Nvidia acquisition of SchedMD raises Slurm neutrality concerns

Nvidia's purchase of SchedMD has given it control of Slurm, an open-source scheduler that sits at the center of many supercomputing and large-model training systems. Researchers and engineers are watching for signs that support could tilt toward Nvidia hardware over AMD and Intel alternatives.

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.

72

Impact Score

HMRC signs £175m Quantexa deal for fraud detection

HM Revenue and Customs has signed a £175 million, 10-year agreement with Quantexa to unify fragmented data and strengthen fraud detection. The deployment is designed to automate routine work while keeping decisions transparent, auditable and subject to human approval.

Us supercomputers test new Artificial Intelligence chip suppliers

Sandia National Laboratories is evaluating chips from Israeli startup NextSilicon as major chipmakers shift their roadmaps toward Artificial Intelligence. The move reflects growing concern that mainstream processors are deprioritizing the scientific computing features government labs still need.

EU Artificial Intelligence Act amendments delay some deadlines and add new bans

A provisional Digital Omnibus on Artificial Intelligence would push back several EU Artificial Intelligence Act deadlines, refine how the law interacts with sector rules, and introduce new prohibited practices. The package also expands limited bias-testing allowances and strengthens centralized oversight for some high-impact systems.

Qwen 3.5 raises concerns about censorship embedded in model weights

A technical analysis of Alibaba Cloud’s Qwen 3.5 points to political censorship circuits embedded directly in the model’s learned weights. The findings highlight operational, compliance, and product risks for startups building on third-party Artificial Intelligence models.

Laptop prices rise as memory shortages hit PCs

Laptop prices are climbing as memory makers redirect production toward data center demand driven by Artificial Intelligence. The squeeze is spreading beyond RAM to graphics memory and SSDs, raising costs across the PC market.

Contact Us

Got questions? Use the form to contact us.

Contact Form

Clicking next sends a verification code to your email. After verifying, you can enter your message.