NVIDIA Expands GPU Cloud Support
Published2017.12.05 12:39NVIDIA announced that it is expanding NVIDIA GPU Cloud (NGC) support on NVIDIA TITAN to hundreds of thousands of artificial intelligence developers using desktop GPUs.
NVIDIA also announced additional NGC capabilities, including new software and major updates to the NGC container registry. These enhancements provide AI developers with a broader and more powerful set of tools to enhance AI and high-performance computing (HPC) research and development.
Customers using NVIDIA Pascal architecture-based Titan GPUs can sign up for a free NGC account to access a comprehensive catalog of GPU-optimized deep learning and HPC software and tools. Other computing platforms are also supported, including NVIDIA DGX-1 and DGX Station, and NVIDIA Volta-enabled instances on Amazon EC2.
Software available through NGC's rapidly expanding container registry includes NVIDIA-optimized deep learning frameworks such as TensorFlow and PyTorch, third-party managed HPC applications, NVIDIA HPC visualization tools, and NVIDIA TensorRT 3.0, NVIDIA's programmable inference accelerator.
“We built NVIDIA GPU Cloud to give AI developers easy access to the software they need to do groundbreaking work,” said Jim McHugh, vice president of Enterprise Systems at NVIDIA. “With GPU-optimized software now available to hundreds of thousands of researchers using NVIDIA desktop GPUs, NGC will be a catalyst for breakthrough advancements in AI and a resource for developers worldwide.”
ONNX is an open format created by Facebook and Microsoft that allows developers to exchange models across different frameworks. NVIDIA has created a converter for deploying ONNX models to the TensorRT inference engine within the TensorRT development container. This allows application developers to easily deploy low-latency, high-throughput models to TensorRT.
These capabilities provide developers with a one-stop shop for software that supports all their AI computing needs, from research and application development to training and deployment.
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