It is a fairly recent trend for companies to amass GPU firepower to build their own AI computing infrastructure and support the growing number of compute requests. Many recent AI tools now enable data scientists to work on data, run experiments, and train models seamlessly with the ability to submit their jobs and monitor their progress. However, for many organizations with mature supercomputing capabilities, Slurm has been the scheduling tool of choice for managing computing clusters.

Our early roadmap in 2024 has been largely focused on improving orchestration and compute infrastructure management capabilities. Last month we released a Resource Allocation Policy Management Control Center with a new, streamlined UI to help teams visualize their compute infrastructure and understand which users have access to what resources.