Title :
Parallel batch pattern training algorithm for deep neural network
Author :
Turchenko, Volodymyr ; Golovko, Vladimir
Author_Institution :
Res. Inst. for Intell. Comput. Syst., Ternopil Nat. Econ. Univ., Ternopil, Ukraine
Abstract :
The development of parallel batch pattern training algorithm for deep multilayered neural network architecture and its parallelization efficiency research on many-core system are presented in this paper. The model of a deep neural network and batch pattern training algorithm are theoretically described. The algorithmic description of the parallel batch pattern training method is presented. Our results show high parallelization efficiency of the developed algorithm on many-core parallel system with 48 CPUs with the use of message passing parallelization technology.
Keywords :
message passing; multilayer perceptrons; multiprocessing systems; parallel algorithms; deep multilayered neural network architecture; deep neural network; many-core parallel system; message passing parallelization technology; parallel batch pattern training algorithm; parallelization efficiency; parallelization efficiency research; Algorithm design and analysis; Artificial neural networks; Computer architecture; Neurons; Parallel algorithms; Training; Vectors;
Conference_Titel :
High Performance Computing & Simulation (HPCS), 2014 International Conference on
Conference_Location :
Bologna
Print_ISBN :
978-1-4799-5312-7
DOI :
10.1109/HPCSim.2014.6903757
