NVIDIA has acquired SchedMD, the company behind the open source Slurm scheduler, pledging to keep it hardware-agnostic.
NVIDIA has acquired SchedMD, the developer of Slurm, one of the world’s most widely used open source workload schedulers for high-performance computing (HPC) and artificial intelligence workloads. Crucially, NVIDIA has confirmed that Slurm will remain open source and hardware-agnostic, ensuring continued broad access for researchers, developers, enterprises, and AI builders.
The company plans to increase investment in Slurm’s development, expanding SchedMD’s access to new systems and accelerating innovation across HPC and AI environments. Slurm is a foundational technology in global supercomputing, currently deployed in more than half of the TOP500 supercomputers worldwide, where it enables complex parallel workloads across thousands of CPUs and GPUs.
With the acquisition, NVIDIA assumes stewardship of a critical layer of the HPC and AI software stack, connecting Blackwell GPUs, InfiniBand networking, and advanced job scheduling and resource orchestration through Slurm. This tighter integration is expected to improve performance and efficiency for large language model training, generative AI workloads, mission-critical scientific simulations, and enterprise-scale AI deployments.
Danny Auble, CEO of SchedMD, said, “We’re thrilled to join forces with NVIDIA, as this acquisition is the ultimate validation of Slurm’s critical role in the world’s most demanding HPC and AI environments. NVIDIA’s deep expertise and investment in accelerated computing will enhance the development of Slurm — which will continue to be open source — to meet the demands of the next generation of AI and supercomputing.”
NVIDIA added, “Slurm, which is supported on the latest Nvidia hardware, is also part of the critical infrastructure needed for generative AI, used by foundation model developers and AI builders to manage model training and inference needs.”
Kari Briski, Vice President of Generative AI at NVIDIA, noted, “This is why we’re committed to it from a software engineering perspective.”
The move reinforces NVIDIA’s position as a leading steward of open source AI and HPC infrastructure at a time when trust, security, and openness are becoming decisive factors in global AI adoption.
