IONOS Cloud GPU Servers Integrations

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NVIDIA virtual GPU (vGPU) software enables powerful GPU performance for workloads ranging from graphics-rich virtual workstations to data science and AI, enabling IT to leverage the management and security benefits of virtualization as well as the performance of NVIDIA GPUs required for modern workloads. Installed on a physical GPU in a cloud or enterprise data center server, NVIDIA vGPU software creates virtual GPUs that can be shared across multiple virtual machines, and accessed by any device, anywhere. Deliver performance virtually indistinguishable from a bare metal environment. Leverage common data center management tools such as live migration. Provision GPU resources with fractional or multi-GPU virtual machine (VM) instances. Responsive to changing business requirements and remote teams.

Intel’s Gaudi software gives developers access to a comprehensive set of tools, libraries, containers, model references, and documentation that support creation, migration, optimization, and deployment of AI models on Intel® Gaudi® accelerators. It helps streamline every stage of AI development including training, fine-tuning, debugging, profiling, and performance optimization for generative AI (GenAI) and large language models (LLMs) on Gaudi hardware, whether in data centers or cloud environments. It includes up-to-date documentation with code samples, best practices, API references, and guides for efficient use of Gaudi solutions such as Gaudi 2 and Gaudi 3, and it integrates with popular frameworks and tools to support model portability and scalability. Users can access performance data to review training and inference benchmarks, utilize community and support resources, and take advantage of containers and libraries tailored to high-performance AI workloads.