Perspectives on Sustainability in HPC: Current Views and Future Considerations

A part of the annual Hyperion Research HPC Multi-Client study (MCS) tracks the various application frameworks respondents use on their HPC systems to discover trends in user preference for the way applications are built and deployed, as well as trends in the functionalities users desire in their solutions and products. This year's iteration of the MCS found the most popular AI/ML/DL and data intensive frameworks were TensorFlow, PyTorch, Jupyter Notebook, SQL, CUDA, Hadoop, and Spark. This data is from an annual study that is part of the eighth edition of Hyperion Research's HPC end-user-based tracking of the HPC marketplace. It included 181 HPC end-user sites with 3,830 HPC systems.

Hyperion Research covers the worldwide market for deep learning (DL) and machine learning (ML) that is challenging enough to require the use of HPC server systems and other HPC resources (we do not cover the mainstream DL/ML market that does not use HPC, e.g. social media and large internet providers).