![]() ![]() PCs that combine hardware, in the form of RTX GPUs, in addition to a "Studio Stack of specialized SDKs and dedicated Studio Drivers" from other solutions, will also be distinguished by a new RTX Studio badge. CUDA-X AI supports popular frameworks like TensorFlow and PyTorch and helps accelerate deployment with tools and APIs like ONYX and WinML.In its press conference held earlier today, Nvidia took the opportunity to unveil its new Nvidia Studio platform which aims to "dramatically improve performance and reliability for the world’s 40 million online and studio-based creatives" who rely on top-tier PC hardware to deliver their work. It also includes higher level SDKs such as NGX SDK which makes it easy to integrate AI features into creative applications with pre-trained networks. ![]() For example libraries like cuDNN and DALI help developers reduce training times while TensorRT optimizes networks and takes advantage of Tensor Cores for the fastest inference on GPUs. These libraries accelerate the entire AI pipeline from data processing to training and inference to deployment. CUDA parallel programming model for general computing on GPUs.ĬUDA-X AI is a collection of optimized libraries built on CUDA. ![]() Capture SDK capture and compress the desktop buffer for transmission or storage.GPUDirect for Video efficiently transfer video frames in and out of NVIDIA GPU memory.Optical Flow SDK highly accurate flow vectors, with robust frame-to-frame intensity variations and true object motion for tracking objects within video frames, video action recognition, stereo depth estimation and many more applications.Video Codec SDK hardware accelerated video encode and decode of industry standard formats. ![]()
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