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parallel coding: how to solve linear system?

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Hi everyone! I need to solve a (very large) linear system in my code, so I'm trying to use a parallel session.
Basically my original local code does the following:
function U = myfun(U0,J0,nx,S0,Mbcs,Bbcs)
A = spdiags(funA(J0),0,nx,nx);
B = spdiags(funB(J0),0,nx,nx);
C = spdiags(funC(J0),0,nx,nx);
D = spdiags(funD(J0),0,nx,nx);
K = [A B; C D];
V = S0;
K([1,nx,nx+1,2*nx],:)=0;
V([1,nx,nx+1,2*nx])=0;
K = K + Mbcs;
V = V + Bbcs;
U = K\V;
The use of sparse array speeds up a lot the solver time. Now I tried to launch a parallel session:
parpool('local2');
And the code was modified as follows for distributing the matrices to the workers:
K = distributed(K);
V = distributed(V);
But at the end I get this error:
Error using \ (line 48)
Sparse input arguments are not supported.
Error in distributed/wrapRemoteCall>iInnerWrapper (line 83)
[varargout{:}] = fcnH( varargin{:} );
Error in spmd_feval_fcn>get_f/body (line 78)
[outCell{:}] = fcnH( inCell{:} );
Where is the error? I don't know much about parallel programming, but from the examples I found, it seems to me that I only need do distribute the matrix to the workers.
Thanks in advance for all your suggestions.
Pietro

Accepted Answer

Edric Ellis
Edric Ellis on 19 Mar 2015
Unfortunately, as the error message states, you cannot use the \ operator with sparse distributed arrays at this time.
  4 Comments
Edric Ellis
Edric Ellis on 20 Mar 2015
Unfortunately, the best options you have are either:
  1. Use sparse on your local machine
  2. Use dense distributed arrays on a cluster
  3. Solve a smaller problem
Note that distributed arrays on a single machine almost never offer any benefit since most linear algebra operations are already fairly efficiently multi-threaded by MATLAB, and using a multi-process approach cannot usually compete.

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