Add Kernels namespace

src/kernels/convolution.cu

@@ -1,7 +1,84 @@
 #include "convolution.cuh"
 #include <iostream>
 
-__global__ void convolution_kernel(
+/*
+Pads matrix width x height x n_channels to width + 2 * padding x height + 2 *
+padding x n_channels Matrix is represented as a pointer to a vector
+
+For example:
+
+w = 2
+h = 3
+n = 2
+p = 1
+
+Channel 0:
+  0  1
+  2  3
+  4  5
+Channel 1:
+  6  7
+  8  9
+ 10 11
+
+Is represented as:
+
+0 1 2 3 4 5 6 7 8 9 10 11
+
+Padded result (as a continuous vector):
+
+0.0f, 0.0f, 0.0f, 0.0f,
+0.0f, 0.0f, 1.0f, 0.0f,
+0.0f, 2.0f, 3.0f, 0.0f,
+0.0f, 4.0f, 5.0f, 0.0f,
+0.0f, 0.0f, 0.0f, 0.0f,
+0.0f, 0.0f, 0.0f, 0.0f,
+0.0f, 6.0f, 7.0f, 0.0f,
+0.0f, 8.0f, 9.0f, 0.0f,
+9.0f, 10.0f, 11.0f, 0.0f,
+0.0f, 0.0f, 0.0f, 0.0f
+
+Args:
+  d_input: Pointer to input vector representing matrix
+  d_padded: Pointer to output vector representing padded matrix (needs to be
+pre-allocated)
+  w: Width of input matrix
+  h: Height of input matrix
+  n: Number of channels in input matrix
+  p: Padding
+*/
+__global__ void Kernels::padding(
+    const float* d_input,
+    float*       d_padded,
+    int          w,
+    int          h,
+    int          n,
+    int          p
+) {
+    int tid = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (tid >= (w + 2 * p) * (h + 2 * p) * n) {
+        return;
+    }
+
+    int idx = tid;
+
+    // unravel index into padded matrix
+    int i_n = idx / ((w + 2 * p) * (h + 2 * p));
+    int i_h = idx % ((w + 2 * p) * (h + 2 * p)) / (w + 2 * p);
+    int i_w = idx % (w + 2 * p);
+
+    // if i is in the padding region
+    if (i_w < p || i_w >= (w + p) || i_h < p || i_h >= (h + p)) {
+        d_padded[tid] = 0.0f;
+    } else {
+        // Get index into input vector
+        int i_orig    = i_n * w * h + (i_h - p) * w + (i_w - p);
+        d_padded[tid] = d_input[i_orig];
+    }
+}
+
+__global__ void Kernels::convolution(
     const float* d_input,
     const float* d_kernel,
     float*       d_output,