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• Monster Battery Power Revisited

  28 mai 2010, par Multimedia Mike — Python, Science Projects

  So I have this new fat netbook battery and I performed an experiment to determine how long it really lasts. In my last post on the matter, it was suggested that I should rely on the information that gnome-power-manager is giving me. However, I have rarely seen GPM report more than about 2 hours of charge ; even on a full battery, it only reports 3h25m when I profiled it as lasting over 5 hours in my typical use. So I started digging to understand how GPM gets its numbers and determine if, perhaps, it’s not getting accurate data from the system.

  I started poking around /proc for the data I wanted. You can learn a lot in /proc as long as you know the right question to ask. I had to remember what the power subsystem is called — ACPI — and this led me to /proc/acpi/battery/BAT0/state which has data such as :

  present :                 yes
  capacity state :          ok
  charging state :          charged
  present rate :            unknown
  remaining capacity :      100 mAh
  present voltage :         8326 mV
  

  "Remaining capacity" rated in mAh is a little odd ; I would later determine that this should actually be expressed as a percentage (i.e., 100% charge at the time of this reading). Examining the GPM source code, it seems to determine as a function of the current CPU load (queried via /proc/stat) and the battery state queried via a facility called devicekit. I couldn’t immediately find any source code to the latter but I was able to install a utility called ’devkit-power’. Mostly, it appears to rehash data already found in the above /proc file.

  Curiously, the file /proc/acpi/battery/BAT0/info, which displays essential information about the battery, reports the design capacity of my battery as only 4400 mAh which is true for the original battery ; the new monster battery is supposed to be 10400 mAh. I can imagine that all of these data points could be conspiring to under-report my remaining battery life.

  Science project : Repeat the previous power-related science project but also parse and track the remaining capacity and present voltage fields from the battery state proc file.

  Let’s skip straight to the results (which are consistent with my last set of results in terms of longevity) :

  
  
  

  So there is definitely something strange going on with the reporting— the 4400 mAh battery reports discharge at a linear rate while the 10400 mAh battery reports precipitous dropoff after 60%.

  Another curious item is that my script broke at first when there was 20% power remaining which, as you can imagine, is a really annoying time to discover such a bug. At that point, the "time to empty" reported by devkit-power jumped from 0 seconds to 20 hours (the first state change observed for that field).

  Here’s my script, this time elevated from Bash script to Python. It requires xdotool and devkit-power to be installed (both should be available in the package manager for a distro).
  

  PLAIN TEXT

  PYTHON :

  1. # !/usr/bin/python
  2.  
  3. import commands
  4. import random
  5. import sys
  6. import time
  7.  
  8. XDOTOOL = "/usr/bin/xdotool"
  9. BATTERY_STATE = "/proc/acpi/battery/BAT0/state"
  10. DEVKIT_POWER = "/usr/bin/devkit-power -i /org/freedesktop/DeviceKit/Power/devices/battery_BAT0"
  11.  
  12. print "count, unixtime, proc_remaining_capacity, proc_present_voltage, devkit_percentage, devkit_voltage"
  13.  
  14. count = 0
  15. while 1 :
  16.   commands.getstatusoutput("%s mousemove %d %d" % (XDOTOOL, random.randrange(0,800), random.randrange(0, 480)))
  17.   battery_state = open(BATTERY_STATE).read().splitlines()
  18.   for line in battery_state :
  19.     if line.startswith("remaining capacity :") :
  20.       proc_remaining_capacity = int(line.lstrip("remaining capacity : ").rstrip("mAh"))
  21.     elif line.startswith("present voltage :") :
  22.       proc_present_voltage = int(line.lstrip("present voltage : ").rstrip("mV"))
  23.   devkit_state = commands.getoutput(DEVKIT_POWER).splitlines()
  24.   for line in devkit_state :
  25.     line = line.strip()
  26.     if line.startswith("percentage :") :
  27.       devkit_percentage = int(line.lstrip("percentage :").rstrip(’\%’))
  28.     elif line.startswith("voltage :") :
  29.       devkit_voltage = float(line.lstrip("voltage :").rstrip(’V’)) * 1000
  30.   print "%d, %d, %d, %d, %d, %d" % (count, time.time(), proc_remaining_capacity, proc_present_voltage, devkit_percentage, devkit_voltage)
  31.   sys.stdout.flush()
  32.   time.sleep(60)
  33.   count += 1

• Multiprocess FATE Revisited

  26 juin 2010, par Multimedia Mike — FATE Server, Python

  I thought I had brainstormed a simple, elegant, multithreaded, deadlock-free refactoring for FATE in a previous post. However, I sort of glossed over the test ordering logic which I had not yet prototyped. The grim, possibly deadlock-afflicted reality is that the main thread needs to be notified as tests are completed. So, the main thread sends test specs through a queue to be executed by n tester threads and those threads send results to a results aggregator thread. Additionally, the results aggregator will need to send completed test IDs back to the main thread.

  
  
  

  But when I step back and look at the graph, I can’t rationalize why there should be a separate results aggregator thread. That was added to cut down on deadlock possibilities since the main thread and the tester threads would not be waiting for data from each other. Now that I’ve come to terms with the fact that the main and the testers need to exchange data in realtime, I think I can safely eliminate the result thread. Adding more threads is not the best way to guard against race conditions and deadlocks. Ask xine.

  
  
  

  I’m still hung up on the deadlock issue. I have these queues through which the threads communicate. At issue is the fact that they can cause a thread to block when inserting an item if the queue is "full". How full is full ? Immaterial ; seeking to answer such a question is not how you guard against race conditions. Rather, it seems to me that one side should be doing non-blocking queue operations.

