NVIDIA has announced its intention to acquire Run:ai, a provider of Kubernetes-based workload management and orchestration software, to help customers optimize their AI computing resources more effectively. With AI deployments becoming increasingly complex, spanning across cloud, edge, and on-premises data centers, managing and orchestrating diverse workloads such as generative AI and recommender systems requires sophisticated scheduling to maximize system-level performance.
Run:ai offers enterprise customers a platform to manage and optimize their compute infrastructure, whether it’s on-premises, in the cloud, or in hybrid environments. Leveraging Kubernetes as the orchestration layer, Run:ai supports various Kubernetes variants and seamlessly integrates with third-party AI tools and frameworks. Its clientele includes some of the world’s largest enterprises across multiple industries, utilizing the platform to manage data-center-scale GPU clusters.
The Run:ai platform empowers AI developers and teams with a centralized interface to oversee shared compute infrastructure, facilitating easier and faster access to complex AI workloads. Additionally, it provides features for user management, team organization, resource allocation, and monitoring of resource usage, catering to various GPU configurations and optimizing GPU cluster resource utilization.
NVIDIA intends to maintain Run:ai’s products under the same business model in the immediate future, continuing to invest in the platform’s roadmap. This includes enabling integration with NVIDIA’s AI platforms like NVIDIA DGX Cloud, an AI platform designed in collaboration with leading clouds, offering a comprehensive service optimized for generative AI. Customers utilizing NVIDIA’s accelerated computing platforms such as DGX and DGX Cloud will benefit from Run:ai’s capabilities, particularly for large language model deployments.
By combining NVIDIA’s accelerated computing platform with Run:ai’s orchestration capabilities, customers will have access to a unified fabric for GPU solutions across different environments. This integration aims to enhance GPU utilization, streamline GPU infrastructure management, and provide greater flexibility through an open architecture. Additionally, the collaboration between NVIDIA and Run:ai will continue to support a broad ecosystem of third-party solutions, offering customers choice and flexibility in their AI computing needs.
