Posts Tagged ‘quicksync’
For now, use Handbrake for simple, effective encodes. Arcsoft or Xilisoft might be worth a look if you know you’ll be using CUDA or Quick Sync and have no plans for any demanding work. Avoid MediaEspresso entirely.
via By Joel Hruska @ ExtremeTech The wretched state of GPU transcoding – Slideshow | ExtremeTech.
Joel Hruska does a great survey of GPU enabled video encoders. He even goes back to the original Avivo and Badaboom encoders put out by AMD and nVidia when they were promoting GPU accelerated video encoding. Sadly the hype doesn’t live up to the results. Even Intel’s most recent competitor in the race, QuickSync, is left wanting. HandBrake appears to be the best option for most people and the most reliable and repeatable in the results it gives.
Ideally the maintainers of the HandBrake project might get a boost by starting up a fork of the source code that has Intel QuickSync support. There’s no indication now that that everyone is interested in proprietary Intel technology like QuickSynch as expressed in this article from Anandtech. OpenCL seems like a more attractive option for the Open Source community at large. So the OpenCL/HandBrake development is at least a little encouraging. Still as Joel Hruska points out the CPU still is the best option for encoding high quality at smaller frame sizes, it just beats the pants off all the GPU accelerated options available to date.
- AnandTech – Testing OpenCL Accelerated Handbrake with AMD’s Trinity (carpetbomberz.com)
- The Wretched State of GPU Transcoding (tech.slashdot.org)
- Lucid Demonstrates XLR8 Frame Rate Boosting Technology (tomshardware.com)
AMD, and NVIDIA before it, has been trying to convince us of the usefulness of its GPUs for general purpose applications for years now. For a while it seemed as if video transcoding would be the killer application for GPUs, that was until Intel’s Quick Sync showed up last year.
There’s a lot to talk about when it comes to accelerated video transcoding, really. Not the least of which is HandBrake’s dominance generally for anyone doing small scale size reductions of their DVD collections for transport on mobile devices. We owe it all to the open source x264 codec and all the programmers who have contributed to it over the years, standing on one another’s shoulders allowing us to effortlessly encode or transcode gigabytes of video to manageable sizes. But Intel has attempted to rock the boat by inserting itself into the fray by tooling its QuickSync technology for accelerating the compression and decompression of video frames. However it is a proprietary path pursued by a few small scale software vendors. And it prompts the question, when is open source going to benefit from the proprietary Intel QuickSync technology? Maybe its going to take a long time. Maybe it won’t happen at all. Lucky for the HandBrake users in the audience some attempt is being made now to re-engineer the x264 codec to take advantage of any OpenCL compliant hardware on a given computer.
- What We’ve Been Waiting For: Testing OpenCL Accelerated Handbrake with AMD’s Trinity (anandtech.com)
- Photoshop CS6 Gives ‘Fangs’ to your GPU (barefeats.com)
Similarly disappointing for everyone who isnt Intel, its been more than a year after Sandy Bridges launch and none of the GPU vendors have been able to put forth a better solution than Quick Sync. If youre constantly transcoding movies to get them onto your smartphone or tablet, you need Ivy Bridge. In less than 7 minutes, and with no impact to CPU usage, I was able to transcode a complete 130 minute 1080p video to an iPad friendly format—thats over 15x real time.
QuickSync for anyone who doesn’t follow Intel’s own technology white papers and cpu releases is a special feature of Sandy Bridge era Intel CPUs. Originally its duty on Intel is as old as the Clarkdale series with embedded graphics (first round of the 32nm design rule). It can do things like just simply speeding up the process of decoding a video stream saved in a number of popular video formats VC-1, H.264, MP4, etc. Now it’s marketed to anyone trying to speed up the transcoding of video from one format to another. The first Sandy Bridge CPUs using the the hardware encoding portion of QuickSync showed incredible speeds as compared to GPU-accelerated encoders of that era. However things have been kicked up a further notch in the embedded graphics of the Intel Ivy Bridge series CPUs.
In the quote at the beginning of this article, I included a summary from the Anandtech review of the Intel Core i7 3770 which gives a better sense of the magnitude of the improvement. The full 130 minute Blu-ray DVD was converted at a rate of 15 times real time, meaning for every minute of video coming off the disk, QuickSync is able to transcode it in 4 seconds! That is major progress for anyone who has followed this niche of desktop computing. Having spent time capturing, editing and exporting video I will admit transcoding between formats is a lengthy process that uses up a lot of CPU resources. Offloading all that burden to the embedded graphics controller totally changes that traditional impedance of slowing the computer to a crawl and having to walk away and let it work.
