Performance Prediction of GPU-based Deep Learning Applications

Eugenio Gianniti; Li Zhang; Danilo Ardagna

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Paper

Performance Prediction of GPU-based Deep Learning Applications

Topics: Cloud Applications Performance and Monitoring; Cloud Cost Analysis; High Performance Computing Cloud Applications ; Use Cases , Experiences with HPC Clouds

In Proceedings of the 9th International Conference on Cloud Computing and Services Science CLOSER - Volume 1, 279-286, 2019 , Heraklion, Crete, Greece

Authors: Eugenio Gianniti ¹ ; Li Zhang ² and Danilo Ardagna ¹

Affiliations: ¹ Dip. Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan and Italy ; ² IBM Research, Yorktown Heights, N.Y. and U.S.A.

Keyword(s): Convolutional Neural Networks, Deep Learning, Performance Prediction, General Purpose GPUs.

Abstract: Recent years saw an increasing success in the application of deep learning methods across various domains and for tackling different problems, ranging from image recognition and classification to text processing and speech recognition. In this paper we propose, discuss, and validate a black box approach to model the execution time for training convolutional neural networks (CNNs), with a particular focus on deployments on general purpose graphics processing units (GPGPUs). We demonstrate that our approach is generally applicable to a variety of CNN models and different types of GPGPUs with high accuracy. The proposed method can support with great precision (within 5% average percentage error) the management of production environments.

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Paper citation in several formats:

Gianniti, E.; Zhang, L. and Ardagna, D. (2019). Performance Prediction of GPU-based Deep Learning Applications. In Proceedings of the 9th International Conference on Cloud Computing and Services Science - CLOSER; ISBN 978-989-758-365-0; ISSN 2184-5042, SciTePress, pages 279-286. DOI: 10.5220/0007681802790286

@conference{closer19,
author={Eugenio Gianniti. and Li Zhang. and Danilo Ardagna.},
title={Performance Prediction of GPU-based Deep Learning Applications},
booktitle={Proceedings of the 9th International Conference on Cloud Computing and Services Science - CLOSER},
year={2019},
pages={279-286},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007681802790286},
isbn={978-989-758-365-0},
issn={2184-5042},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Cloud Computing and Services Science - CLOSER
TI - Performance Prediction of GPU-based Deep Learning Applications
SN - 978-989-758-365-0
IS - 2184-5042
AU - Gianniti, E.
AU - Zhang, L.
AU - Ardagna, D.
PY - 2019
SP - 279
EP - 286
DO - 10.5220/0007681802790286
PB - SciTePress