Parallel Processing with GPUs: Techniques and Advances for Enhanced Deep Learning Performance

Abstract

The rapid evolution of deep learning has necessitated advancements in computing power to handle complex algorithms and large datasets. Graphics Processing Units (GPUs) have emerged as the cornerstone of this computational power, offering unparalleled parallel processing capabilities that significantly enhance the efficiency and speed of deep learning tasks. This paper delves into the latest advances in GPU computing, exploring how parallel processing is being leveraged to drive innovation in deep learning. We discuss the architecture of modern GPUs, their role in training and inference, and the future directions of GPU computing in the context of deep learning.