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./perceptron

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nvcc -arch=sm_50 -rdc=true -lcudadevrt onehiddenlayerperceptron.cu -o perceptron

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Prediction[0] : 0.060997 True Value[0] : 0.000000 Error[0] : 0.060997
Prediction[1] : 0.076193 True Value[1] : 0.000000 Error[1] : 0.076193
Prediction[2] : 0.927551 True Value[2] : 1.000000 Error[2] : -0.072449
Prediction[3] : 0.918263 True Value[3] : 1.000000 Error[3] : -0.081737

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dDot_m1T_m2( X, l_1_d, W0, X_h, X_w, l1_w );

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__global__ void kDot_m1_m2T(const float *m1, const float *m2, float *output, const int m1_columns, const int m2_rows ){
	/*  Updates the output matrix with the product of two matrices: m1 and m2 transposed.
	   	Inputs:
	    m1: array, left matrix of size m1_rows x m1_columns
	    m2: array, right matrix of size m2_rows x m1_columns (m2 transposed will be of size m1_columns x m2_rows)
	    output: array, the results of the computation are to be stored here:
	    		m1 * m2, product of two arrays m1 and m2, a matrix of size m1_rows x m2_rows
	    m1_columns: int, number of columns in the left matrix m1
	    m2_rows: int, number of rows in the left matrix m2
	*/

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dMartixByMatrixElementwise(dDot_m1_m2T(pred_d, W1, l_1_d, X_h, y_w, l1_w), dSigmoid_d(l1, buffer, X_h, l1_w), l_1_d, X_h, l1_w);

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__global__ void kMartixByMatrixElementwise(const float *m1, const float *m2, float *output) {
  /*  Computes the product of two arrays (elementwise multiplication).
   Inputs:
   m1: array
   m2: array
   output: array,the results of the multiplication are to be stored here
  */

  const int id = blockIdx.x * blockDim.x + threadIdx.x;

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__global__ void kMartixSubstractMatrix(const float *m1, const float *m2, float *output) {
    /*  Computes the (elementwise) difference between two arrays
     Inputs:
     m1: array
     m2: array
     output: array,the results of the computation are to be stored here
     */

    const int id = blockIdx.x * blockDim.x + threadIdx.x;

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dMartixByMatrixElementwise(dMartixSubstractMatrix(y, pred, pred_d, X_h, y_w), dSigmoid_d(pred, buffer, X_h, y_w), pred_d, X_h, y_w );

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dSigmoid(dDot(l1, W1, pred, X_h, l1_w, y_w), pred, X_h, y_w);