NVIDIA CUDA on Ubuntu 24.04 with Support by Easycloud

This is a repackaged open source software product wherein additional charges apply for technical support with a 24-hour response time. NVIDIA CUDA 13.2, built on a minimal Ubuntu 24.04 LTS installation, is included in this AMI, repackaged by Easycloud. It provides a complete, framework-neutral GPU compute base with the NVIDIA driver, the full CUDA Toolkit, GPU-enabled containers, and multi-node fabric libraries already assembled and validated together, deliberately engineered to let you start compiling and running accelerated workloads immediately instead of spending hours reconciling driver, toolkit, and container runtime versions.

• Ubuntu 24.04 LTS Minimal: A renowned Linux distribution celebrated for its exceptional stability, vast software repository, and strict adherence to open-source principles. Built on the solid foundation of Debian, it provides unparalleled ecosystem compatibility while delivering a clean, bloat-free, and secure enterprise-grade core.

• NVIDIA CUDA 13.2 with Driver 595.71.05 (GPU Compute Base): The full CUDA Toolkit is installed at /usr/local/cuda-13.2 with nvcc and the complete set of GPU math and profiling libraries already on PATH, so CUDA C++ and custom kernel extensions compile out of the box. The image pairs it with Docker 29.6.2 and the NVIDIA Container Toolkit 1.19.1 for GPU-enabled containers, EFA 3.0.0 with libfabric and the NCCL OFI plugin plus OpenMPI 4 and 5 for multi-node collective communication, and NVIDIA DCGM and Fabric Manager for GPU telemetry and NVSwitch-class instances. No deep learning framework is bundled, keeping the image a clean base you extend with exactly the stack your project needs.

• Framework-Neutral GPU Foundation with a Complete Toolchain: Unlike prebuilt framework images that pin you to one version of one library, this AMI ships the layer underneath them - driver, toolkit, container runtime, and fabric stack - and stops there. You choose the framework, the version, and the packaging, whether that means a pip installed training stack, a custom compiled CUDA extension, or a fleet of GPU containers, without first uninstalling somebody else's opinionated defaults or fighting a driver and toolkit mismatch.

• The Optimal AI Inference and Orchestration Foundation: By starting with a bloat-free Ubuntu 24.04 LTS installation, maximum GPU, CPU, and memory are dedicated entirely to your accelerated workloads. This makes it the perfect, conflict-free foundation for AI and HPC stacks built on CUDA, PyTorch, TensorFlow, Hugging Face models, Python, Docker, and Kubernetes. It seamlessly integrates with model serving and orchestration layers (Ollama, Open WebUI, LibreChat, Dify, Langflow, Flowise, MLflow), and serves as a rock-solid backbone for RAG pipelines, vector search, and large-scale data processing built on RAGFlow, Milvus, Chroma, PostgreSQL, Apache Spark, MinIO, Grafana, and Prometheus, ensuring your GPU infrastructure scales without limits.

• Production Ready & Expert Support: Secured with the latest OS patches. It delivers a highly stable environment, fully supported by comprehensive documentation and fast technical assistance (guaranteed 24-hour response time) to ensure your infrastructure runs smoothly without costly downtime.