Matrix Multiplication Multi Thread
Time python ikjMultiplicationpy -i 2000in 2000-nonparallelout real 36m0699s user 35m53463s sys 0m2356s. That will greatly simplify your code.
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Matrix multiplication between a IxJ matrix d_M and JxK matrix d_N produces a matrix d_P with dimensions IxK.
Matrix multiplication multi thread. Multi-threading can be done to improve it. The input to the program is two matrices A xy and B yz that are read from corresponding files while he output is a matrix C xz that is written to an output file. The most simple way to parallelize the ikj algorith is to use the multiprocessing module and compute every line of the result matrix.
Matrix-Multiplication-Using-ThreadsmatrixmultiplicationMatrixMultiplicationjava Jump toCode definitionsMatrixMultiplication Class main Method. Int rows1 matrix1length. I first created threads equal to the result matrixs column.
The normal method for multiplying two such matrices involves performing all the calculations in the main thread. This action is self contained and requires no synchronization within you thread code. Thread thread new Threadtask.
Matrix3 allocate_matrix size. In multi-threading instead of utilizing a single core of your processor we utilizes all or more core to solve the problem. If size num_threads 0 fprintf stderr size d must be a multiple of num of threads d n size num_threads.
For int i 0. Matrix1 allocate_matrix size. It has both implementation of matrix multiplication- one without multi-threading and another one using multi-threading.
Once its done it advances by n rows. A very simple demo program of multiplying two matrices using SDL threads. Depending upon the number of cores your processor has you can create the number of threads required.
For k in range len Y. Import time m 100 X 1mm Y 1mm def mult X Y. The ikj single core algorithm implemented in Python needs.
For example if you need to add two matrices on n threads divide the destination matrix every heightn rows and give each thread those rows only. Although you can create as many threads as you need a better way is to create each thread. In the multi-threaded version you will divide this computation among threads to achieve parallelism.
You start with threads 0n-1. Each thread Calculates a Matrix Value and sets it to C matrix. Public static void multiplyint matrix1 int matrix2 int result List threads new ArrayList.
Code for matrix multiplication using a Single thread. Creates 9 Worker threads. Matrix2 allocate_matrix size.
Result 0 z X 0 Y k z print result start timeperf_counter for i in range len X 0. Each element ij of the product matrix is obtained by multiplying the ith row of the first matrix with the jth column of the second. A thread computes each row in the output C matrix.
Thread i starts processing at row i. Note that matrix multiplication lends itself to using multiple threads in a non-blocking manner. Return-1 threads pthread_t malloc num_threads sizeof pthread_t.
A parallelized version of matrix multiplication can be done using one of the following two methods. The thing to remember is that c ij sum a ik b kj for all k. Mult X i Y end timeperf_counter print fTime taken to complete mult mx m without threading.
Private static void waitForThreadsList threads for Thread thread. The formula used to calculate elements of d_P is d_Pxy 𝝨. I RowMultiplyWorker task new RowMultiplyWorkerresult matrix1 matrix2 i.
If threadssize 10 0 waitForThreadsthreads. Result 0m for z in range len Y 0. For multi-threading implementation I used Javas Executor Framework.
We create different threads each thread evaluating some part of matrix multiplication. Init_matrix matrix1 size.
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