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• Visualizing Call Graphs Using Gephi

  1er septembre 2014, par Multimedia Mike — General

  When I was at university studying computer science, I took a basic chemistry course. During an accompanying lab, the teaching assistant chatted me up and asked about my major. He then said, “Computer science ? Well, that’s just typing stuff, right ?”

  My impulsive retort : “Sure, and chemistry is just about mixing together liquids and coming up with different colored liquids, as seen on the cover of my high school chemistry textbook, right ?”

  
  
  

  In fact, pure computer science has precious little to do with typing (as is joked in CS circles, computer science is about computers in the same way that astronomy is about telescopes). However, people who study computer science often pursue careers as programmers, or to put it in fancier professional language, software engineers.

  So, what’s a software engineer’s job ? Isn’t it just typing ? That’s where I’ve been going with this overly long setup. After thinking about it for long enough, I like to say that a software engineer’s trade is managing complexity.

  A few years ago, I discovered Gephi, an open source tool for graph and data visualization. It looked neat but I didn’t have much use for it at the time. Recently, however, I was trying to get a better handle on a large codebase. I.e., I was trying to manage the project’s complexity. And then I thought of Gephi again.

  Prior Work
  One way to get a grip on a large C codebase is to instrument it for profiling and extract details from the profiler. On Linux systems, this means compiling and linking the code using the -pg flag. After running the executable, there will be a gmon.out file which is post-processed using the gprof command.

  GNU software development tools have a reputation for being rather powerful and flexible, but also extremely raw. This first hit home when I was learning how to use the GNU tool for code coverage — gcov — and the way it outputs very raw data that you need to massage with other tools in order to get really useful intelligence.

  And so it is with gprof output. The output gives you a list of functions sorted by the amount of processing time spent in each. Then it gives you a flattened call tree. This is arranged as “during the profiled executions, function c was called by functions a and b and called functions d, e, and f ; function d was called by function c and called functions g and h”.

  How can this call tree data be represented in a more instructive manner that is easier to navigate ? My first impulse (and I don’t think I’m alone in this) is to convert the gprof call tree into a representation suitable for interpretation by Graphviz. Unfortunately, doing so tends to generate some enormous and unwieldy static images.

  Feeding gprof Data To Gephi
  I learned of Gephi a few years ago and recalled it when I developed an interest in gaining better perspective on a large base of alien C code. To understand what this codebase is doing for a particular use case, instrument it with gprof, gather execution data, and then study the code paths.

  How could I feed the gprof data into Gephi ? Gephi supports numerous graphing formats including an XML-based format named GEXF.

  Thus, the challenge becomes converting gprof output to GEXF.

  Which I did.

  Demonstration
  I have been absent from FFmpeg development for a long time, which is a pity because a lot of interesting development has occurred over the last 2-3 years after a troubling period of stagnation. I know that 2 big video codec developments have been HEVC (next in the line of MPEG codecs) and VP9 (heir to VP8’s throne). FFmpeg implements them both now.

  I decided I wanted to study the code flow of VP9. So I got the latest FFmpeg code from git and built it using the options "--extra-cflags=-pg --extra-ldflags=-pg". Annoyingly, I also needed to specify "--disable-asm" because gcc complains of some register allocation snafus when compiling inline ASM in profiling mode (and this is on x86_64). No matter ; ASM isn’t necessary for understanding overall code flow.

  After compiling, the binary ‘ffmpeg_g’ will have symbols and be instrumented for profiling. I grabbed a sample from this VP9 test vector set and went to work.

  ./ffmpeg_g -i vp90-2-00-quantizer-00.webm -f null /dev/null
  gprof ./ffmpeg_g > vp9decode.txt
  convert-gprof-to-gexf.py vp9decode.txt > /bigdisk/vp9decode.gexf
  

  Gephi loads vp9decode.gexf with no problem. Using Gephi, however, can be a bit challenging if one is not versed in any data exploration jargon. I recommend this Gephi getting starting guide in slide deck form. Here’s what the default graph looks like :

  
  
  

  Not very pretty or helpful. BTW, that beefy arrow running from mid-top to lower-right is the call from decode_coeffs_b -> iwht_iwht_4x4_add_c. There were 18774 from the former to the latter in this execution. Right now, the edge thicknesses correlate to number of calls between the nodes, which I’m not sure is the best representation.

