The Centre for Genomic Regulation (CRG) is the largest genomic research center in Spain and among the largest in Europe. The diversity of research in human, animal, and plant genome studies, coupled with a broad collaborative approach that requires the sharing of data and resources, creates a variety of computational and data management challenges.
For Paolo Di Tomasso, a software engineer in the Comparative Bioinformatics Group at CRG, the best way to address current and future challenges, especially when using the center’s own 2,000-core cluster, the Mare Nostrum supercomputer at BSC, or the cloud – all the while preserving reproducibility – was to mesh Univa’s Grid Engine workload scheduler with Docker containers and thereby automate a large part of the process of submitting and managing jobs.
The ability to virtualize a single process or the execution of a bunch of applications in a Docker container yielded reduced configuration and deployment problems and produced an increase in task run times and ease of replication for CRG. “Running jobs in a Docker container combined with Univa Grid Engine resulted in minimal performance loss of execution time as well as in simplified and optimized Docker image deployments,” stated Tomasso.
Click here to download the Benchmark Report: Univa Grid Engine, Nextflow, and Docker for running Genomic Analysis Workflows