Neural Network Exemplar Parallelization with Go
Neural Network Exemplar Parallelization with Go
This paper presents a case for exemplar parallelism of neural networks using Go as parallelization framework. Further it is shown that also limited multi-core hardware systems are feasible for these parallelization tasks, as notebooks and single board computer systems. The main question was how much speedup can be generated when using concurrent Go goroutines specifically. A simple concurrent feedforward network for MNIST digit recognition with the programming language Go was created to find the answer. The first findings when using a notebook (Lenovo Yoga 2) showed a speedup of 252% when utilizing 4 goroutines. Testing a single board computer (Banana Pi M3) delivered more convincing results: 320% with 4 goroutines, and 432% with 8 goroutines.
12 pages, to be submitted
- University of Vienna Austria
- Universität Wien Austria
- Universität Wien Austria
FOS: Computer and information sciences, D.1.3, Exemplar Parallelization, I.2.5, Go Programming Language, Computer Science - Neural and Evolutionary Computing, Backpropagation, MNIST, I.2.5; D.1.3, 102009 Computer simulation, 68T07, Computer Science - Distributed, Parallel, and Cluster Computing, 102018 Artificial neural networks, 102018 Künstliche Neuronale Netze, Neural and Evolutionary Computing (cs.NE), Distributed, Parallel, and Cluster Computing (cs.DC), 102009 Computersimulation
FOS: Computer and information sciences, D.1.3, Exemplar Parallelization, I.2.5, Go Programming Language, Computer Science - Neural and Evolutionary Computing, Backpropagation, MNIST, I.2.5; D.1.3, 102009 Computer simulation, 68T07, Computer Science - Distributed, Parallel, and Cluster Computing, 102018 Artificial neural networks, 102018 Künstliche Neuronale Netze, Neural and Evolutionary Computing (cs.NE), Distributed, Parallel, and Cluster Computing (cs.DC), 102009 Computersimulation
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