CUDAnet post draft

content/blog/cuda_net.md

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+---
+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