Now transcoding is trivial, it costs nothing in terms of CPU load. And any time it can be faster than realtime means you don’t have to walk away from your computer (or at least not for very long), but 10X faster than real time makes that doubly true. Now we are fully at 15X realtime for a full length movie. The time spent is so short you wouldn’t ever have a second thought about “Will this transcode slow down the computer?” It won’t in fact you can continue doing all your other work, be productive, have fun and continue on your way just as if you hadn’t just asked your computer to do the most complicated, time consuming chore that (up until now) you could possibly ask it to do.
Knowing this application of the embedded graphics is so useful for desktop computers makes me wonder about Scientific Computing. What could Intel provide in terms of performance increases for simulations and computation in a super-computer cluster? Seeing how hybrid super computers using nVidia Tesla GPU co-processors mixed with Intel CPUs have slowly marched up the list of the Top 500 Supercomputers makes me think Intel could leverage QuickSync further,. . . Much further. Unfortunately this performance boost is solely dependent on a few vendors of proprietary transcoding software. The open software developers do not have an opening into the QuickSync tech in order to write a library that will re-direct a video stream into the QuickSync acceleration pipeline. When somebody does accomplish this feat, it may be shortly after when you see some Linux compute clusters attempt to use QuickSync as an embedded algorithm accelerator too.
- Intel Core i7-3770K review: Ivy Bridge brings lower power, better performance (alltech360.wordpress.com)
- Image Quality: Intel Ivy Bridge vs. Radeon Gallium3D (phoronix.com)
- Intel Ivy Bridge CPUs now available to order (slashgear.com)
Quick Sync is just awesome. Its simply the best way to get videos onto your smartphone or tablet. Not only do you get most if not all of the quality of a software based transcode, you get performance thats better than what high-end discrete GPUs are able to offer. If you do a lot of video transcoding onto portable devices, Sandy Bridge will be worth the upgrade for Quick Sync alone.
For everyone else, Sandy Bridge is easily a no brainer. Unless you already have a high-end Core i7, this is what youll want to upgrade to.
Previously in this blog I have recounted stories from Tom’s Hardware and Anandtech.com surrounding the wicked cool idea of tapping the vast resources contained within your GPU while you’re not playing video games. Producers of GPUs like nVidia and AMD both wanted to market their products to people who not only gamed but occasionally ripped video from DVDs and played them back on ipods or other mobile devices. The amount of time sunk into doing these kinds of conversions were made somewhat less of a pain due to the ability to run the process on a dual core Wintel computer, browsing web pages while re-encoding the video in the background. But to get better speeds one almost always needs to monopolize all the cores on the machine and free software like HandBrake and others will take advantage of those extra cores, thus slowing your machine, but effectively speeding up the transcoding process. There was hope that GPUs could accelerate the transcoding process beyond what was achievable with a multi-core cpu from Intel. An example is also Apple’s widespread adoption of OpenCL as a pipeline to the GPU to send rendering requests for any video frames or video processing that may need to be done in iTunes, QuickTime or the iLife applications. And where I work, we get asked to do a lot of transcoding of video to different formats for customers. Usually someone wants a rip from a DVD that they can put on a flash drive and take with them into a classroom.
However, now it appears there is a revolution in speed in the works where Intel is giving you faster transcodes for free. I’m talking about Intel’s new Quick Sync technology using the integrated graphics core as a video transcode accelerator. The speeds of transcoding are amazingly fast and given the speed, trivial to do for anyone including the casual user. In the past everyone seemed to complain about how slow their computer was especially for ripping DVDs or transcoding the rips to smaller more portable formats. Now, it takes a few minutes to get an hour of video into the right format. No more blue Monday. Follow the link to the story and analysis from Anandtech.com as they ran head to head comparisons of all the available techniques of re-encoding/transcoding a Blue-ray video release into a smaller .mp4 file encoded in as h.264. They did comparisons of Intel four-core cpus (which took the longest and got pretty good quality) versus GPU accelerated transcodes, versus the new Intel QuickSync technology coming out soon on the Sandy Bridge gen Intel i7 cpus. It is wicked cool how fast these transcodes are and it will make the process of transcoding trivial compared to how long it takes to actually ‘watch’ the video you spent all that time converting.
Links to older GPU accelerated video articles: