I believe the idiosyncrasies of most HPC technologies represent the major road block to their adoption (in any language or system). HPC technologies are often difficult to set up, use, and manage. They often rely on frequently changing and complex software library dependencies, and sometimes highly specific library versions. Managing all this boils down to spending more time on system administration, and less time on research.
How do we make things easier? One approach to help accelerate the adoption of HPC technology by the R community uses Singularity, a modern application containerization technique suited to HPC.
Join Our Mailing List
Overview With CentOS 7 reaching end of life on June 30th, 2024 and CentOS 8 already discontinued in favor of CentOS Stream, users of open source SingularityCE might find themselves in a situation where a migration to another open source operating system is necessary....
With the ever increasing adoption of AI techniques in scientific research, as well as growing use of accelerators for traditional numerical workloads, easy access to GPUs and other devices in HPC environments is critical.The 4.0 release of the SingularityCE container...
Transforming Alzheimer’s Research with Singularity Containers: A Milestone in Scientific Reproducibility
Addressing The Grand Challenges of Our Time Through Singularity Container TechnologyAt Sylabs, our mission and vision aren't just statements on a wall, they're an ethos we embody daily. We're committed to facilitating cutting-edge research that seeks to address...