Sort GPU - The BenefitsThe graphics processing unit or GPU has become an important part of most modern computer design. A GPU is a specialized form of processor implemented in a computer to reduce the workload on the central processing unit or CPU. A GPU is also integrated because, by design, it can perform certain graphics operations with greater efficiency than the more general-purpose CPU. According to Denny Atkin, “More than 90% of new desktop and laptop computers have integrated GPUs.” There are generally two forms of GPUs, integrated and non-integrated. Integrated GPUs sit directly on a computer's motherboard. Integrated GPUs are often less expensive than their non-integrated counterparts, but this advantage is offset by performance. Integrated GPUs are often less powerful than non-integrated GPUs which usually come in the form of a graphics card. A recent example of a graphics card is the ATI Radeon HD 5970. A graphics card mainly consists of two parts, the memory and the GPU. Memory is typically used to store information about each pixel (of a computer screen) until it is ready to be displayed. The GPU is similar to a CPU, but it is specifically designed to perform complex geometric and mathematical calculations associated with graphics rendering. GPUs can be classified, using Flynn's taxonomy, under the Single Instruction, Multiple Data Streams, or SIMD, computer classification. architectures. Generally, the most common processors can be categorized as single instruction, single data stream, or SISD. Generally, SIMD is faster but less diverse, SISD is probably slower but more diverse. So it is often interesting to execute certain tasks on a GPU rather than on a CPU, rather based on graphics or... middle of paper ......oposition Sort), then to execute said algorithm in parallel, Nice performance improvements can be achieved. Therefore, a graphics processing unit is not only a valid platform for sorting algorithms, it can excel at sorting. A valid argument can be made that there are many non-parallel algorithms that trump bubble sort in terms of computational time. While heap sort, quick sort, Radix sort, and other advanced sorting algorithms can indeed, like GPU-based odd-even transpose sort, destroy the sort times of bubble sort. This begs the question: how does GPU-based OETS compete against these advanced types? The goal of this article, however, is not to demonstrate a superior sorting technique, but rather to suggest that sorting algorithms can be run on the GPU optimally. success. This suggests that GPUs have many applications beyond simple graphics operations..