Copy and Paste  -   An Application to Copy/Paste Text
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S.No 5728 Name ..... Date/Time 20-Jun-2023 08:38:08 AM Copy text from below import numpy as np N = 100 # Size of the matrices # Generate random matrices A and B A = np.random.rand(N, N) B = np.random.rand(N, N) # Sequential matrix multiplication def matrix_multiplication(A, B): rows_A, cols_A = A.shape rows_B, cols_B = B.shape # Check if matrices can be multiplied if cols_A != rows_B: raise ValueError("Matrices dimensions are not compatible for multiplication.") # Initialize resulting matrix C C = np.zeros((rows_A, cols_B)) # Perform matrix multiplication for i in range(rows_A): for j in range(cols_B): for k in range(cols_A): C[i][j] += A[i][k] * B[k][j] return C # Perform matrix multiplication using sequential algorithm C_seq = matrix_multiplication(A, B) # Print the resulting matrix C print("Sequential matrix multiplication:") print(C_seq) from mpi4py import MPI # Initialize MPI comm = MPI.COMM_WORLD num_processes = comm.Get_size() rank = comm.Get_rank() # Scatter matrix A to all other processes if rank == 0: scattered_A = np.array_split(A, num_processes) else: scattered_A = None # Receive the scattered portion of matrix A local_A = comm.scatter(scattered_A, root=0) # Print the received portion of matrix A on each process print("Rank", rank, "received portion of matrix A:") print(local_A) # Scatter matrix B to all processes scattered_B = comm.bcast(B, root=0) # Print the received portion of matrix B on each process print("Rank", rank, "received portion of matrix B:") print(scattered_B) # Perform local matrix multiplication local_C = matrix_multiplication(local_A, scattered_B) # Print the resulting local matrix on each process print("Rank", rank, "local matrix multiplication result:") print(local_C)# Reduce the local matrix portions using MPI_Reduce with the MPI_SUM operation reduced_C = comm.reduce(local_C, op=MPI.SUM, root=0) # Print the resulting matrix C on process rank 0 if rank == 0: print("Parallel matrix multiplication result:") print(reduced_C) import time # Measure the execution time of sequential matrix multiplication start_time = time.time() C_seq = matrix_multiplication(A, B) end_time = time.time() seq_execution_time = end_time - start_time # Measure the execution time of parallel matrix multiplication start_time = time.time() local_C = matrix_multiplication(local_A, scattered_B) reduced_C = comm.reduce(local_C, op=MPI.SUM, root=0) end_time = time.time() parallel_execution_time = end_time - start_time # Print the execution times if rank == 0: print("Sequential execution time:", seq_execution_time) print("Parallel execution time:", parallel_execution_time) comments powered by Disqus NEW ENTRIES S.No Name Entry Time/Date 5905 Comfort Ride 29-Feb-2024 04:03:14 PM 5904 David\'s RV P 26-Feb-2024 11:15:44 AM 5903 Child HOT 22-Feb-2024 06:43:26 AM 5902 Dumpsterfl 20-Feb-2024 01:33:22 PM 5901 Danielle Simpson 18-Feb-2024 03:26:15 AM 5900 KID Vids 05-Feb-2024 08:43:49 AM 5899 02-Feb-2024 07:00:42 PM 5898 pool 26-Jan-2024 06:49:53 PM 5897 vvvv 24-Jan-2024 08:50:49 PM 5896 qqqqq 24-Jan-2024 08:26:57 PM 5895 addmaxexport 20-Jan-2024 06:39:13 PM 5894 geophrmarx 20-Jan-2024 06:38:48 PM 5893 readymedicin 20-Jan-2024 06:38:01 PM 5892 18-Jan-2024 10:37:50 AM 5891 Full-CP 17-Jan-2024 12:09:21 PM 5890 ss 17-Jan-2024 10:12:18 AM 5889 NEW KIDs 16-Jan-2024 08:06:16 AM 5888 Test 2 13-Jan-2024 11:57:53 AM 5887 Child Vids 09-Jan-2024 06:40:28 AM 5886 EntranceIQ 05-Jan-2024 02:04:27 PM 5885 New Child 03-Jan-2024 07:13:03 AM 5884 xyz 31-Dec-2023 04:09:19 AM 5883 aaaaaa 29-Dec-2023 01:24:48 AM 5882 Saragamasa 29-Dec-2023 01:19:17 AM 5881 copyWithin() 28-Dec-2023 09:21:58 AM 5880 Paster 27-Dec-2023 10:02:58 PM 5879 imagePicker 22-Dec-2023 10:33:52 PM 5878 Test 1 22-Dec-2023 11:07:15 AM 5877 Test 2 22-Dec-2023 11:06:28 AM 5876 Test 3 22-Dec-2023 11:04:29 AM [First] [Prev] 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 [Next] [Last]
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