NVIDIA has recently made the acquisition of SchedMD, the most popular maintainer of the open-source job management system, Slurm, in its effort to enrich its open-source software ecosystem and promote innovation in high-performance computing and artificial intelligence. The highly popular job manager, used for allocating resources in large-scale compute clusters, has been adopted on more than half the top 10 and top 100 supercomputers in the world. According to NVIDIA, it will “continue to develop and distribute Slurm as open-source, vendor-neutral software, making it widely available to and supported by the broader HPC and AI community across diverse hardware and software environments.” The acquisition was recently highlighted in the blog section on the NVIDIA website, where the corporation emphasized the importance of the job manager in managing HPC and AI jobs and its determination to maintain the openness of the product despite its acquisition of the SchedMD corporation and its technology.
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The corporation’s CEO, Danny Auble, was quoted as saying, “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,” and continued, “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.” As part of the acquisition, NVIDIA will use its accelerated computing infrastructure to fully optimize the job manager, ensuring that users efficiently allocate resources on heterogeneous infrastructure, in addition to maintaining the training, development, and full support services offered to its current customer base, including research labs, cloud providers, and enterprises in the autonomous driving, healthcare, energy, and finance industries, including autonomous driving, healthcare, energy, and finance. The acquisition demonstrates the continued effort by the corporation to develop a full AI infrastructure technology stack encompassing hardware and open-source technology and its contributions to the growth and development of the field of generative AI and high-performance computing.