  This is how I’m planning to revise the logic in the main thread :

  test_set = set of all tests to execute
  tests_pending = test_set
  tests_blocked = empty set
  tests_queue = multi-consumer queue to send test specs to tester threads
  results_queue = multi-producer queue through which tester threads send results
  while there are tests in tests_pending :
    pop a test from test_set
    if test depends on any tests that appear in tests_pending :
      add test to tests_blocked
    else :
      add test to tests_queue in a non-blocking manner
      if tests_queue is full, add test to tests_blocked
    while there are results in the results_queue :
  
      get a result from result_queue in non-blocking manner
  
      remove the corresponding test from tests_pending
  if tests_blocked is non-empty :
  
    sleep for 1 second
  
    test_set = tests_blocked
  
    tests_blocked = empty set
  
  else :
  
    insert n shutdown signals, one from each thread
  go to the top of the loop and repeat until there are no more tests
  while there are results in the results_queue :
  
    get a result from result_queue in a blocking manner
  

  Not mentioned in the pseudocode (so it doesn’t get too verbose) is logic to check whether the retrieved test result is actually an end-of-thread signal. These are accounted and the whole test process is done when one is received for each thread.

  On the tester thread side, it’s safe for them to do blocking test queue retrievals and blocking result queue insertions. The reason for the 1-second delay before resetting tests_blocked and looping again is because I want to guard against the situation where tests A and B are to be run, A depends of B running first, and while B is running (and happens to be a long encoding test), the main thread is spinning about, obsessively testing whether it’s time to insert A into the tests queue.

  It all sounds just crazy enough to work. In fact, I coded it up and it does work, sort of. The queue gets blocked pretty quickly. Instead of sleeping, I decided it’s better to perform the put operation using a 1-second timeout.

  Still, I’m paranoid about the precise operation of the IPC queue mechanism at work here. What happens if I try to stuff in a test spec that’s a bit too large ? Will the module take whatever I give it and serialize it through the queue as soon as it can ? I think an impromptu science project is in order.

  big-queue.py :

  PLAIN TEXT

  PYTHON :

  1. # !/usr/bin/python
  2.  
  3. import multiprocessing
  4. import Queue
  5.  
  6. def f(q) :
  7.   str = q.get()
  8.   print "reader function got a string of %d characters" % (len(str))
  9.  
  10. q = multiprocessing.Queue()
  11. p = multiprocessing.Process(target=f, args=(q,))
  12. p.start()
  13. try :
  14.   q.put_nowait(’a’ * 100000000)
  15. except Queue.Full :
  16.   print "queue full"

  $ ./big-queue.py
  reader function got a string of 100000000 characters
  

  Since 100 MB doesn’t even make it choke, FATE’s little test specs shouldn’t pose any difficulty.

• Summary Video Accessibility Talk

  23 avril 2013, par silvia

  I’ve just got off a call to the UK Digital TV Group, for which I gave a talk on HTML5 video accessibility (slides best viewed in Google Chrome).

  The slide provide a high-level summary of the accessibility features that we’ve developed in the W3C for HTML5, including :

  • Subtitles & Captions with WebVTT and the track element
  • Video Descriptions with WebVTT, the track element and speech synthesis
  • Chapters with WebVTT for semantic navigation
  • Audio Descriptions through synchronising an audio track with a video
  • Sign Language video synchronized with a main video

  I received some excellent questions.

  The obvious one was about why WebVTT and not TTML. While for anyone who has tried to implement TTML support, the advantages of WebVTT should be clear, for some the decision of the browsers to go with WebVTT still seems to be bothersome. The advantages of CSS over XSL-FO in a browser-context are obvious, but not as much outside browsers. So, the simplicity of WebVTT and the clear integration with HTML have to speak for themselves. Conversion between TTML and WebVTT was a feature that was being asked for.

  I received a question about how to support ducking (reduce the volume of the main audio track) when using video descriptions. My reply was to either use video descriptions with WebVTT and do ducking during the times that a cue is active, or when using audio descriptions (i.e. actual audio tracks) to add an additional WebVTT file of kind=metadata to mark the intervals in which to do ducking. In both cases some JavaScript will be necessary.

  I received another question about how to do clean audio, which I had almost forgotten was a requirement from our earlier media accessibility document. “Clean audio” consists of isolating the audio channel containing the spoken dialog and important non-speech information that can then be amplified or otherwise modified, while other channels containing music or ambient sounds are attenuated. I suggested using the mediagroup attribute to provide a main video element (without an audio track) and then the other channels as parallel audio tracks that can be turned on and off and attenuated individually. There is some JavaScript coding involved on top of the APIs that we have defined in HTML, but it can be implemented in browsers that support the mediagroup attribute.

  Another question was about the possibilities to extend the list of @kind attribute values. I explained that right now we have a proposal for a new text track kind=”forced” so as to provide forced subtitles for sections of video with foreign language. These would be on when no other subtitle or caption tracks are activated. I also explained that if there is a need for application-specific text tracks, the kind=”metadata” would be the correct choice.

  I received some further questions, in particular about how to apply styling to captions (e.g. color changes to text) and about how closely the browser are able to keep synchronization across multiple media elements. The earlier was easily answered with the ::cue pseudo-element, but the latter is a quality of implementation feature, so I had to defer to individual browsers.

  Overall it was a good exercise to summarize the current state of HTML5 video accessibility and I was excited to show off support in Chrome for all the features that we designed into the standard.