How can use parallel programming in the below code?
显示 更早的评论
Hello. The below code calculates a PDE equation. I'd like to use parallel to speed up in finer discritization.
How is it possible to use parallel in this structure ?
Thanks.
clc
close all
%Time
delt=0.2;
totalTime = 1e3;
timestepn=round(totalTime/delt);%size(delt,2);
% parameters
L=0.29;
gamma=3;
kappa=2;
% geometry settings; % phase field numbers
mboxsize=64; % system grid numbers in x direction
nboxsize=64; % system grid numbers in y direction
delx=2; % Delta x
Nx=mboxsize;
Ny=Nx;
dx=delx;
dy=delx;
% calculation-loading data
load etas
ngrain=25;
eta2 = zeros(Nx,Ny,ngrain);
eta = etas;
eta2 = eta;
p=ngrain;
%evolution
for tn=1:10
for i=1:mboxsize
for j=1:nboxsize
% calculation of nabla square eta(Laplacian)
del2=1/delx^2*(0.5*(eta(indg(i+1,nboxsize),j,:)-2*eta(i,j,:)+eta(indg(i-1,nboxsize),j,:))...
+0.25*(eta(indg(i+2,nboxsize),j,:)-2*eta(i,j,:)+eta(indg(i-2,nboxsize),j,:)))...
+1/delx^2*(0.5*(eta(i,indg(j+1,mboxsize),:)-2*eta(i,j,:)+eta(i,indg(j-1,mboxsize),:))...
+0.25*(eta(i,indg(j+2,mboxsize),:)-2*eta(i,j,:)+eta(i,indg(j-2,mboxsize),:)));
% summation
sumterm=eta(i,j,:)*sum(eta(i,j,:).^2)-eta(i,j,:).^3;
detadtM=(-eta(i,j,:)+eta(i,j,:).^3-kappa*del2);
detadt=-L*(detadtM+2*gamma*(sumterm));
eta2(i,j,:)=eta(i,j,:)+delt*detadt;
% for making sure eta is not outside the equilibrium values
% actually it is unnecessary
for pind=1:p
if eta2(i,j,pind)>1
eta2(i,j,pind)=1;
end
if eta2(i,j,pind)<0
eta2(i,j,pind)=0;
end
end
end
end
eta=eta2;
phi=sum(eta(:,:,1:p).^2,3);
imagesc(phi)
colorbar
title(tn)
waitbar(tn/10)
end
回答（1 个）
Thiago Henrique Gomes Lobato
2020-1-12
You can indeed try to do the code in parallel with a parfor loop in the "i" loop and some tweak in the eta2 variable bound like this:
clc
close all
%Time
delt=0.2;
totalTime = 1e3;
timestepn=round(totalTime/delt);%size(delt,2);
% parameters
L=0.29;
gamma=3;
kappa=2;
% geometry settings; % phase field numbers
mboxsize=64; % system grid numbers in x direction
nboxsize=64; % system grid numbers in y direction
delx=2; % Delta x
Nx=mboxsize;
Ny=Nx;
dx=delx;
dy=delx;
% calculation-loading data
load etas
ngrain=25;
eta2 = zeros(Nx,Ny,ngrain);
eta = etas;
eta2 = eta;
p=ngrain;
%evolution
for tn=1:10
parfor i=1:mboxsize
for j=1:nboxsize
% calculation of nabla square eta(Laplacian)
del2=1/delx^2*(0.5*(eta(indg(i+1,nboxsize),j,:)-2*eta(i,j,:)+eta(indg(i-1,nboxsize),j,:))...
+0.25*(eta(indg(i+2,nboxsize),j,:)-2*eta(i,j,:)+eta(indg(i-2,nboxsize),j,:)))...
+1/delx^2*(0.5*(eta(i,indg(j+1,mboxsize),:)-2*eta(i,j,:)+eta(i,indg(j-1,mboxsize),:))...
+0.25*(eta(i,indg(j+2,mboxsize),:)-2*eta(i,j,:)+eta(i,indg(j-2,mboxsize),:)));
% summation
sumterm=eta(i,j,:)*sum(eta(i,j,:).^2)-eta(i,j,:).^3;
detadtM=(-eta(i,j,:)+eta(i,j,:).^3-kappa*del2);
detadt=-L*(detadtM+2*gamma*(sumterm));
eta2(i,j,:)=eta(i,j,:)+delt*detadt;
end
end
% for making sure eta is not outside the equilibrium values
% actually it is unnecessary
eta2(eta2>1) = 1;
eta2(eta2<0) = 0;
eta=eta2;
phi=sum(eta(:,:,1:p).^2,3);
imagesc(phi)
colorbar
title(tn)
waitbar(tn/10)
end
I however don't think this is the best solution, since the only loop you actually need to calculate is the time on. If you substitute your i and j loops for vector operations (calculate all matrix values at once) it will probably be way faster than the parallelization and your problem will have only one loop.
3 个评论
Amir Torabi
2020-1-12
编辑：Amir Torabi
2020-1-18
Thiago Henrique Gomes Lobato
2020-1-12
In your new example you're looping for "i" and then replacing it inside the loop
Amir Torabi
2020-1-18
类别
在 帮助中心 和 File Exchange 中查找有关 Eigenvalue Problems 的更多信息
2020-1-11
2020-1-18
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!
Translated by 
