NVIDIA has decided that NVIDIA GPUDirect for Video Technology, which allows developers to use more efficient parallel processing in graphics processing unit during image processing. GPU Direct gives more realistic graphical effects in live broadcasts. New technology, which was already presented in June, gives better communication between Quadro, Tesla graphics cards and video devices by reducing latency.
New GPUDirect technology is a new method of video transmission to graphics processing unit. Developers can write better and more efficient software for such processor. Main advantage of GPUDirect is full synchronization of input/output devices. Before this technology was available professional had to work with latency of 10 frames.
Whether racing to model fast-moving financial markets, exploring mountains of geological data, or researching solutions to complex scientific problems, you need a computing platform that delivers the highest throughput and lowest latency possible. GPU-accelerated clusters and workstations are widely recognized for providing the tremendous horsepower required to perform compute-intensive workloads, and your applications can achieve even faster results with NVIDIA GPUDirect™.
First released in June 2010, GPUDirect is supported by InfiniBand solutions available from Mellanox and QLogic, and other vendors are adding support for GPUDirect in their hardware and software products now.
Using GPUDirect, 3rd party network adapters, solid-state drives (SSDs) and other devices can directly read and write CUDA host memory, eliminating unnecessary system memory copies and CPU overhead, resulting in significant performance improvements in data transfer times on NVIDIA Tesla™ and Quadro™ products.
GPUDirect also includes support for peer-to-peer (P2P) DMA transfers directly between GPUs and NUMA-style direct access to GPU memory from other GPUs. These capabilities lay the foundation for direct P2P communication between GPUs and other devices in a future release.
- Accelerated communication with network and storage devices
- Avoid unnecessary system memory copies and CPU overhead by copying data directly to/from pinned CUDA host memory
- Peer-to-Peer Transfers between GPUs
- Use high-speed DMA transfers to copy data from one GPU directly to another GPU in the same system
- Peer-to-Peer memory access
- Optimize communication between GPUs using NUMA-style access to memory on other GPUs from within CUDA kernels
- GPUDirect for Video
- Optimized pipeline for frame-based devices such as frame grabbers, video switchers, HD-SDI capture, and CameraLink devices.