diverse and immediate requirements.”
OranAlgeriaCyborgsEmerging TechnologiesMachine LearningDepartment of Computer Sciences
NETL
NSTL
Springer Nature
