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• VP8 : a retrospective

  13 juillet 2010, par Dark Shikari — DCT, VP8, speed

  I’ve been working the past few weeks to help finish up the ffmpeg VP8 decoder, the first community implementation of On2′s VP8 video format. Now that I’ve written a thousand or two lines of assembly code and optimized a good bit of the C code, I’d like to look back at VP8 and comment on a variety of things — both good and bad — that slipped the net the first time, along with things that have changed since the time of that blog post.

  These are less-so issues related to compression — that issue has been beaten to death, particularly in MSU’s recent comparison, where x264 beat the crap out of VP8 and the VP8 developers pulled a Pinocchio in the developer comments. But that was expected and isn’t particularly interesting, so I won’t go into that. VP8 doesn’t have to be the best in the world in order to be useful.

  When the ffmpeg VP8 decoder is complete (just a few more asm functions to go), we’ll hopefully be able to post some benchmarks comparing it to libvpx.

  1. The spec, er, I mean, bitstream guide.

  Google has reneged on their claim that a spec existed at all and renamed it a “bitstream guide”. This is probably after it was found that — not merely was it incomplete — but at least a dozen places in the spec differed wildly from what was actually in their own encoder and decoder software ! The deblocking filter, motion vector clamping, probability tables, and many more parts simply disagreed flat-out with the spec. Fortunately, Ronald Bultje, one of the main authors of the ffmpeg VP8 decoder, is rather skilled at reverse-engineering, so we were able to put together a matching implementation regardless.

  Most of the differences aren’t particularly important — they don’t have a huge effect on compression or anything — but make it vastly more difficult to implement a “working” VP8 decoder, or for that matter, decide what “working” really is. For example, Google’s decoder will, if told to “swap the ALT and GOLDEN reference frames”, overwrite both with GOLDEN, because it first sets GOLDEN = ALT, and then sets ALT = GOLDEN. Is this a bug ? Or is this how it’s supposed to work ? It’s hard to tell — there isn’t a spec to say so. Google says that whatever libvpx does is right, but I doubt they intended this.

  I expect a spec will eventually be written, but it was a bit obnoxious of Google — both to the community and to their own developers — to release so early that they didn’t even have their own documentation ready.

  2. The TM intra prediction mode.

  One thing I glossed over in the original piece was that On2 had added an extra intra prediction mode to the standard batch that H.264 came with — they replaced Planar with “TM pred”. For i4x4, which didn’t have a Planar mode, they just added it without replacing an old one, resulting in a total of 10 modes to H.264′s 9. After understanding and writing assembly code for TM pred, I have to say that it is quite a cool idea. Here’s how it works :

  1. Let us take a block of size 4×4, 8×8, or 16×16.

  2. Define the pixels bordering the top of this block (starting from the left) as T[0], T[1], T[2]…

  3. Define the pixels bordering the left of this block (starting from the top) as L[0], L[1], L[2]…

  4. Define the pixel above the top-left of the block as TL.

  5. Predict every pixel <X,Y> in the block to be equal to clip3( T[X] + L[Y] – TL, 0, 255).

  It’s effectively a generalization of gradient prediction to the block level — predict each pixel based on the gradient between its top and left pixels, and the topleft. According to the VP8 devs, it’s chosen by the encoder quite a lot of the time, which isn’t surprising ; it seems like a pretty good idea. As just one more intra pred mode, it’s not going to do magic for compression, but it’s a cool idea and elegantly simple.

  3. Performance and the deblocking filter.
  

  On2 advertised for quite some that VP8′s goal was to be significantly faster to decode than H.264. When I saw the spec, I waited for the punchline, but apparently they were serious. There’s nothing wrong with being of similar speed or a bit slower — but I was rather confused as to the fact that their design didn’t match their stated goal at all. What apparently happened is they had multiple profiles of VP8 — high and low complexity profiles. They marketed the performance of the low complexity ones while touting the quality of the high complexity ones, a tad dishonest. More importantly though, practically nobody is using the low complexity modes, so anyone writing a decoder has to be prepared to handle the high complexity ones, which are the default.

  The primary time-eater here is the deblocking filter. VP8, being an H.264 derivative, has much the same problem as H.264 does in terms of deblocking — it spends an absurd amount of time there. As I write this post, we’re about to finish some of the deblocking filter asm code, but before it’s committed, up to 70% or more of total decoding time is spent in the deblocking filter ! Like H.264, it suffers from the 4×4 transform problem : a 4×4 transform requires a total of 8 length-16 and 8 length-8 loopfilter calls per macroblock, while Theora, with only an 8×8 transform, requires half that.

