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NVIDIA Run:ai

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What is Thunder Compute?

Thunder Compute is a cutting-edge cloud service that simplifies the use of GPUs over TCP, allowing developers to easily migrate from CPU-only environments to large GPU clusters with just one command. By creating a virtual link to distant GPUs, it enables CPU-centric systems to operate as if they have access to dedicated GPU resources, while the actual GPUs are distributed across numerous machines. This method not only improves the utilization rates of GPUs but also reduces costs by allowing multiple workloads to effectively share a single GPU through intelligent memory management. Developers can kick off their projects in CPU-focused setups and effortlessly scale to extensive GPU clusters with minimal setup requirements, thereby avoiding unnecessary expenses associated with idle computational power during the development stage. Thunder Compute provides users with instant access to powerful GPU options like the NVIDIA T4, A100 40GB, and A100 80GB, all at competitive rates and with high-speed networking capabilities. This platform streamlines workflows, simplifying the process for developers to enhance their projects without the usual challenges tied to GPU oversight. As a result, users can focus more on innovation while leveraging high-performance computing resources.

What is NVIDIA Run:ai?

NVIDIA Run:ai is a powerful enterprise platform engineered to revolutionize AI workload orchestration and GPU resource management across hybrid, multi-cloud, and on-premises infrastructures. It delivers intelligent orchestration that dynamically allocates GPU resources to maximize utilization, enabling organizations to run 20 times more workloads with up to 10 times higher GPU availability compared to traditional setups. Run:ai centralizes AI infrastructure management, offering end-to-end visibility, actionable insights, and policy-driven governance to align compute resources with business objectives effectively. Built on an API-first, open architecture, the platform integrates with all major AI frameworks, machine learning tools, and third-party solutions, allowing seamless deployment flexibility. The included NVIDIA KAI Scheduler, an open-source Kubernetes scheduler, empowers developers and small teams with flexible, YAML-driven workload management. Run:ai accelerates the AI lifecycle by simplifying transitions from development to training and deployment, reducing bottlenecks, and shortening time to market. It supports diverse environments, from on-premises data centers to public clouds, ensuring AI workloads run wherever needed without disruption. The platform is part of NVIDIA's broader AI ecosystem, including NVIDIA DGX Cloud and Mission Control, offering comprehensive infrastructure and operational intelligence. By dynamically orchestrating GPU resources, Run:ai helps enterprises minimize costs, maximize ROI, and accelerate AI innovation. Overall, it empowers data scientists, engineers, and IT teams to collaborate effectively on scalable AI initiatives with unmatched efficiency and control.