/usr/share/psychtoolbox-3/PsychTests/StandaloneTimingTest.m is in psychtoolbox-3-common 3.0.11.20131230.dfsg1-1build1.
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% StandaloneTimingTest(use_sigsetjmp, savemask)
%
% run a timing loop in a separate process, indepenent of MATLAB. plot the results.
%
% use_sigsetmask specifies whether the StandaloneTimingTest program will
% call sigsetjmp() within the timing loop. If sigsetmask is set, then
% StandaloneTimingTest passes savemask to sigsetjmp in the second argument.
%
% comparing results of TestStandaloneTimingOSX with and without
% sigsetjmp shows that calling sigsetjmp with the savemask
% argument set causes OS X to suspend execution of the StandaloneTimingTest
% application for up to 13 ms.
%
% SEE ALSO: StandaloneTimingTest.c
% AUTHORS:
% Allen Ingling awi Allen.Ingling@nyu.edu
%
% HISTORY:
% 8/26/03 awi Wrote it.
% 9/14/03 awi Merged in features from TestMATLABTimingOSX.m, mostly
% to improve plotting features.
% 9/24/03 awi Changed the name of the standalone application to
% "StandaloneTimingApp"
% 11/04/03 awi Added axis labels.
% 12/02/03 awi Added use_sigsetjmp and savemask flags.
% 4/6/05 awi Replaced "GetBusFrequencymex" calls with "MachTimebase"
% 4/8/05 awi Updated "MachTimebase" to new name "MachAbsoluteTimeClockFrequency"
% Setting "time constrait" priority settings and blocking duration:
%
% periodSecs= 1/1000;
% computationSecs = periodSecs/10;
% constraintSecs= computationSecs;
% preemptibleFlag=1;
% blockingIntervalSecs=periodSecs;
%
% Out of every millisecond guarantee the MATLAB process up to 100 microseconds
% of CPU time. That is, MATLAB will lay claim to up to 1/10 of the total CPU time.
% Gurantee that that MATLAB's 100 microseconds of CPU time fall within a
% 100 microsecond window, from the start of computation to the end of
% computation. Within that window, allow MATLAB to be interrupted by other
% threads.
%
% Note that we do not know in advance of the timing loop how much CPU time we will
% actually need, that depends on how much CPU time MATLAB expends
% in processing a scripted loop pass. We can however retroactively validate our
% choice of values by examing timing results:
%
% blockingInterval + actualMATLABCPUUsage = loopPassDuration
%
% therefore:
%
% loopPassDuration - blockingInterval = actualMATLABCPUUsage
%
% we know everything on the left hand side can find actualMATLABCPUUsage. If we have chosen
% parameters correctly then:
%
% actualMATLABCPUUsage <= computationSeconds
%
% and,
%
% actualMATLABCPUUsage/(actualMATLABCPUUsage + blockingInterval) < computationSeconds/periodSeconds)
%
% unknown quantity actualMATLABCPUUsage is found:
%
% loopPassDuration = actualMATLABCPUUsage + blockingInterval
% actualMATLABCPUUsage = loopPassDuration - blockingInterval
%
% substituting into the inequality we get:
%
% (loopPassDuration - blockingInterval)/loopPassDuration < computationSeconds/periodSeconds)
%
% Note that the above is sufficient when loopPassDuration < periodSeconds.
% If loopPassDuration > periodSeconds then we must also have
% actualMATLABCPUUsage <= computationSeconds.
if(nargin<2)
error('Arguments "use_sigsetjmp" and "savemask" are required.');
end
% designate an index for the block of test parameters to be used.
tci = 1; %tci stands for test condition index.
fixedAxisY=0;
fixedAxisValueY=0.020;
% Test condition 1 shows delays at 30-second intervals.
