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Nvidia, SchedMD deal sparks AI fears over software access

Nvidia’s December announcement that it would acquire SchedMD, the company behind open-source software Slurm, has sparked concern among some AI and supercomputing specialists that the chipmaker could steer a key tool toward its own hardware.

Slurm helps schedule computing tasks for AI model training and government supercomputers, and SchedMD said it runs about 60% of supercomputers worldwide.

Some industry participants said they are watching whether Nvidia prioritises support for its own chips over rivals such as AMD, while others see potential for faster development under Nvidia’s ownership.

Nvidia said Slurm will remain open source and vendor-neutral, and that it will continue to support customers and development efforts.

🔗 Source: Reuters

🧠 Food for thought

Implications, context, and why it matters.

This acquisition builds on Nvidia’s software push

  • Nvidia already bought Bright Computing in 2022 and announced a planned purchase of Run:ai in 2024, a Kubernetes (an open-source system for running and managing containerized applications)-based orchestrator 1.
  • Those products cover a wide span of AI operations, from provisioning servers with Base Command Manager (formerly Bright Cluster Manager) to running containerized AI jobs with Run:ai and now scheduling bare-metal jobs (workloads that run directly on physical servers, not in virtual machines) with Slurm 1.
  • Slurm was already the default scheduler inside Nvidia’s cluster management software, so the deal focuses on controlling a dependency rather than adopting new tech 1.
  • The purchase also pulls workload management into Nvidia’s “AI factory” platform, which bundles chips, networking, and orchestration software into one offering 1.

The deal tests claims of vendor neutrality in open source

  • Nvidia says it will stay neutral, while it controls an estimated 88% of the world’s graphics processing units (GPUs) and faces antitrust scrutiny over its business practices 2.
  • Slurm uses the GNU General Public License (GPL) v2.0, so the open-source community can fork the project if Nvidia appears to tilt it toward its own hardware 1.
  • That risk matters most for data centers that run mixed hardware from several vendors 3.
  • Teams could end up choosing Nvidia’s Slurm, which may fit its ecosystem better, or a community fork aimed at wider compatibility, which can add operational overhead 1.

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