[surki]

Well, the example(at least the first one) in that video is bit skewed. First, he runs gzip and then immediately runs 'parallel gzip' without dropping disk caches. So in the later case the bottleneck would be CPU rather than disk IO(everything read from disk cache in the RAM). IMO I expect for the work that is IO bound we won't see any significant improvement using parallel or anything similar.

[oletange]

Ideas for next video are most welcome. The ideal task:

1. Is single threaded 2. Takes a lot of CPU 3. Is a task that everyone can understand and relate to and which is close to a real world scenario

I have loads of examples meeting requirement 1+2. It is 3 that is the hard part.

Post them to [e-mail]

[surki]

How about doing something with imagemagick or mencoder? I think video encoding/decoding gives a nice balance between disk and cpu usage.

[eschulte]

Here's an imagemagick example; over six minutes with xargs, under 20 seconds with parallel

  $ ls *.png |wc -l
  3580

  $ time ls|sed 's/\(.*\)\..*/\1/'|parallel convert {}.png {}.ppm
  ls --color  0.00s user 0.01s system 63% cpu 0.016 total
  sed 's/\(.*\)\..*/\1/'  0.01s user 0.00s system 39% cpu 0.025 total
  parallel convert {}.png {}.ppm  97.39s user 61.87s system 890% cpu 17.883 total

  $ time ls|sed 's/\(.*\)\..*/\1/'|xargs -I {} convert {}.png {}.ppm
  ls --color  0.01s user 0.00s system 63% cpu 0.016 total
  sed 's/\(.*\)\..*/\1/'  0.01s user 0.00s system 39% cpu 0.025 total
  xargs -I {} convert {}.png {}.ppm  93.08s user 47.88s system 38% cpu 6:10.88 total