We'll provide an introduction to high-dynamic range and describe application programming techniques for HDR rendering and display on NVIDIA GPUs. We'll discuss concepts such as colorspaces, expanding chromaticity versus luminance, and scene- and display-referred imaging. For application developers, takeaways will include methods to query and set GPU and display capabilities for HDR as well as OpenGL and DirectX programming to render and display HDR imagery.

We'll explore best practices and techniques for the development of efficient GPU-based video and image- processing applications. Topics to be discussed include threading models for efficient parallelism, CPU affinity to optimize system memory and GPU locality, image segmentation for overlapped asynchronous transfers, optimal memory usage strategies to reduce expensive data movement, and image format considerations to reduce and eliminate data conversions. Single and multi-GPU systems for uncompressed real time 4K video capture, processing, display, and play-out will be considered. Takeaways should prove applicable to developers of video broadcast and digital post production systems, as well as to developers of large scale visualization systems that require video ingest.

We'll provide an introduction to High Dynamic Range (HDR) and describe application programming techniques for HDR rendering and display on NVIDIA GPUs. Concepts to be discussed include color spaces, expanding chromaticity versus luminance, and scene and display referred imaging. For application developers, takeaways will include methods to query and set GPU and display capabilities for HDR as well as OpenGL and DirectX programming to render and display HDR imagery.

This session will explore best practices and techniques for the development of efficient GPU-based video and image processing applications. Topics to be discussed include threading models for efficient parallelism, CPU affinity to optimize system memory and GPU locality, image segmentation for overlapped asynchronous transfers, optimal memory usage strategies to reduce expensive data movement, and image format considerations to reduce and eliminate data conversions. Single and multi-GPU systems for uncompressed real time 4K video capture, processing, display and play-out will be considered. Takeaways should prove applicable to developers of video broadcast and digital post production systems as well as to developers of large scale visualization systems that require video ingest.

The GPU is a high performing floating point parallel processor with extremely high memory bandwidth. This makes it ideally suited for video and image processing applications. This tutorial will present the latest techniques for optimal GPU-based video processing.

A high performance parallel floating point processor with very high memory bandwidth, the GPU is ideal for video and image processing applications. This tutorial will describe best practices for the efficient transfer of video and image data to and from the GPU as well as techniques for the optimal use of GPU resources for video and image data processing. Simple CUDA-based examples will be utilized to demonstrate concepts presented.

Have questions, concerns or thoughts about the direction of GPU-based video and image processing? Join NVIDIA experts and partners for a lively discussion of such topics as application design, multi-GPU architecture, data movement, threading, APIs, and color management as they apply to Video and Image processing applications.

This tutorial will demonstrate how video I/O devices can take advantage of the GPU Direct for Video API to optimize the data transfer performance for digital video, film and broadcast applications and computer vision applications. The GPU Direct for Video API is a technology that permits the DMA transfer of data buffers between video I/O devices and the GPU through the use of a shared system memory buffer for immediate processing by OpenGL, DirectX, CUDA and OpenCL. This direct transfer can improve synchronization and eliminate latency between video capture, GPU processing and video output.

The combination of the GPU's massively parallel compute engine with extremely high memory bandwidth and new programming paradigms such as CUDA and OpenCL have made the GPU well suited for image and video processing applications. This session will explore best practices and techniques for the development of efficient GPU-based video and image processing applications. Topics to be discussed include image segmentation and threading models for efficient parallelism, optimal memory usage strategies to reduce expensive data movement as well as multi-GPU considerations. Case studies and examples specific to video and image processing will be presented.

Have questions, concerns or thoughts about the direction of GPU-based video and image processing? Join NVIDIA engineers and product managers for a lively discussion of such topics as application design, multi-GPU architecture, data movement, threading, APIs, and color management as they apply to Video and Image processing applications.

This tutorial session teaches attendees how to program the NVIDIA Quadro Digital Video Pipeline with OpenGL. It will go in-depth into the techniques and recommended practices.

Learn how to program the NVIDIA Quadro Digital Video pipeline using Direct3D. This session will provide an overview of the SDK, discuss device control, data transfers, performance measuring and tuning, ancillary data and application design considerations.

The Quadro Professional Video Pipeline enables the binding of SDI video input and output devices directly to the GPU. This provides applications with the extraordinary capability to performing capture, processing and then output live to air or other video device completely in video memory on the GPU. Gone are the days of needing a CPU and lots of system memory for video processing. Come learn how to capture SDI video directly to GPU memory for subsequent processing as Video Textures, Video Buffer Objects or in CUDA. Once in the GPU, the video processing possibilities are endless, color grading, transcoding, compositing, restoration, effects etc. Then, output the ultimate quality imagery directly from GPU memory live to air, the network, presentation system or other video recording or display device. This session will present the Quadro Profession Video API and solution stack with case studies and usage examples.