首页|Findings from Vellore Institute of Technology in the Area of Machine Learning Re ported (Dynamic Machine Learning-based Heuristic Energy Optimization Approach On Multicore Architecture)
Findings from Vellore Institute of Technology in the Area of Machine Learning Re ported (Dynamic Machine Learning-based Heuristic Energy Optimization Approach On Multicore Architecture)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on Machine Learn ing have been published. According to news reporting from Tamil Nadu, India, by NewsRx journalists, research stated, "In the present era, energy is progressivel y turning into the major limitation in designing multicore chips. However, power and performance are the primary segments of energy, which are contrarily correl ated in multicore architectures." The news correspondents obtained a quote from the research from the Vellore Inst itute of Technology, "This research primarily focused on optimizing energy level of multicore chips using parallel workloads by utilizing either power or execut ion advancement based on machine learning computation on dynamic programming. To do as such, the novel dynamic machine learning-based heuristic energy optimizat ion (DML-HEO) algorithm has been designed and developed in this research on appl ication-specific controllers to optimize energy-level on multicore architecture. Here DML-HEO is implemented on the controller to maximize the execution inside a fixed power spending plan or to limit the expended capacity to accomplish a si milar pattern execution. The controller is additionally scalable as it does not bring about critical overhead due to the increase in quantity of cores. The stra tegy has been assessed utilizing controllers on a full-framework test system at lab-scale analysis."
Tamil NaduIndiaAsiaCyborgsEmergi ng TechnologiesMachine LearningVellore Institute of Technology
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