Facts, Issues and Questions - GPUs for Dependability

Abstract

Graphics Processing Units (GPUs) offer massive parallelism, comprising many actual paradigms like manycore, multithreading and SIMD. Today, nearly every computer is equipped with at least one graphics card, containing one or more GPUs bringing massive parallelism to the desktop. GPUs are usually used in their main function, that is, to compute visibility, lightning, perspective, etc. in games. As this technology is widely used, it is lowcost. In the majority of the cases, graphic cards do not spend their entire lives by executing game code. Thus, such a massive parallel system is underchallenged most of the time. Shortly after the availability of comfortable programming environments, based on CUDA (Compute Unified Device Architecture) or HLSL (high-level shader language), researchers have become interested in using this power for general-purpose computing (GPGPU, General-Purpose computing on the GPU). Thus, different applications originated, e.g. physics, cryptography 0, DNA sequencing 0 and medical imaging. For further examples and overview, see 0 and 0.