Question: Can you suggest a platform that offers scalable GPU clusters with pre-installed ML frameworks like TensorFlow and PyTorch?

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Lambda

If you want a platform that comes with pre-installed ML frameworks like TensorFlow and PyTorch and has a scalable GPU cluster, Lambda could be the ticket. This cloud computing service lets you provision on-demand and reserved NVIDIA GPU instances and clusters for training and inferencing AI. It supports a range of GPUs, including NVIDIA H100, H200 and GH200 Tensor Core GPUs, and comes with preconfigured ML environments with Ubuntu, TensorFlow, PyTorch, CUDA and cuDNN. The service also comes with one-click Jupyter access, scalable file systems and transparent pricing with flexible billing options.

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RunPod

Another good choice is RunPod, a cloud service for building, training and running AI models. It lets you spin up GPU pods instantly with a range of GPUs, including MI300X and H100 PCIe. RunPod offers serverless ML inference with autoscaling and job queuing, instant hot-reloading for local changes, and more than 50 preconfigured templates for frameworks like PyTorch and TensorFlow. The service also comes with a CLI tool for easy provisioning and deployment, with pricing that varies depending on the type of GPU instance and usage.

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Salad

If you're looking for something more economical, Salad offers a cloud-based service for deploying and managing AI/ML production models at scale. It taps into thousands of consumer GPUs around the world to offer scalable and highly available solutions. Salad supports a range of GPU-hungry workloads and integrates with container registries. The service also offers a global edge network, on-demand elasticity and multi-cloud support, with pricing starting at $0.02 per hour for GTX 1650 GPUs.

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Anyscale

Last, Anyscale is a more mature service for building, deploying and scaling AI applications. Based on the open-source Ray framework, Anyscale supports a broad range of AI models and offers features like workload scheduling, cloud flexibility and heterogeneous node control. The service is designed to optimize resource use with GPU and CPU fractioning, and offers native integration with popular IDEs and persisted storage. Anyscale offers flexible pricing with a free tier and customizable plans for bigger businesses.

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