Innovative Devops for Artificial Intelligence

Author:

Ciucu R.1,Adochiei F.C.1,Adochiei Ioana-Raluca2,Argatu F.1,Seriţan G.C.1,Enache B.1,Grigorescu S.1,Argatu Violeta Vasilica1

Affiliation:

1. University POLITEHNICA of Bucharest , Romania

2. Technical Military Academy “Ferdinand I” Bucharest Romania

Abstract

Abstract Developing Artificial Intelligence is a labor intensive task. It implies both storage and computational resources. In this paper, we present a state-of-the-art service based infrastructure for deploying, managing and serving computational models alongside their respective data-sets and virtual environments. Our architecture uses key-based values to store specific graphs and datasets into memory for fast deployment and model training, furthermore leveraging the need for manual data reduction in the drafting and retraining stages. To develop the platform, we used clustering and orchestration to set up services and containers that allow deployment within seconds. In this article, we cover high performance computing concepts such as swarming, GPU resource management for model implementation in production environments with emphasis on standardized development to reduce integration tasks and performance optimization.

Publisher

Walter de Gruyter GmbH

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1. The pipeline for the continuous development of artificial intelligence models—Current state of research and practice;Journal of Systems and Software;2023-05

2. An Overview of PAI: Distributed Machine Learning Platform;2022 IEEE 5th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC);2022-12-16

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