Description
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.
