Influence of optimization techniques on software performance for subsequent generations of CUDA architecture

From the very beginning of the CUDA technology, it was essential to apply state-of-the-art optimization techniques. Only then was it possible to fully utilize the enormous computational power of graphic processing units. However, with the development of the CUDA architecture, the impact of typical optimization techniques on software performance has changed significantly. This article shows how the impact of several optimization techniques on the performance of the image filtering algorithm has changed for the subsequent generations of CUDA architecture. Then, based on the results obtained, it attempts to answer whether tedious and time-consuming optimization of the CUDA software is still necessary.