I am using Iterative Methods, like preconditioned conjugate gradients to solve large sparse linear equations(800,000*800,000). I am glad to find that the distributed array could use parallel methods to achieve this. I think this may be faster. However, in my test data. The distributed array is always slower than the normal sparse matrix. (200 VS 50 seconds). Is this normal? what is the advantages of distributed array to solve the sparse linear equations? My part code is like below. Did I miss some steps for distributed array?
% A is a sparse large matrix ,800,000*800,000 size
% b is the right vector of the equations, 800,000*1 size
Adist = distributed(A);bdist = distributed(b);M = ichol(A, struct('type','ict','droptol',1e-3)); [xPCG1,flagPCG1,relresPCG1,iterPCG1,resvecPCG1]=pcg(Adist,bdist,tol,maxit,M,M'); % about 200s
[xPCG2,flagPCG2,relresPCG2,iterPCG22,resvecPCG2]=pcg(A,b,tol,maxit,M,M');% about 50s
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