We will now use the Process object of the multiprocessing module to construct parallel row-partitioned matrix multiplication. Each of the three processes receives its row and matrix B from the master process and multiplies them to create the row of the output matrix C. The input matrices A and B are tiny 33 matrices. The associated row of matrixC from a worker is then sent to the master.For this algorithm, we must take the following into account: when a process is spawned using the Process module, it has all of the data of the parent process but the modifications it makes are not reflected in the parent process. In order to have the product matrix C shared between the processes, we need to use the Manager object of the multiprocessing module and define C as an array to be shared from this object. Each worker process performs multiplication and stores the result in its row entry of matrix C. implement above statement in python
We will now use the Process object of the multiprocessing module to construct parallel row-partitioned matrix multiplication. Each of the three processes receives its row and matrix B from the master process and multiplies them to create the row of the output matrix C. The input matrices A and B are tiny 33 matrices. The associated row of matrixC from a worker is then sent to the master.For this
implement above statement in python
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