Singularity for Machine Learning Applications - Analysis of Performance Impact
- Resource Type
- Conference
- Authors
- Jordan, Bruce R.; Barrett, David; Burke, David; Jardin, Patrick; Littrell, Amelia; Monticciolo, Paul; Newey, Michael; Piou, Jean; Warner, Kara
- Source
- 2019 IEEE High Performance Extreme Computing Conference (HPEC) High Performance Extreme Computing Conference (HPEC), 2019 IEEE. :1-6 Sep, 2019
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Containers
Graphics processing units
Training
Machine learning
Neural networks
Computational modeling
Libraries
containers
hpc
singularity
docker
machine learning
deep learning
neural network
- Language
- ISSN
- 2643-1971
Software deployments in general, and deep learning applications in particular, suffer from difficulty in reproducible results. The use of containers to mitigate these issues is becoming a common practice. Singularity is a container technology which targets the unique issues present in High Performance Computing (HPC) Centers. This paper characterizes the impact of using Singularity for both Training and Inference on deep learning applications.