  This problem is aggravated in VP8 by the fact that the deblocking filter isn’t strength-adaptive ; if even one 4×4 block in a macroblock contains coefficients, every single edge has to be deblocked. Furthermore, the deblocking filter itself is quite complicated ; the “inner edge” filter is a bit more complex than H.264′s and the “macroblock edge” filter is vastly more complicated, having two entirely different codepaths chosen on a per-pixel basis. Of course, in SIMD, this means you have to do both and mask them together at the end.

  There’s nothing wrong with a good-but-slow deblocking filter. But given the amount of deblocking one needs to do in a 4×4-transform-based format, it might have been a better choice to make the filter simpler. It’s pretty difficult to beat H.264 on compression, but it’s certainly not hard to beat it on speed — and yet it seems VP8 missed a perfectly good chance to do so. Another option would have been to pick an 8×8 transform instead of 4×4, reducing the amount of deblocking by a factor of 2.

  And yes, there’s a simple filter available in the low complexity profile, but it doesn’t help if nobody uses it.

  4. Tree-based arithmetic coding.

  Binary arithmetic coding has become the standard entropy coding method for a wide variety of compressed formats, ranging from LZMA to VP6, H.264 and VP8. It’s simple, relatively fast compared to other arithmetic coding schemes, and easy to make adaptive. The problem with this is that you have to come up with a method for converting non-binary symbols into a list of binary symbols, and then choosing what probabilities to use to code each one. Here’s an example from H.264, the sub-partition mode symbol, which is either 8×8, 8×4, 4×8, or 4×4. encode_decision( context, bit ) writes a binary decision (bit) into a numbered context (context).

  8×8 : encode_decision( 21, 0 ) ;

  8×4 : encode_decision( 21, 1 ) ; encode_decision( 22, 0 ) ;

  4×8 : encode_decision( 21, 1 ) ; encode_decision( 22, 1 ) ; encode_decision( 23, 1 ) ;

  4×4 : encode_decision( 21, 1 ) ; encode_decision( 22, 1 ) ; encode_decision( 23, 0 ) ;

  As can be seen, this is clearly like a Huffman tree. Wouldn’t it be nice if we could represent this in the form of an actual tree data structure instead of code ? On2 thought so — they designed a simple system in VP8 that allowed all binarization schemes in the entire format to be represented as simple tree data structures. This greatly reduces the complexity — not speed-wise, but implementation-wise — of the entropy coder. Personally, I quite like it.

  5. The inverse transform ordering.

  I should at some point write a post about common mistakes made in video formats that everyone keeps making. These are not issues that are patent worries or huge issues for compression — just stupid mistakes that are repeatedly made in new video formats, probably because someone just never asked the guy next to him “does this look stupid ?” before sticking it in the spec.

  One common mistake is the problem of transform ordering. Every sane 2D transform is “separable” — that is, it can be done by doing a 1D transform vertically and doing the 1D transform again horizontally (or vice versa). The original iDCT as used in JPEG, H.263, and MPEG-1/2/4 was an “idealized” iDCT — nobody had to use the exact same iDCT, theirs just had to give very close results to a reference implementation. This ended up resulting in a lot of practical problems. It was also slow ; the only way to get an accurate enough iDCT was to do all the intermediate math in 32-bit.

  Practically every modern format, accordingly, has specified an exact iDCT. This includes H.264, VC-1, RV40, Theora, VP8, and many more. Of course, with an exact iDCT comes an exact ordering — while the “real” iDCT can be done in any order, an exact iDCT usually requires an exact order. That is, it specifies horizontal and then vertical, or vertical and then horizontal.

  All of these transforms end up being implemented in SIMD. In SIMD, a vertical transform is generally the only option, so a transpose is added to the process instead of doing a horizontal transform. Accordingly, there are two ways to do it :

  1. Transpose, vertical transform, transpose, vertical transform.

  2. Vertical transform, transpose, vertical transform, transpose.

  These may seem to be equally good, but there’s one catch — if the transpose is done first, it can be completely eliminated by merging it into the coefficient decoding process. On many modern CPUs, particularly x86, transposes are very expensive, so eliminating one of the two gives a pretty significant speed benefit.

  H.264 did it way 1).

  VC-1 did it way 1).

