Practice and Experience in using Parallel and Scalable Machine Learning with Heterogenous Modular Supercomputing Architectures.
Morris RiedelRocco SedonaChadi BarakatPetur EinarssonReza HassanianGabriele CavallaroMatthias BookHelmut NeukirchenAndreas LintermannPublished in: IPDPS Workshops (2021)
Keyphrases
- support vector machine
- machine learning
- feature selection
- parallel computing
- knowledge acquisition
- high performance computing
- pattern recognition
- data mining
- parallel architectures
- machine learning methods
- learning algorithm
- distributed memory
- model selection
- multi core processors
- communication skills
- computer vision
- reinforcement learning
- parallel computers
- parallel processing
- grid computing
- varying degrees
- parallel implementation
- computer architecture
- practical experiences
- multi processor
- national laboratory
- highly scalable
- databases
- massively parallel
- explanation based learning
- shared memory
- user experience
- learning tasks
- learning systems
- text mining
- natural language processing
- knowledge representation
- data analysis
- decision trees