Seminar: Building a Culture of Research Software Engineering
7:00 – 8:00 pm UTC
Speaker: Daniel Howard, NCAR/CISL
Abstract
Research Software Engineers, or RSEs, are vital to the modern research enterprise. Nearly all instrumentation and analysis workflows are dependent on software. Within HPC, modeling software itself is considered just as much the scientific instrument as the cyberinfrastructure hardware it runs on. Given that NSF NCAR plays an integral role in advancing science and technology for the public good, it is important to recognize the value people who serve in RSE roles bring towards enabling the long term sustainability, innovation, and usability of research products, such as through CISL's SEAL initiative, Software Engineering Across Labs.
This seminar aims to highlight the value RSEs bring to the scientific community and how you can get involved. Specifically, the ongoing work of the US-RSE organization, now 2,500+ strong, will be discussed. Being free to join, opportunities to engage will be shared including various volunteer opportunities and conferences. Members may also join working groups, focused on areas including code review, user experience, RSE empowerment in national labs, and others.
Given the software complexity of NSF NCAR's large modeling programs, there is significant interest towards how best to retain and cultivate essential RSE talent who build and innovate software solutions in Earth system science. Organizations must evolve their research enterprise to promote and reward these valuable contributions RSEs bring. The growing RSE community both in the US and globally can certainly support this effort.
Biography
Daniel Howard is an HPC Consultant in CISL and joined the Consulting Services Group in 2021. Previously, Daniel worked on GPU development efforts for the NRL's WaveWatch3 program and studied monsoon dynamics at Notre Dame. With a background in applied mathematics and computational science, Daniel is passionate about furthering Earth system science through best practices in research software engineering as well as the use of compute efficient mathematical toolsets deployed on modern computing hardware, which recently has been GPU processors.