Closing the gap between HPC and AI

HPC and AI are converging, whether your organization has planned for it or not. Simulation teams and model-building teams are landing on the same infrastructure, and the habits that kept HPC running for decades — untracked jobs, no reproducibility, no audit trail — don't hold up once that work feeds directly into governed AI pipelines. This guide breaks down what's driving the convergence, the governance gap it creates, and what data science leaders need in place before the two worlds collide.

You'll learn how Slurm became the de facto standard sitting between both worlds, see what a mixed simulation-and-training pipeline looks like in practice, and get a clear checklist for what a truly unified platform requires — from job accounting and audit trails to running fully air-gapped for regulated environments. Download the whitepaper to see how to bring HPC under the same governance as the rest of your AI work, without asking researchers to change how they work.