NVIDIA Cuda Delivers 446% Speed Increase To Pegasys Video Processing Solution

TMPGEnc 4.0 XPress Software from Pegasys Inc. Will Use NVIDIA GeForce GPUs to Rapidly Move Video across Multiple Formats.

Today, at the NVISION® 2008 conference, NVIDIA Corporation in conjunction with Pegasys Inc., makers of TMPGEnc 4.0 XPress multi-format video encoding software, showcased a technology demonstration to optimize video processing with the massively parallel architecture of the GPU.

Using NVIDIA® CUDA™ technology (a C-language programming environment for the GPU), Pegasys is taking advantage of the parallel processing capabilities of an NVIDIA GeForce® GPU to create a GPU-enabled beta version of TMPGEnc 4.0 XPress software. The software is used to dramatically increase video decode and processing speed by as much as 446% on a GeForce GPU.1

“Leveraging NVIDIA CUDA technology to accelerate our application on the GPU has dramatically improved the filtering speed of the TMPGEnc 4.0 XPress software,” said Tak EBINE, CEO, Pegasys Inc. “CUDA technology has helped us deliver this result in a relatively short development time because it is intuitive to C programmers.”

TMPGEnc 4.0 XPress software converts and compresses (encodes) all types of video files that can be played on the PC, including MPEG, AVI, WMV, DivX, FLV, as well as DVD video..Pegasys’ unique Video Mastering Engine’s interface has gained a reputation for being user-friendly, enabling easy editing and conversion of video sources.

“Pegasys’ video transcoder software has earned top ratings in Japan and overseas for its quality and ease of use,” says Patrick Beaulieu, product marketing manager, Photo/Video Technologies, NVIDIA. “The inclusion of CUDA technology into this video processing software illustrates its broad applicability and particular value in consumer, life-style applications. We’re looking forward to further collaboration and delivering the final version of the software to market.”

NVIDIA first released CUDA in 2007, providing software developers with a programming environment based on the industry-standard C-language for the easy creation of applications running on NVIDIA GPUs. Numerous commercial and scientific applications have adopted CUDA technology and now consumer applications are emerging that show considerable performance improvements using the technology. Some of the first consumer applications to market are video encoding and decoding programs, which market analysts and consumer technology advocates consider prime candidates for GPU acceleration.

NVIDIA has shipped more than 80 million CUDA-enabled GPUs into the market, creating the largest installed base of general-purpose, parallel-computing processors ever produced and the latest generation of NVIDIA GeForce GPUs offer up to 240 processor cores. Processes that can be divided into multiple elements and run in parallel can be programmed to take advantage of the massive processing potential of the GPU.

The two companies plan to continue development of the software, expanding the use of CUDA within the TMPGEnc software to include acceleration of more functions and additional video formats.