  Following the tutorial slide deck, I at least learned how to enable the node labels (function symbols in this case) and apply a layout algorithm. The tutorial shows the force atlas layout. Here’s what the node neighborhood looks like for probing file type :

  
  
  

  Okay, so that’s not especially surprising– avprobe_input_format3 calls all of the *_probe functions in order to automatically determine input type. Let’s find that decode_coeffs_b function and see what its neighborhood looks like :

  
  
  

  That’s not very useful. Perhaps another algorithm might help. I select the Fruchterman–Reingold algorithm instead and get a slightly more coherent representation of the decoding node neighborhood :

  
  
  

  Further Work
  Obviously, I’m just getting started with this data exploration topic. One thing I would really appreciate in such a tool is the ability to interactively travel the graph since that’s what I’m really hoping to get out of this experiment– watching the code flows.

  Perhaps someone else can find better use cases for visualizing call graph data. Thus, I have published the source code for this tool at Github.

• What is best way to feed ffmpeg in Android ?

  26 octobre 2014, par trololo

  I have compiled ffmpeg for Android for rtmp.
  I want to feed ffmpeg by video and audio (2 channels) at the same time. I found a solution by just one input (only video in my case) pipe streaming (stdin).
  I’m trying to use pure Java code.

  I know that ffmpeg can comsume data from numbered (or may be named Pipe) :

  ffmpeg -i pipe:Number ...

  Number == 0 it means stdin (i’m using it for video)
  But what is the way to create a pipe of another number ?

  I’ve tried mkfifo MYFIFO but the Android gives me IOExcepion

  I’ve tried Filedescriptor but getFd() give an error too. Futhermore, it requires high-level API.

  Is it possible to solve this problem ?

• Metal Gear Solid VP3 Easter Egg

  4 août 2011, par Multimedia Mike — Game Hacking

  Metal Gear Solid : The Twin Snakes for the Nintendo GameCube is very heavy on the cutscenes. Most of them are animated in real-time but there are a bunch of clips — normally of a more photo-realistic nature — that the developers needed to compress using a conventional video codec. What did they decide to use for this task ? On2 VP3 (forerunner of Theora) in a custom transport format. This is only the second game I have seen in the wild that uses pure On2 VP3 (first was a horse game). Reimar and I sorted out most of the details sometime ago. I sat down today and wrote a FFmpeg / Libav demuxer for the format, mostly to prove to myself that I still could.

  Things went pretty smoothly. We suspected that there was an integer field that indicated the frame rate, but 18 fps is a bit strange. I kept fixating on a header field that read 0x41F00000. Where have I seen that number before ? Oh, of course — it’s the number 30.0 expressed as an IEEE 32-bit float. The 4XM format pulled the same trick.

  Hexadecimal Easter Egg
  I know I finished the game years ago but I really can’t recall any of the clips present in the samples directory. The file mgs1-60.vp3 contains a computer screen granting the player access and illustrates this with a hexdump. It looks something like this :

  
  
  

  Funny, there are only 22 bytes on a line when there should be 32 according to the offsets. But, leave it to me to try to figure out what the file type is, regardless. I squinted and copied the first 22 bytes into a file :

   1F 8B 08 00   85 E2 17 38   00 03 EC 3A   0D 78 54 D5
   38 00 03 EC   3A 0D
  

  And the answer to the big question :

  $ file mgsfile
  mgsfile : gzip compressed data, from Unix, last modified : Wed Oct 27 22:43:33 1999
  

  A gzip’d file from 1999. I don’t know why I find this stuff so interesting, but I do. I guess it’s no more and less strange than writing playback systems like this.