GPU accelerated image processing for everyone
Multiplies two matrices with each other.
Category: Math
Availability: Available in Fiji by activating the update sites clij and clij2. This function is part of clij2_-2.5.0.1.jar.
Ext.CLIJ2_multiplyMatrix(Image matrix1, Image matrix2, Image matrix_destination);
// init CLIJ and GPU import net.haesleinhuepf.clij2.CLIJ2; import net.haesleinhuepf.clij.clearcl.ClearCLBuffer; CLIJ2 clij2 = CLIJ2.getInstance(); // get input parameters ClearCLBuffer matrix1 = clij2.push(matrix1ImagePlus); ClearCLBuffer matrix2 = clij2.push(matrix2ImagePlus); matrix_destination = clij2.create(matrix1);
// Execute operation on GPU clij2.multiplyMatrix(matrix1, matrix2, matrix_destination);
// show result matrix_destinationImagePlus = clij2.pull(matrix_destination); matrix_destinationImagePlus.show(); // cleanup memory on GPU clij2.release(matrix1); clij2.release(matrix2); clij2.release(matrix_destination);
% init CLIJ and GPU clij2 = init_clatlab(); % get input parameters matrix1 = clij2.pushMat(matrix1_matrix); matrix2 = clij2.pushMat(matrix2_matrix); matrix_destination = clij2.create(matrix1);
% Execute operation on GPU clij2.multiplyMatrix(matrix1, matrix2, matrix_destination);
% show result matrix_destination = clij2.pullMat(matrix_destination) % cleanup memory on GPU clij2.release(matrix1); clij2.release(matrix2); clij2.release(matrix_destination);
// init CLIJ and GPU importClass(net.haesleinhuepf.clicy.CLICY); importClass(Packages.icy.main.Icy); clij2 = CLICY.getInstance(); // get input parameters matrix1_sequence = getSequence(); matrix1 = clij2.pushSequence(matrix1_sequence); matrix2_sequence = getSequence(); matrix2 = clij2.pushSequence(matrix2_sequence); matrix_destination = clij2.create(matrix1);
// Execute operation on GPU clij2.multiplyMatrix(matrix1, matrix2, matrix_destination);
// show result matrix_destination_sequence = clij2.pullSequence(matrix_destination) Icy.addSequence(matrix_destination_sequence); // cleanup memory on GPU clij2.release(matrix1); clij2.release(matrix2); clij2.release(matrix_destination);
import pyclesperanto_prototype as cle cle.multiply_matrix(matrix1, matrix2, matrix_destination)
matrix_multiply
multiply_matrices.ipynb
matrix_multiplication.ipynb
matrix_multiply.ijm
matrix_multiply.m
matrix_multiply_benchmarking.m