Why does MATLAB R2016a produce wrong eigenvalues for large matrices (N>7799) when forced to run as a single threaded application?
Example code:
t=1;
tic;
T=gallery('tridiag',N,t,0,t);
T=full(T);
T(1,N)=t;
T(N,1)=t;
[V,D]=eig(T,'vector');
fprintf('Invoking "eig()" yields eigenvalues:\n')
fprintf('max: %2.4f \n',max(D))
fprintf('min: %2.4f \n',min(D))
toc;
exit
Execution Command:
taskset -c 0 /opt/MATLAB/R2016a/bin/matlab -nodisplay -nodesktop -nosplash -nojvm -r "N=7800;test"
The above command yields wrong eigenvalues. The correct max and min eigenvalues are supposed to be 2 and -2 respectively.
However, the following multithreaded implementation produces accurate results:
taskset -c 0,1 /opt/MATLAB/R2016a/bin/matlab -nodisplay -nodesktop -nosplash -nojvm -r "N=7800;test"
