use the Process object of the multiprocessing module to make Python implement row-partitioning for parallel 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: The data of the parent process is entirely present in the process when it is launched using the Process module, but any changes it makes are not reflected in the parent process.We must utilise the Manager object of the multiprocessing module and declare C as an array to be shared from this object in order to distribute the product matrix C amongst the processes. Each worker process multiplies and records the outcome in the corresponding row entry of matrix C.

use the Process object of the multiprocessing module to make Python implement row-partitioning for parallel 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: The data of the parent process is entirely present in the process when it is launched using the Process module, but any changes it makes are not reflected in the parent process.We must utilise the Manager object of the multiprocessing module and declare C as an array to be shared from this object in order to distribute the product matrix C amongst the processes. Each worker process multiplies and records the outcome in the corresponding row entry of matrix C.

C++ for Engineers and Scientists

4th Edition

ISBN:9781133187844

Author:Bronson, Gary J.

Publisher:Bronson, Gary J.

Chapter13: Structures

Section: Chapter Questions

Problem 4PP

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make python implement parallel matrix multiplication by row-partitioning using theProcess object of multiprocessing module. The input matrices A and B are small3×3 matrices and each of 3 processes receives its row and matrix B from the masterprocess, multiplies its row with matrix B to form the row of product matrix C. Aworker then sends its associated row of matrixC to the master.We need to consider thefollowing for this algorithm: 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 notreflected in the parent process. In order to have the product matrix C shared betweenthe processes, we need to use the Manager object of the multiprocessing module anddefine C as an array to be shared from this object. Each worker process performsmultiplication and stores the result in its row entry of matrix C.
implement parallel matrix multiplicationC = A×B by row partitioningmatrix A and sending each process its partition and the whole of matrix B. Eachprocess performs its own multiplication and sends the partial product to the masterprocess which collects all results and then prints the product matrix C, we have 4processes including the master process. The output matrix C displayed is the product of matrices A and B.use python to code.
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