%
%
% designate an index for this block of test parameters.
tcb= 1;
%set flags which specify various test conditions
tc(tcb).enableTCPriority=1;
%specify the 'time constraint' parameters
tc(tcb).periodSecs= 1/1000;
tc(tcb).computationSecs = tc(tcb).periodSecs/10 * 5 ;
tc(tcb).constraintSecs= tc(tcb).computationSecs;
tc(tcb).preemptibleFlag=0;
tc(tcb).blockingIntervalSecs=tc(tcb).periodSecs - tc(tcb).computationSecs;
% specify for how many seconds we want to run out timing loop
tc(tcb).testDurationSeconds = 2*60+1;
%specify a factor by which to mulitply the memory allocation estimate, for
%saftey margin.
tc(tcb).maxDisplayExcessComputationDurations=100;
% specify values describing expected period glitches. As part of the analysis after
% the timing test we search for regular glitches described by these
% paramters.
tc(tcb).interGlitchIntevalSecs = 30;
tc(tcb).interGlitchIntervalJitter = 0.1; % tolerance of interGlitchIntevalSecs value.
clear tcb; % make sure that we do not use tcb below. (It sneaks in when we cut and past from conditions above and forget to sub in tci.)
% --------------------------------------------------------------------------------------------------------------------------------------------
%
%convert units of seconds to ticks.
ticksPerSecond= MachAbsoluteTimeClockFrequency;
periodTicks = round(tc(tci).periodSecs * ticksPerSecond);
computationTicks = round(tc(tci).computationSecs * ticksPerSecond);
constraintTicks = round(tc(tci).computationSecs * ticksPerSecond);
%launch the external process with specified parameters
dataFileName= 'StandaloneTimingRawResults';
testProgramName= 'StandaloneTimingProgram'; %assumes that the executable of this name exists in the same directory as this script.
myFullName=mfilename('fullpath');
[myPath, myName, myExt, myVersionNumber] = fileparts(myFullName);
fullTestProgramName=fullfile(myPath, testProgramName);
fullDataFileName=fullfile(myPath, dataFileName);
s=' ';
invocationString=['! ' fullTestProgramName s num2str(periodTicks) s num2str(computationTicks) s ...
num2str(constraintTicks) s num2str(tc(tci).preemptibleFlag) s num2str(tc(tci).blockingIntervalSecs) ...
s num2str(tc(tci).testDurationSeconds) s num2str(use_sigsetjmp) s num2str(savemask)];
invocationStringRedirect = [invocationString ' > ' fullDataFileName];
fprintf('Timing program invoking with shell command:\n');
fprintf(invocationStringRedirect);
fprintf('\n');
fprintf('This will take %f seconds...\n', tc(tci).testDurationSeconds);
eval(invocationStringRedirect);
%open the data file created by the external proces and read back the
%results back into MATLAB
f = fopen(fullDataFileName, 'r');
tVec=fscanf(f,'%f\n');
fclose(f);
% plot stuff and calculate stuff
tVec=tVec(1:end-1);
tDiffVec=diff(tVec);
tDiffVecSampleTimes=tVec(1:end-1)-tVec(1);
plot(tDiffVecSampleTimes, tDiffVec, 'b');
xlabel('loop start time (seconds)');
ylabel('loop pass time (seconds)');
if fixedAxisY
axis([-5, max(tDiffVecSampleTimes)+5, 0, fixedAxisValueY]);
else
axis([-5, max(tDiffVecSampleTimes)+5, 0, 1.25 *max(max(tDiffVec), tc(tci).periodSecs)]);
end
minLoopDuration=min(tDiffVec);
maxLoopDuration=max(tDiffVec);
medianLoopDuration=median(tDiffVec);
fprintf('The shortest loop was: %f seconds\n', minLoopDuration);
fprintf('The longest loop was: %f seconds\n', maxLoopDuration);
fprintf('The median loop was: %f seconds\n', medianLoopDuration);
%plot horizontal lines across the graph marking "time constraint"
%parameters "period" and the blocking interval.
