Running a neural network on GPU using OpenCL (finally, it took a while)

A developer implements neural network training on GPU using OpenCL and Zig, building a custom framework from scratch. The project involves creating matrix multiplication kernels, sigmoid activation functions, and fully connected layers for GPU computation. The implementation focuses on batch processing for efficiency and includes detailed explanations of OpenCL kernel development, memory management, and the challenges of GPU programming for machine learning workloads.