Published Online: May 04, 2019
Page range: 58 - 63
DOI: https://doi.org/10.1515/sbeef-2019-0011
Keywords
© 2019 R. Ciucu et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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.