namesny-com/content/blog/cuda_net.md

title	draft
Writing a Convolutional Neural Network library with CUDA Support	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
• naive conv2d
• learning 3D memory representation
• optimizing conv2d
• softmax sum reduce