hold on;
periodSecsLineX=[0 tc(tci).testDurationSeconds];
periodSecsLineY=[tc(tci).periodSecs tc(tci).periodSecs ];
plot(periodSecsLineX, periodSecsLineY, 'g');
blockingSecsLineX=periodSecsLineX;
blockingSecsLineY=[tc(tci).blockingIntervalSecs tc(tci).blockingIntervalSecs ];
plot(blockingSecsLineX, blockingSecsLineY, 'r');
% Find the n longest glitches. n is set with the assumption that
% the total number of glitches is predicted by their falling
% at 30-second intervals. If that assumption is wrong then
% we will not find all of the long glitches
numExpectedGlitches=floor(tc(tci).testDurationSeconds/tc(tci).interGlitchIntevalSecs);
[sortedtDiffVec, sortedtDiffVecIndices]=sort(tDiffVec);
sortedtDiffVecRev=fliplr(sortedtDiffVec);
sortedtDiffVecIndicesRev=fliplr(sortedtDiffVecIndices);
nLongestGlitches= sortedtDiffVecRev(1:numExpectedGlitches);
nLongestGlitchesIndices=sortedtDiffVecIndicesRev(1:numExpectedGlitches);
nLongestGlitchesTimestamps=tDiffVecSampleTimes(nLongestGlitchesIndices);
[nLongestGlitchesTimestampsSequenced, nLongestGlitchesTimestampsSequencedIndices]=sort(nLongestGlitchesTimestamps);
interGlitchIntervals=diff(nLongestGlitchesTimestampsSequenced);
% for i=1:numExpectedGlitches
% plot(nLongestGlitchesTimestamps(i), nLongestGlitches(i), 'rx');
% end
hold off;
fprintf([int2str(numExpectedGlitches) ' glitches predicted in ' num2str(tc(tci).testDurationSeconds) ' second test interval, assuming 30-second interval between glitches\n']);
fprintf(['The ' int2str(numExpectedGlitches) ' longest loop delays occured at times and intervals:\n']);
for i=1:numExpectedGlitches
fprintf([ '\t' num2str(nLongestGlitchesTimestampsSequenced(i)) ' s\n']);
if i<numExpectedGlitches
fprintf([ '\t\tdelta=' num2str(interGlitchIntervals(i)) ' s\n']);
end
end
%identify those glitches among the longest 4 which fall at 30-second
%intervals. First find the intervals of 30-second duration, then find
%the samples which mark the end points of those intervals.
synchedIntervalDoubleIndices=find( (interGlitchIntervals < (tc(tci).interGlitchIntevalSecs + tc(tci).interGlitchIntervalJitter)) & (interGlitchIntervals > (tc(tci).interGlitchIntevalSecs - tc(tci).interGlitchIntervalJitter)));
if ~isempty(synchedIntervalDoubleIndices)
synchedIntervals=interGlitchIntervals(synchedIntervalDoubleIndices);
intervalsStartGlitchesTimestamps=nLongestGlitchesTimestampsSequenced(1:end-1);
intervalsEndGlitchesTimestamps=nLongestGlitchesTimestampsSequenced(2:end);
synchedGlitchesTimestamps=unique([intervalsStartGlitchesTimestamps(synchedIntervalDoubleIndices) intervalsEndGlitchesTimestamps(synchedIntervalDoubleIndices)]);
else
synchedGlitchesTimestamps=[];
end
% find the next longest glitch.
nextLongestDelay=sortedtDiffVecRev(numExpectedGlitches+1);
nextLongestDelayIndex=sortedtDiffVecIndicesRev(numExpectedGlitches+1);
nextLongestDelayTimestamp=tDiffVecSampleTimes(nextLongestDelayIndex);
fprintf(['The ' int2str(numExpectedGlitches+1) 'th longest loop delay, ']);
fprintf(['at time ' num2str(nextLongestDelayTimestamp) ' seconds, was ' num2str(nextLongestDelay) ' seconds, ']);
fprintf([num2str(nLongestGlitches(numExpectedGlitches)/nextLongestDelay) ' times smaller than the ' int2str(numExpectedGlitches) 'th longest delay\n']);
% Check to see that we always blocked for the specified period.
