matrix_softmax.cu File Reference

Implementation of the softmax function for matrices. More...

#include "matrix.h"
#include <cuda_runtime.h>
#include <cfloat>

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Functions
__global__ void	softmaxKernel (const double *input, double *output, int rows, int cols)
	CUDA kernel for applying the softmax function column-wise. More...

Detailed Description

Implementation of the softmax function for matrices.

Definition in file matrix_softmax.cu.

Function Documentation

softmaxKernel()

__global__ void softmaxKernel	(	const double *	input,
		double *	output,
		int	rows,
		int	cols
	)

CUDA kernel for applying the softmax function column-wise.

Parameters

input	Pointer to the input matrix data.
output	Pointer to the output matrix data.
rows	Number of rows in the matrix.
cols	Number of columns in the matrix.

Definition at line 17 of file matrix_softmax.cu.

                                                                                       {
    // Calculate the column index
    int col = blockIdx.x * blockDim.x + threadIdx.x;
    
    // Check if the column is within bounds
    if (col < cols) {
        // Initialize maximum value to negative infinity
        double max_val = -DBL_MAX;
        
        // Find the maximum value in the column
        for (int row = 0; row < rows; ++row) {
            max_val = fmax(max_val, input[row * cols + col]);
        }
        
        // Initialize sum of exponentials
        double sum_exp = 0.0;
        
        // Calculate the sum of exponentials
        for (int row = 0; row < rows; ++row) {
            sum_exp += exp(input[row * cols + col] - max_val);
        }
        
        // Add a small epsilon to avoid division by zero
        sum_exp += 1e-15;
        
        // Apply softmax function
        for (int row = 0; row < rows; ++row) {
            output[row * cols + col] = exp(input[row * cols + col] - max_val) / sum_exp;
        }
    }
}