Vulkan CNN upscaling optimizations cut runtime from 393ms to 68ms

The author details initial optimizations for a Vulkan compute neural upscaling convolutional neural network, successfully reducing processing time from 393ms to 68ms. Key techniques include vectorizing operations with packed 4-element vectors, reducing data precision to 16-bit floating point numbers to minimize memory traffic, and utilizing workgroup shared memory to eliminate duplicate memory loads. Open article →