From MathWorks User Community thread.

http://www.mathworks.com/matlabcentral/newsreader/view_thread/261541

As was discussed here not too long ago, the order in which
one adds numbers represented by inexact floating point formats
might have an impact on the magnitude of the error in the
end result:

>> v = rand(1000,1);
>> V = sort(v);
>> s = sum(v);
>> S = sum(V);
>> s-S % Should equal 0

ans =

 -1.7053e-013

In a matrix-vector multiplication, all the threads need
access to the vector. It might be that the two threads
access the variables in non-obvious ways to minimize the
chance of race conditions or deadlocks.