Cyber Training: Pilot -- Breaking the Compute Barrier, Upskilling Agri-Food Researchers to Utilize HPC Resources

The era of “Big Data in Agriculture” is rapidly moving well beyond genomics data to encompass environmental, management and socio-economic data sourced from satellites, unmanned aerial vehicles (UAV), stationary and robot-enabled ground-based sensors, and ever more data-enabled agri-food machinery (Kamilaris et al. 2017; Shekhar et al. 2017). Leveraging high-performance computing (HPC) assets into the agri-food domain space is key to realizing a big data revolution in agriculture (EU 2018; Georgiou et al. 2020). However, there is a dearth of scientists with expertise in the agri-food and natural resource domains that have compute-to-scale capabilities enabled by HPC environments. Low adoption of HPC capabilities among agri-food researchers can be largely attributed to the real (or perceived) complexity of using HPC. The goal of this work is to onboard and upskill the agri-food workforce so they can effectively and efficiently tap the analytical horsepower of cyberinfrastructure (CI), specifically HPC, via the creation of a tiered multi-module learning curriculum tailored to CI-applications in the agri-food sciences.