Spendthrift: Machine learning based resource and frequency scaling for ambient energy harvesting nonvolatile processors.
Kaisheng MaXueqing LiSrivatsa Rangachar SrinivasaYongpan LiuJohn SampsonYuan XieVijaykrishnan NarayananPublished in: ASP-DAC (2017)
Keyphrases
- machine learning
- resource allocation
- parallel algorithm
- energy minimization
- parallel processing
- machine learning methods
- ambient intelligence
- resource management
- information extraction
- explanation based learning
- decision trees
- pattern recognition
- learning tasks
- data mining
- learning algorithm
- computer vision
- support vector machine
- supervised learning
- text mining
- energy consumption
- multiprocessor systems
- knowledge acquisition
- computational intelligence
- active learning
- natural language
- low frequency
- artificial intelligence
- single processor
- parallel computation
- energy saving
- feature selection
- machine learning approaches
- web resources
- metadata
- learning systems
- inductive learning
- computer science
- statistical methods
- model selection