This article was published in Grid Today on June 2, 2003.

One of the first applications that I see coming down the pike that brings grid computing right into our homes is in the digital entertainment segment. Today, the digital video camera is one of the fastest selling consumer electronic products. In fact, Forrester Research estimates that 92% of US households will be dabbling in digital content creation by 2005.

The proliferation of digital video cameras is, in turn, driving demand in the consumer sector for digital video manipulation products such as editors, compositing tools, DVD creation tools and the like. Many of these tools output video in a number of different formats and thus, feature native video encoding capabilities.

So, after shooting the future Palme D’Or winning masterpiece with our digital camera there begins the painful process of encoding the video stream to compress the raw digital video data in order to make transmission and storage more practical. Some of the most popular encoding schemes are those developed by the Moving Pictures Expert Group (MPEG). MPEG-4 is the most recent of the commonly implemented MPEG standards. Like other encoding schemes, the MPEG4 encoding process is computationally intensive and takes a frustratingly long time. But should it?

With 31 million homes having more than one PC and half of those homes having local area networks, it wouldn’t be too outrageous to want to distribute the encoding process to the other (presumably idle) PCs in our home.

GridIron Software, based in Ottawa, Canada is one of the companies already thinking along these same lines. They recently announced that they have successfully encoded MPEG-4 video using multiple computers with its GridIron XLR8™ software for distributed computing.

Taking advantage of the MPEG4 specification which represents content using a hierarchy of video objects, GridIron was able to treat the encoding process as an embarrassingly parallel software algorithm with a reasonable level of granularity to accommodate typical CPU and bandwidth capabilities. Their published test results indicate that a 60 second NTSC broadcast was compressed from a raw file size of 923 Mbytes to an MPEG4 encoded file of 13 Mbytes – a 98.75% reduction in size. The encoding time was reduced by a factor of 20 on a system of 12 nodes and decreased from 2 hours 33 minutes to 7 minutes and 4 seconds.

Most importantly, the test result showed a linear reduction in encoding time. So even if the video encoding process is distributed amongst just two home PCs, the encoding time will be reduced by a half.

To create our Personal Digital Entertainment Grid (PDEG) we now have to convince Sony, Panasonic, Adobe and the like to add this proven distributed computing capability to their encoding software. Hopefully they are already paying attention!

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