Implementing deep neural networks for financial market prediction on the intel xeon phi

Matthew Dixon, Diego Klabjan, Jin Hoon Bang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

Deep neural networks (DNNs) are powerful types of artificial neural networks (ANNs) that use several hidden layers. They have recently gained considerable attention in the speech transcription and image recognition community (Krizhevsky et al., 2012) for their superior predictive prop- erties including robustness to overfitting. However their application to financial market prediction has not been pre- viously researched, partly because of their computational complexity. This paper describes the application of DNNs to predicting financial market movement directions. A critical step in the viability of the approach in practice is the ability to effectively deploy the algorithm on general purpose high performance computing infrastructure. Using an Intel Xeon Phi co-processor with 61 cores, we describe the process for efficient implementation of the batched stochastic gradient descent algorithm and demonstrate a 11.4x speedup on the Intel Xeon Phi over a serial implementation on the Intel Xeon.

Original languageEnglish (US)
Title of host publicationProceedings of WHPCF 2015
Subtitle of host publication8th Workshop on High Performance Computational Finance - Held in conjunction with SC 2015: The International Conference for High Performance Computing, Networking, Storage and Analysis
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450340151
DOIs
StatePublished - Nov 15 2015
Event8th Workshop on High Performance Computational Finance, WHPCF 2015 - Austin, United States
Duration: Nov 15 2015Nov 20 2015

Other

Other8th Workshop on High Performance Computational Finance, WHPCF 2015
CountryUnited States
CityAustin
Period11/15/1511/20/15

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Software

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    Dixon, M., Klabjan, D., & Bang, J. H. (2015). Implementing deep neural networks for financial market prediction on the intel xeon phi. In Proceedings of WHPCF 2015: 8th Workshop on High Performance Computational Finance - Held in conjunction with SC 2015: The International Conference for High Performance Computing, Networking, Storage and Analysis [a6] Association for Computing Machinery, Inc. https://doi.org/10.1145/2830556.2830562