Start implementing padding kernel

src/kernels/padding.cu

@@ -0,0 +1,57 @@
+/*
+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 column major 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 2 4 1 3 5 6 8 10 7 9 11
+
+Padded result:
+
+0 0 0 0 0 0 0 2 4 0 0 1 3 5 0 0 0 0 0 0 0 0 0 0 0 0 6 8 10 0 0 7 9 11 0 0 0 0 0 0
+
+
+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 pad_matrix_kernel(
+    const float* d_input,
+    float*       d_padded,
+    int          w,
+    int          h,
+    int          n,
+    int          p
+) {
+    int stride = gridDim.x * blockDim.x;
+    int tid    = blockDim.x * blockIdx.x + threadIdx.x;
+
+	for (int i = tid; i < (w + 2 * p) * (h + 2 * p) * n; i += stride) {
+		
+		// if i is in the padding region
+		if (i < p * (h + 2 * p) * n || i >= (w + p) * (h + 2 * p) * n) {
+			d_padded[i] = 0.0f;
+		} else {
+			// if i is in the original region
+			d_padded[i] = d_input[(i - p * (h + 2 * p) * n) / (h + 2 * p) * w + (i - p * (h + 2 * p) * n) % (h + 2 * p)];
+		}
+	}
+}