Machine learning based predictive models in mobile platforms using CPU-GPU

Javad Sohankar, Madhurima Pore, Ayan Banerjee, Koosha Sadeghi, Sandeep K.S. Gupta

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

Abstract

Physiological signal based interactive systems communicate with human users in real time manner. However, the large size of data generated by sensors, complex computations necessary for processing physiological signals (e.g. machine learning algorithms) hamper the real-time performance of such systems. The main challenges to overcome these issues are limited computational capability of mobile platform and also the latency of offloading computation to servers. A solution is to use predictive models to access future data in order to improve the response time of the system. However, these predictive models have complex computation which result in high execution times on mobile phone that interferes with real time performance. With the advent of OpenCL enabled GPUs in mobile platform, there is a potential of developing general purpose applications (e.g. predictive models) which offload complex computation to GPUs. Although the use of GPUs will reduce the computation time in physiological signal based mobile systems, satisfying the time constraints of these systems can be challenging. That is due to the dynamically changing nature of physiological data which requires frequent updating of physiological models in the system. In this work, computations of a predictive model for brain signals is offloaded to mobile phone GPU. The evaluation of the performance shows that GPU can outperform CPU in mobile platform for general purpose computing.

Original languageEnglish (US)
Title of host publication2020 7th International Conference on Internet of Things
Subtitle of host publicationSystems, Management and Security, IOTSMS 2020
EditorsLarbi Boubchir, Elhadj Benkhelifa, Yaser Jararweh, Imad Saleh
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9780738124605
DOIs
StatePublished - Dec 14 2020
Event7th International Conference on Internet of Things: Systems, Management and Security, IOTSMS 2020 - Virtual, Paris, France
Duration: Dec 14 2020Dec 16 2020

Publication series

Name2020 7th International Conference on Internet of Things: Systems, Management and Security, IOTSMS 2020

Conference

Conference7th International Conference on Internet of Things: Systems, Management and Security, IOTSMS 2020
CountryFrance
CityVirtual, Paris
Period12/14/2012/16/20

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems and Management
  • Energy Engineering and Power Technology

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