AI summary

This paper discusses the evolution of GPUs from fixed-function 3D graphics pipelines to flexible, general-purpose computational engines, highlighting their architecture, parallel processing capabilities, and the shift towards programmable shaders, achieving tremendous speedups over CPUs and enabling general-purpose computation on GPUs (GPGPU).

Abstract

In the early 1990s, ubiquitous interactive 3D graphics was still the stuff of science fiction. By the end of the decade, nearly every new computer contained a graphics processing unit (GPU) dedicated to providing a high-performance, visually rich, interactive 3D experience. This dramatic shift was the inevitable consequence of consumer demand for videogames, advances in manufacturing technology, and the exploitation of the inherent parallelism in the feed-forward graphics pipeline. Today, the raw computational power of a GPU dwarfs that of the most powerful CPU, and the gap is steadily widening. Furthermore, GPUs have moved away from the traditional fixed-function 3D graphics pipeline toward a flexible general-purpose computational engine. Today, GPUs can implement many parallel algorithms directly using graphics hardware. Well-suited algorithms that leverage all the underlying computational horsepower often achieve tremendous speedups. Truly, the GPU is the first widely deployed commodity desktop parallel computer.