diff --git a/content/blog/cuda_net.md b/content/blog/cuda_net.md new file mode 100644 index 0000000..1b70993 --- /dev/null +++ b/content/blog/cuda_net.md @@ -0,0 +1,17 @@ +--- +title: Writing a Convolutional Neural Network library with CUDA Support +draft: true +--- + +"Just use cuBLAS, it'll be easier. You don't have to implement custom CUDA kernels.", they said. Actually, noone said that. I just thought that because I didn't do enough research. + +Why not combine multiple challenging things into 1 (C++, cmake, CUDA, CNN) + +Quickly discovering that without writing custom kernels, you can't really progress + +- cuBLAS column major layout, macro +- cmake woes (findCUDA) +- google test +- padding kernel +- column major / row major headache +- removing cuBLAS -> just row major representation