HD Video Decoding on GPUs with VLC 1.1.0

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HD Video Decoding on GPUs with VLC 1.1.0
by Ganesh T S on 6/25/2010 4:35:00 AM
Posted in Home Theater , HTPC

It is time for HTPC enthusiasts to rejoice! Videolan announced the availability of VLC 1.1.0 a couple of days back. VLC's popularity soared in the mid-2000s when standard definition videos were all the craze, and CPUs were powerful enough to easily decode them. Over the last few years, many people have built up a big library of high definition videos, and one of the complaints against VLC was the fact that all the inbuilt codecs relied completely on the CPU horsepower for decoding. Even the most powerful modern day multi-core processors have trouble decoding HD videos.

HTPC users with GPUs capable of accelerating HD video decode initially relied on the bundled software (from Cyberlink / ArcSoft / Corel). However, the bloatware and container restrictions imposed by these players led enthusiasts to other open source projects such as Media Player Classic - Home Cinema (MPC-HC). These tapped into the GPU capabilities using DXVA / DXVA2 APIs on Windows and VAAPI on Linux. The extent of support provided in these APIs depended on the GPU vendor. Historically, Nvidia has provided much better support than ATI, while Intel was lagging behind for quite some time till late last year. This is evident from one of the popular blog posts used as a reference by people wanting to get DXVA working on their GPUs. Users of MPC-HC also had to deal with external codec packs such as CCCP. In addition, a large number of options had to be set up correctly in order to get GPU decoding to work. There was an urgent need for the big player in this space to come to the party, and Videolan has done that exactly with the 1.1.0 release of the VLC Media Player.

However, all is not well yet in VLC land. Videolan supplied the caveat that the experimental GPU acceleration would work only on Nvidia GPUs as of now. They cited troubles with the ATI drivers and the lack of access to a Intel IGP as the reason for not being able to support non-Nvidia platforms with confidence. With a core developer team of just 5 people, coupled with the fact that most of them are not Windows developers, it is hard to find fault with that reasoning.

At the end of our testing, we found out some unexpected good things. However, there was some disappointment as well. Before going into the details, let us take a look at the test bed and test suite we used for the analysis.