Challenges and Opportunities in Enhancing Weather, Water, and Climate HPC Systems

The purpose of this study was to gain a better understanding of the activities and use behaviors of AI users leveraging HPC-centric cloud resources. Key goals included creating a picture of user goals for AI integration, their current and planned methodologies, budget allocations, model lifecycle expectations, and preferred hardware and cloud platforms for their HPC-centric AI endeavors. This study also sought to gain a greater understanding of inferencing activities among organizations currently or planning to integrate AI into their workflow. Highlights from the study results include: •     Public cloud resources are considered a valuable asset in exploration and integration of AI into HPC or compute-intensive environments. •     Respondent organizations are leveraging a wide range of public cloud offerings. •     There are numerous architectures and device types currently used to meet inferencing needs. •     There is a plethora of desired qualities for the future of cloud computing expected by current and prospective AI users. •     Budgets among respondent organizations are expected to increase to meet training and inference needs, both in the cloud and on-premises.

Dating back to 1986, ISC is the world’s longest running and Europe’s foremost HPC conference. In June 2020, ISC held ISC2020 Digital, an online event for the HPC community. This update summarizes a presentation from that digital conference entitled, DEEP Framework for Deep Learning: Deep learning on a Cloud and HPC environment, given by Valentin Kozlov, a researcher from the Karlsruhe Institute of Technology.