Nvidia acquisition of SchedMD raises Slurm neutrality concerns

Nvidia’s December acquisition of SchedMD has handed it control of Slurm, the open-source scheduling software that runs around 60% of the world’s supercomputers and underpins large-language-model training workloads at labs including Anthropic, Meta and Mistral. The deal has raised concern among Artificial Intelligence specialists and high performance computing engineers that Nvidia could gradually shape a critical layer of infrastructure to favor its own chips and networking technology.

Slurm is presented as a strategic control point because it turns clusters of GPUs into usable systems for supercomputing and model training. Its role spans workloads such as weather forecasting, nuclear weapons design, and frontier model development, making vendor neutrality especially important. One key test will be how quickly Nvidia integrates AMD’s upcoming chips into Slurm compared with how quickly it adds support for its own InfiniBand networking and other Nvidia-specific hardware. Intersect360 Research CEO Addison Snell warned that Nvidia “could take what’s a common open-source tool and make it so that it works better or exclusively for its own parts.”

The concern is reinforced by Nvidia’s 2022 acquisition of Bright Computing, a cluster-management company. Artificial Intelligence industry sources cited by Reuters said Bright’s software became “optimised for Nvidia, creating a performance penalty for users of other chips without additional work”. Nvidia disputed that characterization and said Bright supports “nearly any” CPU or GPU cluster. The latest acquisition has therefore prompted scrutiny over whether a similar pattern could emerge around Slurm.

OpenAI is noted as an exception because it does not use Slurm and instead relies on Google-derived scheduling. That limits Nvidia’s leverage to the broader frontier lab and high performance computing ecosystem rather than the entire industry. For universities, national supercomputing facilities, and enterprises running mixed-vendor GPU clusters, the immediate issue is contingency planning. Slurm remains open-source, so a fork is technically possible, but “it takes effort to produce fully working software”, making governance and development patterns important signals to monitor.