  Theora (inherited from VP3) did it way 1).

  But no. VP8 has to do it way 2), where you can’t eliminate the transpose. Bah. It’s not a huge deal ; probably only 1-2% overall at most speed-wise, but it’s just a needless waste. What really bugs me is that VP3 got it right — why in the world did they screw it up this time around if they got it right beforehand ?

  RV40 is the other modern format I know that made this mistake.

  (NB : You can do transforms without a transpose, but it’s generally not worth it unless the intermediate needs 32-bit math, as in the case of the “real” iDCT.)

  6. Not supporting interlacing.

  THANK YOU THANK YOU THANK YOU THANK YOU THANK YOU THANK YOU THANK YOU.

  Interlacing was the scourge of H.264. It weaseled its way into every nook and cranny of the spec, making every decoder a thousand lines longer. H.264 even included a highly complicated — and effective — dedicated interlaced coding scheme, MBAFF. The mere existence of MBAFF, despite its usefulness for broadcasters and others still stuck in the analog age with their 1080i, 576i , and 480i content, was a blight upon the video format.

  VP8 has once and for all avoided it.

  And if anyone suggests adding interlaced support to the experimental VP8 branch, find a straightjacket and padded cell for them before they cause any real damage.

• Anatomy of an optimization : H.264 deblocking

  26 mai 2010, par Dark Shikari — H.264, assembly, development, speed, x264

  As mentioned in the previous post, H.264 has an adaptive deblocking filter. But what exactly does that mean — and more importantly, what does it mean for performance ? And how can we make it as fast as possible ? In this post I’ll try to answer these questions, particularly in relation to my recent deblocking optimizations in x264.

  H.264′s deblocking filter has two steps : strength calculation and the actual filter. The first step calculates the parameters for the second step. The filter runs on all the edges in each macroblock. That’s 4 vertical edges of length 16 pixels and 4 horizontal edges of length 16 pixels. The vertical edges are filtered first, from left to right, then the horizontal edges, from top to bottom (order matters !). The leftmost edge is the one between the current macroblock and the left macroblock, while the topmost edge is the one between the current macroblock and the top macroblock.

  Here’s the formula for the strength calculation in progressive mode. The highest strength that applies is always selected.

  If we’re on the edge between an intra macroblock and any other macroblock : Strength 4
  If we’re on an internal edge of an intra macroblock : Strength 3
  If either side of a 4-pixel-long edge has residual data : Strength 2
  If the motion vectors on opposite sides of a 4-pixel-long edge are at least a pixel apart (in either x or y direction) or the reference frames aren’t the same : Strength 1
  Otherwise : Strength 0 (no deblocking)

  These values are then thrown into a lookup table depending on the quantizer : higher quantizers have stronger deblocking. Then the actual filter is run with the appropriate parameters. Note that Strength 4 is actually a special deblocking mode that performs a much stronger filter and affects more pixels.

  One can see somewhat intuitively why these strengths are chosen. The deblocker exists to get rid of sharp edges caused by the block-based nature of H.264, and so the strength depends on what exists that might cause such sharp edges. The strength calculation is a way to use existing data from the video stream to make better decisions during the deblocking process, improving compression and quality.

  Both the strength calculation and the actual filter (not described here) are very complex if naively implemented. The latter can be SIMD’d with not too much difficulty ; no H.264 decoder can get away with reasonable performance without such a thing. But what about optimizing the strength calculation ? A quick analysis shows that this can be beneficial as well.

  Since we have to check both horizontal and vertical edges, we have to check up to 32 pairs of coefficient counts (for residual), 16 pairs of reference frame indices, and 128 motion vector values (counting x and y as separate values). This is a lot of calculation ; a naive implementation can take 500-1000 clock cycles on a modern CPU. Of course, there’s a lot of shortcuts we can take. Here’s some examples :

  • If the macroblock uses the 8×8 transform, we only need to check 2 edges in each direction instead of 4, because we don’t deblock inside of the 8×8 blocks.
  • If the macroblock is a P-skip, we only have to check the first edge in each direction, since there’s guaranteed to be no motion vector differences, reference frame differences, or residual inside of the macroblock.
  • If the macroblock has no residual at all, we can skip that check.
  • If we know the partition type of the macroblock, we can do motion vector checks only along the edges of the partitions.
  • If the effective quantizer is so low that no deblocking would be performed no matter what, don’t bother calculating the strength.

