Assume an Python MPI program where a master node sends a pair of complex matrices to each worker node and the worker node is supposed to compute their product (conventional matrix product). The input matrices are constructed at the master node according to some algorithm which there is no need to explain. Now imagine for simplicity that we have only 2 MPI processes, one master and one worker. I have created two versions of this program for this case. The first one constructs two complex numbers (1-by-1 matrices for simplicity) and sends them to the worker to compute the product. This program is like a skeleton for what I am trying to do with multiple workers. In the second program, I have omitted the algorithm and have just hard-coded these two complex numbers into the code. The programs are supposed to give the same product shown here:
a = 28534314.10478439+28534314.10478436j b = -1.39818115e+09+1.39818115e+09j a*b = -7.97922802e+16+48j This has been checked in Matlab. Instead, the first program does not work and the worker gives a*b = -7.97922801e+16+28534416.j while the second program works correctly. Please note that the data is transmitted correctly from the master to the worker and the data structures are the same in both cases (see the print() functions). The first (wrong) program is program1.py and the second (correct) is program2.py I am using MPI4py 3.0.0. along with Python 2.7.14 and the kernel of Open MPI 2.1.2. I have been straggling with this problem for a whole day and still cannot figure out what's going on. I have tried numerous initializations like np.zeros(), np.zeros_like(), np.empty_like() as well as both np.array and np.matrix and functions np.dot(), np.matmul() and the operator *. Finally, I think that the problem is always with the imaginary part of the product based on other examples I tried. Any suggestions?
program1.py
Description: Binary data
program2.py
Description: Binary data
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