The release of NVIDIA Video Codec SDK 13.0 marks a significant upgrade, adding support for the latest-generation NVIDIA Blackwell GPUs. This version brings a wealth of improvements aimed at elevating both video encoding and decoding capabilities. From enhanced compression efficiency to better throughput and encoding quality, SDK 13.0 addresses the ever-evolving demands of the video ecosystem.
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NVIDIA announces the implementation of Multi-View High Efficiency Video Coding (MV-HEVC) encoder in the latest NVIDIA Video Codec SDK release, version 13.0. This significant update marks a major leap forward in hardware-accelerated, multi-view video compression. It offers enhanced compression efficiency and quality for stereoscopic and 3D video applications as compared to simulcast encoding.
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NVIDIA recently announced a new generation of PC GPUs��the GeForce RTX 50 Series��alongside new AI-powered SDKs and tools for developers. Powered by the NVIDIA Blackwell architecture, fifth-generation Tensor Cores and fourth-generation RT Cores, the GeForce RTX 50 Series delivers breakthroughs in AI-driven rendering, including neural shaders, digital human technologies, geometry and lighting.
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Today, over 80% of internet traffic is video. This content is generated by and consumed across various devices, including IoT gadgets, smartphones, computers, and TVs. As pixel density and the number of connected devices grow, continued investment in fast, efficient, high-quality video encoding and decoding is essential. The latest NVIDIA data center GPUs, such as the NVIDIA L40S and NVIDIA��
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NVIDIA Video Codec SDK provides a comprehensive set of APIs for hardware-accelerated video encode and decode on Windows and Linux. The 12.2 release improves video quality for high-efficiency video coding (HEVC). It offers a significant reduction in bit rates, particularly for natural video content. This post details the following new features: The lookahead level can help analyze��
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Video quality metrics are used to evaluate the fidelity of video content. They provide a consistent quantitative measurement to assess the performance of the encoder. VMAF combines human vision modeling with machine learning techniques that are continuously evolving, enabling it to adapt to new content. VMAF excels in aligning with human visual perception by combining detailed analysis��
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Capturing video footage and playing games at 8K resolution with 60 frames per second (FPS) is now possible, thanks to advances in camera and display technologies. Major leading multimedia companies including RED Digital Cinema, Nikon, and Canon have already introduced 8K60 cameras for both the consumer and professional markets. On the display side, with the newest HDMI 2.1 standard��
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For over a decade, NVIDIA GPUs have been built with dedicated encoders and decoders called NVENC and NVDEC. They have a highly parallelized architecture, support popular codec formats, and provide direct access to GPU memory for optimized encode and decode operations. GPU-accelerated video means offloading your video processing to NVENCs and NVDECs, reducing CPU cycles and harnessing the more��
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Vulkan Video gives developers the choice of a powerful new API for accessing video processing acceleration. NVIDIA is expanding its commitment to Vulkan Video with tools and samples to help applications efficiently harness this significant new functionality. This post will help you discover whether Vulkan Video is right for your application��and if so, how to get started.
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AV1 is the new gold standard video format, with superior efficiency and quality compared to older H.264 and H.265 formats. It is the most recent royalty-free, efficient video encoder standardized by the Alliance for Open Media. NVIDIA Ampere architecture introduced hardware-accelerated AV1 decoding. NVIDIA Ada Lovelace architecture supports both AV1 encoding and decoding.
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DirectX 12 is a low-level programming API from Microsoft that reduces driver overhead in comparison to its predecessors. DirectX 12 provides more flexibility and fine-grained control on the underlying hardware using command queues, command lists, and so on, which results in better resource utilization. You can take advantage of these functionalities and optimize your applications and get better��
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The NVIDIA Video Codec SDK consists of GPU hardware-accelerated APIs for the following tasks: While writing an application using the NVDECODE or NVENCODE APIs, it is crucial to use video memory in an efficient way. If an application uses multiple decoders or encoder instances in parallel, it��s even more crucial because the application can get bottlenecked by video memory availability.
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All NVIDIA GPUs starting with the Kepler generation support fully accelerated hardware video encoding, and all GPUs starting with the Fermi generation support fully accelerated hardware video decoding through the NVIDIA Video Codec SDK. The NVIDIA NVENC presets design in Video Codec SDK 9.1 and earlier evolved based on various NVENC use cases, which have emerged over time.
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NVIDIA VRWorks 360 is no longer available or supported. For more information about other VRWorks products, see NVIDIA VRWorks Graphics. There are over one million VR headsets in use this year, and the popularity of 360 video is growing fast. From YouTube to Facebook, most social media platforms support 360 video and there are many cameras on the market that simplify capturing these videos.
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