  But even all of this doesn’t save us from ourselves. We still have to iterate over a ton of edges, checking each one. Stuff like the partition-checking logic greatly complicates the code and adds overhead even as it reduces the number of checks. And in many cases decoupling the checks to add such logic will make it slower : if the checks are coupled, we can avoid doing a motion vector check if there’s residual, since Strength 2 overrides Strength 1.

  But wait. What if we could do this in SIMD, just like the actual loopfilter itself ? Sure, it seems more of a problem for C code than assembly, but there aren’t any obvious things in the way. Many years ago, Loren Merritt (pengvado) wrote the first SIMD implementation that I know of (for ffmpeg’s decoder) ; it is quite fast, so I decided to work on porting the idea to x264 to see if we could eke out a bit more speed here as well.

  Before I go over what I had to do to make this change, let me first describe how deblocking is implemented in x264. Since the filter is a loopfilter, it acts “in loop” and must be done in both the encoder and decoder — hence why x264 has it too, not just decoders. At the end of encoding one row of macroblocks, x264 goes back and deblocks the row, then performs half-pixel interpolation for use in encoding the next frame.

  We do it per-row for reasons of cache coherency : deblocking accesses a lot of pixels and a lot of code that wouldn’t otherwise be used, so it’s more efficient to do it in a single pass as opposed to deblocking each macroblock immediately after encoding. Then half-pixel interpolation can immediately re-use the resulting data.

  Now to the change. First, I modified deblocking to implement a subset of the macroblock_cache_load function : spend an extra bit of effort loading the necessary data into a data structure which is much simpler to address — as an assembly implementation would need (x264_macroblock_cache_load_deblock). Then I massively cleaned up deblocking to move all of the core strength-calculation logic into a single, small function that could be converted to assembly (deblock_strength_c). Finally, I wrote the assembly functions and worked with Loren to optimize them. Here’s the result.

  And the timings for the resulting assembly function on my Core i7, in cycles :

  deblock_strength_c : 309
  deblock_strength_mmx : 79
  deblock_strength_sse2 : 37
  deblock_strength_ssse3 : 33

  Now that is a seriously nice improvement. 33 cycles on average to perform that many comparisons–that’s absurdly low, especially considering the SIMD takes no branchy shortcuts : it always checks every single edge ! I walked over to my performance chart and happily crossed off a box.

  But I had a hunch that I could do better. Remember, as mentioned earlier, we’re reloading all that data back into our data structures in order to address it. This isn’t that slow, but takes enough time to significantly cut down on the gain of the assembly code. And worse, less than a row ago, all this data was in the correct place to be used (when we just finished encoding the macroblock) ! But if we did the deblocking right after encoding each macroblock, the cache issues would make it too slow to be worth it (yes, I tested this). So I went back to other things, a bit annoyed that I couldn’t get the full benefit of the changes.

  Then, yesterday, I was talking with Pascal, a former Xvid dev and current video hacker over at Google, about various possible x264 optimizations. He had seen my deblocking changes and we discussed that a bit as well. Then two lines hit me like a pile of bricks :

  <_skal_> tried computing the strength at least ?
  <_skal_> while it’s fresh

  Why hadn’t I thought of that ? Do the strength calculation immediately after encoding each macroblock, save the result, and then go pick it up later for the main deblocking filter. Then we can use the data right there and then for strength calculation, but we don’t have to do the whole deblock process until later.

  I went and implemented it and, after working my way through a horde of bugs, eventually got a working implementation. A big catch was that of slices : deblocking normally acts between slices even though normal encoding does not, so I had to perform extra munging to get that to work. By midday today I was able to go cross yet another box off on the performance chart. And now it’s committed.

  Sometimes chatting for 10 minutes with another developer is enough to spot the idea that your brain somehow managed to miss for nearly a straight week.

  NB : the performance chart is on a specific test clip at a specific set of settings (super fast settings) relevant to the company I work at, so it isn’t accurate nor complete for, say, default settings.

  Update : Here’s a higher resolution version of the current chart, as requested in the comments.
  

  http://git.videolan.org/?p=x264.git ;a=commit ;h=b9ec3ea27812288485329ac7771143021cd4917b

• Anomalie #3539 : 2 fois prévisualiser pour voir le bloc de prévisualisation

  30 octobre 2015, par chan kalan

  De mon côté je reproduis le problème.
  plugin Forum 1.9.29
  Un bug au chargement ajax ?