JAKARTA - Nvidia officially acquired SchedMD, a US-based AI software provider. This is a strategic move to strengthen the open-source technology push and maintain its dominance in the global artificial intelligence ecosystem.
SchedMD is known as the main developer of Slurm, an open-source workload management system that is the backbone of large-scale computing scheduling in data centers, especially for high-performance computing and AI.
Slurm plays a crucial role in organizing the training and inference of AI models that can suck in massive amounts of server capacity. So far, the software is free to use, while SchedMD provides technical support and maintenance services.
This acquisition confirms that the AI war is no longer just about chips, but also about software and orchestration. For Nvidia, Slurm is a strategic complement to CUDA, a proprietary platform that has become the de facto standard for AI developers around the world.
In its official statement, Nvidia did not disclose the value of the transaction, but confirmed its commitment to keeping Slurm licensed open-source. The company calls Slurm a critical infrastructure in the era of generative AI, used by basic model developers and AI builders to manage training processes to large-scale inference.
SchedMD CEO Danny Auble welcomed the acquisition. He assessed Nvidia's expertise in accelerated computing will accelerate the development of Slurm to be able to meet the needs of the next generation of AI and supercomputers, without abandoning the principle of source code openness.
This announcement coincides with the launch of Nvidia's latest family of open-source AI models, Nemotron 3, which is claimed to be faster, more efficient, and smarter than previous generations.
The combination of the SchedMD acquisition and the launch of Nemotron 3 sends a clear signal: Nvidia is locking down its ecosystem from hardware to software, while preparing for a wave of new open-source competitors, especially from China's AI labs.
Founded in 2010 in California, SchedMD currently has around 40 employees. Despite its small size, its role is big. In the modern world of AI, organizing computing is often as important as creating the model. Nvidia seems to understand this very well: AI is not just about how fast the chip works, but also how neatly the work is scheduled.
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