In the process of researching the latest Nvidia graphics cards, I came across a technology which has had bits of coverage over the past couple of years but never enough to make me look into it any further and with that I found Badaboom which encodes and transcodes using the power of your Nvidia graphics card. GPU encoding and transcoding not only allow you to use your computer as normal while encoding, its also meens its done at blistering speeds and can reduce encode times by upto 20x.

Eager to to see what this old & fairly outdated 8600 GTS could do, I downloaded Badaboom and was suprised to see a ‘Zune’ output option. Therefore I decided to to transcode some files which I had planned to put on my Zune before I head on holiday next week rather than just a few random media files I had kicking about.

Nvidia CUDA GPU

The CUDA-enabled graphics cards which Badaboom requires one of are pretty common these days and if you’ve built or bought a PC in the last couple of years there is a good chance you have one. All the GeForce 8, 9, 100 & 200-series GPUs which have a minimum of 256MB of local graphics memory should be CUDA-enabled, as well as Tesla, Quadro, Ion and Mobile technology. For full compatability assurance please check Nvidia CUDA Products. Theres a wide range of CUDA cards from very budget ones such as an Nvidia 8400 GS to the high performance GTX 295.

Not for Zune 30?

Nope, the Zune 30 does not and probably never will support MP4 playback. At this time badaboom only converts to MP4 so your out of luck until Elemental Technologies manage to develop transcoding and encoding to WMV.

Supported Formats

Currently format support is limited but hopefully will be improved in the future.

Input and output resolutions must be below 1920 x 1080 which shouldn’t be a problem since nothing is available larger yet.

What I Tested & My Results

I decided to test an AVI of Catch Me If You Can which was 768mb and an MKV containing a 720p MP4 of Transporter with DTS Audio which was 4.37gb. Suprisingly the DTS Audio worked even though it is not stated as being supported by badaboom. Both films transcoded at great speeds without using up too much CPU usage so that I could continue with whatever I wanted.

Catch Me If You Can – AVI

Catch Me If You Can used an average of 25% CPU and only hit 40% CPU at one point in the film. The CPU is being used due to the graphics card not being able to decode and encode at the same time, so the CPU is used to decode. I’m not too sure whether this is because currently the GPU’s can’t decode certain formats or whether its just because this older card doesn’t support both at once. The transcode only took 18 minutes, 52 seconds and averaged at 178.8 FPS (Frames per Second).

Transporter – MKV

Transporter used an average of 40% CPU throughout the film which once again was being used to decode the video, while the GPU did all the work to encode it and at no point did the CPU usage spike. The transcode was complete in 38 minutes, 43 seconds which is an average of 57.3 FPS. This certainly took longer than the standard definition transcode, the FPS being transcoded was just over 1/3 of Catch Me If You Can. However this is understandable, since the 720p film has about 3x as many pixels as the standard definition film.

Conclusion

Overall i’m really impressed with badaboom – as a first version its a great program. The formats that it does support work extremely well, the results looks brilliant and can’t be beaten and its all done extremely quickly. Its a shame it has a few let downs such as the lack of format choices to output to (making it useless for Zune 30) and the fact that I could not find any subtitle support for it. However its still a great program and I shouldn’t let this small things put it down, so if your a 2nd Gen Zune owner or future Zune HD owner who has a CUDA-enabled GPU and is looking for an encoder / transcoder I highly advise you look into badaboom.

I really hope Elemental Technologies continue to develop this product and hopefully I’ll be able to test these files again on a newer CUDA GPU in the future to compare results.