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NVIDIA Acquires SchedMD to Bring Slurm Into AI and HPC

NVIDIA announced the acquisition of SchedMD, the primary developer of Slurm, the widely used open-source workload manager for high-performance computing and AI clusters. The deal brings one of the most critical pieces of HPC infrastructure under NVIDIA’s software umbrella as AI and supercomputing systems scale in size, complexity, and power consumption.

Slurm handles queuing, scheduling, and resource allocation across large clusters running parallel workloads. As AI training and inference jobs expand across tens of thousands of GPUs and mixed accelerator environments, efficient utilization of compute resources has become a central architectural challenge. Slurm already plays a foundational role in this environment, with deployments across more than half of the top 10 and top 100 systems on the TOP500 list of supercomputers.

NVIDIA said it will continue to develop and distribute Slurm as open-source, vendor-neutral software, supporting heterogeneous hardware and software environments. The company plans to accelerate Slurm innovation by expanding SchedMD’s access to new NVIDIA-based systems, while maintaining broad ecosystem support for customers running mixed CPU, GPU, and accelerator clusters across on-premises, cloud, and research environments.

“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,” said Danny Auble, CEO of SchedMD. “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.”

🌐  Analysis

The acquisition aligns NVIDIA more tightly with the software control plane that governs large-scale AI and HPC clusters, complementing its growing portfolio that spans GPUs, networking, and system software. As competitors such as AMD, Intel, and hyperscalers continue investing in alternative schedulers and cloud-native orchestration layers, NVIDIA’s stewardship of Slurm positions it to influence how heterogeneous AI infrastructure is deployed and optimized across the industry.

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