underBlockIndices=find(tDiffVec < tc(tci).blockingIntervalSecs);
underBlocks=tDiffVec(underBlockIndices);
if ~isempty(underBlocks)
fprintf('Detected loop durations shorter than blocking period. The durations and times are:\n');
for i=1:length(underBlocks);
fprintf(['\t' num2str(underBlocks(i)) '\t' num2str(tDiffVecSampleTimes(underBlockIndices(i))) '\n']);
end
end
% Check to see when we exceeded the specified "computation" CPU time
% allowance specified when assigning 'time constraint' priority. excessComputationSecsIndices=find(measuredComputationSecs > tc(tci).computationSecs);
measuredComputationSecs=tDiffVec-tc(tci).blockingIntervalSecs;
excessComputationSecsIndices=find(measuredComputationSecs > tc(tci).computationSecs);
excessComputationSecs=measuredComputationSecs(excessComputationSecsIndices);
excessComputationTotalSecs=tDiffVec(excessComputationSecsIndices);
exessComputationSecsTimes=tDiffVecSampleTimes(excessComputationSecsIndices);
numExcessComputationLoops=length(excessComputationSecs);
fprintf(['The timing loop computation time exceeded the allocated computation time on ' int2str(numExcessComputationLoops) ' loops.\n']);
if numExcessComputationLoops > 0
fprintf('The loop durations, computation times, and timestamps are listed below.\n');
if numExcessComputationLoops > tc(tci).maxDisplayExcessComputationDurations
fprintf(['(only the first ' int2str(tc(tci).maxDisplayExcessComputationDurations) ' are dislayed)\n']);
end
for i = 1:min([numExcessComputationLoops, tc(tci).maxDisplayExcessComputationDurations])
fprintf('\t%1.5f\t%1.5f\t%2.5f\n', excessComputationTotalSecs(i), excessComputationSecs(i), exessComputationSecsTimes(i) );
end
end
% Check for compliance with:
% (loopPassDuration - blockingInterval)/loopPassDuration < computationSeconds/periodSeconds)
% For more info see notes at top of the file about this.
% For the tests which use flip instead of BlockSecs we do not actually
% know the blocking interval. This section should be modified accordingly.
computationRatioLimit = tc(tci).computationSecs / tc(tci).periodSecs;
computationRatios = (tDiffVec - tc(tci).blockingIntervalSecs) / medianLoopDuration;
computationRatioViolationIndices=find(computationRatios > computationRatioLimit);
computationRatioViolationDurations=tDiffVec(computationRatioViolationIndices);
computationRatioViolationTimestamps=tDiffVecSampleTimes(computationRatioViolationIndices);
numComputationRatioViolations=length(computationRatioViolationIndices);
% Check to see if we exceed the "computation" CPU time allowance before the
% first glitch. One possible explanation for the glitches is that the
% Mach Kernel revokes realtime status at 30-second intervals as penalty
% for the main MATLAB thread exceeding "computation" allowance. However,
% if the thread has not exceeded that allowance before the first
% synchronized glitch, that would rule out the possibility.
if ~isempty(synchedGlitchesTimestamps)
earlyComputationViolations=exessComputationSecsTimes(exessComputationSecsTimes < min(synchedGlitchesTimestamps));
if isempty(earlyComputationViolations)
fprintf('The MATLAB thread did not exceed the CPU computation allowance before the first synchronized glitch.\n');
else
fprintf('The MATLAB thread exceeded the CPU computation allowance before the first synchronized glitch.\n');
fprintf(['The violations occured at times: ' num2str(earlyComputationViolations) '\n']);
end
end
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