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Need to pass the entire global workspace, if subroutines called by the _core loops need them. Updated parallel test.

time-shift
Marco Ratto 2012-09-11 15:45:08 +02:00
parent 8789151c73
commit 428b193c11
2 changed files with 7 additions and 13 deletions
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14
matlab/parallel/masterParallel.m
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@ -92,9 +92,7 @@ if nargin>8 && initialize==1
evalin('base','clear PRCDirTmp,')
else
% Delete the traces (if existing) of last local session of computations.
if Strategy==1,
mydelete(['slaveParallel_input*.mat']);
end
mydelete(['slaveParallel_input*.mat']);
end
return
end
@ -128,12 +126,8 @@ end
% Save input data for use by the slaves.
switch Strategy
case 0
if exist('fGlobalVar'),
save([fname,'_input.mat'],'fInputVar','fGlobalVar')
else
save([fname,'_input.mat'],'fInputVar')
end
save([fname,'_input.mat'],'Parallel','-append')
storeGlobalVars([fname,'_input.mat']);
save([fname,'_input.mat'],'fInputVar','Parallel','-append')
case 1
if exist('fGlobalVar'),
@ -270,7 +264,7 @@ for j=1:totCPU,
% are created localy, then copied in remote directory and then
% deleted (loacal)!
save( ['slaveParallel_input',int2str(j),'.mat'],'Parallel');
save( ['slaveParallel_input',int2str(j),'.mat'],'j');
if Parallel(indPC).Local==0,
dynareParallelSendFiles(['P_',fname,'_',int2str(j),'End.txt'],PRCDir,Parallel(indPC));

6
tests/parallel/ls2003.mod
View File

@ -62,8 +62,8 @@ stderr e_pies,inv_gamma_pdf,1.88,0.9827;
end;
estimation(datafile=data_ca1,first_obs=8,nobs=79,mh_replic=0);
estimation(datafile=data_ca1,first_obs=8,nobs=79,mode_compute=0, mode_file=ls2003_mode, mh_nblocks=4, prefilter=1, mh_jscale=0.5, mh_replic=2000);
estimation(datafile=data_ca1,first_obs=8,nobs=79,mode_compute=0, mode_file=ls2003_mode, mh_nblocks=4,prefilter=1,mh_jscale=0.5,mh_replic=2000,bayesian_irf,load_mh_file,smoother,forecast=12, filtered_vars, filter_step_ahead=[1 2 3 4]) y y_s R pie dq pie_s de A y_obs pie_obs R_obs;
estimation(datafile=data_ca1,first_obs=8,nobs=79,mh_replic=0,nodisplay);
estimation(datafile=data_ca1,first_obs=8,nobs=79,mode_compute=0,nodisplay, mode_file=ls2003_mode, mh_nblocks=4, prefilter=1, mh_jscale=0.5, mh_replic=2000);
estimation(datafile=data_ca1,first_obs=8,nobs=79,mode_compute=0,nodisplay, mode_file=ls2003_mode, mh_nblocks=4,prefilter=1,mh_jscale=0.5,mh_replic=2000,bayesian_irf,load_mh_file,smoother,forecast=12, filtered_vars, filter_step_ahead=[1 2 3 4]) y y_s R pie dq pie_s de A y_obs pie_obs R_obs;