Details of Award
NERC Reference : NE/X006999/1
Getting started with High Performance Computing: FAIR training for environmental scientists
Training Grant Award
- Lead Supervisor:
- - E Rand, University of York, Biology
- Grant held at:
- University of York, Biology
- Science Area:
- Atmospheric
- Earth
- Freshwater
- Marine
- Terrestrial
- Overall Classification:
- Atmospheric
- ENRIs:
- Biodiversity
- Environmental Risks and Hazards
- Global Change
- Natural Resource Management
- Pollution and Waste
- Science Topics:
- Bioinformatics
- Environmental Informatics
- High Performance Computing
- Tools for the biosciences
- Abstract:
- We will develop resources to train researchers in the reproducible analysis of large environmental datasets with high performance computing (HPC). We aim to make working with HPC accessible to ECRs with no prior experience of remote computing, the command-line interface (CLI) or project organisation. Our emphasis will be best practice in project organisation, documentation with good quality metadata and the reproducibility of analyses on HPC with scripting. Environmental science attracts researchers from a range of backgrounds including the life and social sciences who may have no previous experience of the skills needed for analyses on high performance computing infrastructure. There is a steep learning curve made difficult by the need to install packages with multiple dependencies for users that have a limited understanding of filesystems or the command line. We will simplify this for learners by using cloud-based containerised instances (Amazon Web Services, AWS) with data and software preinstalled. This will allow learners to develop some skills and confidence with HPC to achieve data analysis and visualisation tasks without first having to manage their computing environment. Our training materials and delivery are designed with accessibility and sustainability at the forefront. Our hands-on workshop will be delivered online over four weeks with each weekly session being 2-3 hours long and timed to avoid the school run. Participants will be provided a second monitor and headset to maximise their ability to interact with the trainers, and each other, while participating. In addition, there will be a "supported self-study" mode of participation for those whose schedule prevents attendance at the workshop. Workshop and self-studying participants will be fully integrated. A dedicated Community manager will foster interaction between workshop participants, self-studying learners and trainers using an online forum. To our knowledge there are no courses that support synchronous and asynchronous engagement as a learning community in reproducible handling and visualising of large environmental datasets on HPC. To further remove barriers to participation, we will provide Diversity scholarships to cover childcare or support needs. Our resources will be Findable, Accessible, Interoperable and Reusable (FAIR) so that others may self-study them after the end of this project. In addition, we will include teaching notes to enable other instructors to deliver the workshop. Our team has established protocols for delivering online training using AWS instances, for making training resources FAIR and for developing communities. We have a track record of providing well-received HPC training for researchers in interdisciplinary fields.
- NERC Reference:
- NE/X006999/1
- Grant Stage:
- Completed
- Scheme:
- Doctoral Training
- Grant Status:
- Closed
- Programme:
- Advanced Training
This training grant award has a total value of £29,514
FDAB - Financial Details (Award breakdown by headings)
| Total - Other Costs |
|---|
| £29,514 |
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