MATLAB:在并行模式下运行全局变量时会发生什么

Question

全局变量在并行模式下运行时会发生什么?

我有一个全局变量，"to_be_optimized_parameterIndexSet"，这是一个索引向量，应该使用gamultiobj进行优化，我只在主脚本中设置了它的值(没有其他地方)。

我的代码在串行模式下正常工作，但当我切换到并行模式(使用"matlabpool open"并为"gaoptimset"设置适当的值)时，提到的全局变量在适应度函数中变为空(=[])并导致此错误:

??? Error using ==> parallel_function at 598
Error in ==> PF_gaMultiFitness at 15 [THIS LINE: constants(to_be_optimized_parameterIndexSet) = individual;]
 In an assignment  A(I) = B, the number of elements in B and
 I must be the same.
Error in ==> fcnvectorizer at 17
        parfor (i = 1:popSize)
Error in ==> gamultiobjMakeState at 52
        Score =
        fcnvectorizer(state.Population(initScoreProvided+1:end,:),FitnessFcn,numObj,options.SerialUserFcn);
Error in ==> gamultiobjsolve at 11
state = gamultiobjMakeState(GenomeLength,FitnessFcn,output.problemtype,options);
E    rror in ==> gamultiobj at 238
[x,fval,exitFlag,output,population,scores] = gamultiobjsolve(FitnessFcn,nvars, ...
Error in ==> PF_GA_mainScript at 136
[x, fval, exitflag, output] = gamultiobj(@(individual)PF_gaMultiFitness(individual, initialConstants), ...
Caused by:
    Failure in user-supplied fitness function evaluation. GA cannot continue.

我检查了所有的代码，以确保我没有在其他地方改变这个全局变量。

我有一个四核处理器。

bug在哪里?任何建议吗?

EDIT 1:主脚本中的MATLAB代码:

clc
clear
close all
format short g
global simulation_duration % PF_gaMultiFitness will use this variable
global to_be_optimized_parameterIndexSet % PF_gaMultiFitness will use this variable
global IC  stimulusMoment % PF_gaMultiFitness will use these variables
[initialConstants IC] = oldCICR_Constants; %initialize state
to_be_optimized_parameterIndexSet = [21    22    23    24    25    26    27    28    17    20];
LB = [ 0.97667      0.38185      0.63529     0.046564      0.23207      0.87484      0.46014    0.0030636   0.46494      0.82407 ];
UB = [1.8486      0.68292      0.87129      0.87814      0.66982       1.3819      0.64562      0.15456   1.3717       1.8168];
PopulationSize = input('Population size? ') ;
GaTimeLimit = input('GA time limit? (second)  ');
matlabpool open
nGenerations = inf;
options = gaoptimset('PopulationSize', PopulationSize, 'TimeLimit',GaTimeLimit, 'Generations', nGenerations, ...
    'Vectorized','off', 'UseParallel','always');
[x, fval, exitflag, output] = gamultiobj(@(individual)PF_gaMultiFitness(individual, initialConstants), ...
    length(to_be_optimized_parameterIndexSet),[],[],[],[],LB,UB,options);
matlabpool close
some other piece of code to show the results...

适应度函数"PF_gaMultiFitness"的MATLAB代码:

function objectives =PF_gaMultiFitness(individual, constants)
global simulation_duration IC stimulusMoment to_be_optimized_parameterIndexSet
%THIS FUNCTION RETURNS MULTI OBJECTIVES AND PUTS EACH OBJECTIVE IN A COLUMN
constants(to_be_optimized_parameterIndexSet) = individual;
[smcState , ~, Time]= oldCICR_CompCore(constants, IC, simulation_duration,2);
targetValue = 1; % [uM]desired [Ca]i peak concentration
afterStimulus = smcState(Time>stimulusMoment,14); % values of [Ca]i after stimulus
peak_Ca_value = max(afterStimulus); % smcState(:,14) is [Ca]i
if peak_Ca_value < 0.8 * targetValue
    objectives(1,1) = inf;
else
    objectives(1, 1) =  abs(peak_Ca_value - targetValue);
end
pkIDX = peakFinder(afterStimulus);
nPeaks = sum(pkIDX);
if nPeaks > 1
    peakIndexes = find(pkIDX);
    period = Time(peakIndexes(2)) - Time(peakIndexes(1));
    objectives(1,2)  = 1e5* 1/period;
elseif nPeaks ==   1 && peak_Ca_value > 0.8 * targetValue
    objectives(1,2) = 0;
else 
    objectives(1,2) = inf;
end

end

Answer 1

全局变量不会从MATLAB客户端传递给执行PARFOR循环主体的工作器。唯一被发送到循环体中的数据是程序文本中的变量。

Answer 2

这取决于你放入的变量的类型。我需要看到更多的代码来指出这个缺陷，但一般来说，避免假设复杂的变量将传递给每个worker是一种良好的做法。换句话说，任何超出原语的对象都可能需要在并行例程中重新初始化，或者可能需要特定的函数调用(比如对函数句柄使用feval)。

我的建议:RTM