GPU Sorting: The Benefits The graphics processing unit or GPU has become an important part of the design of most modern computers. A GPU is a specialized form of processor implemented in a computer to lighten the workload of the central processing unit, or CPU. A GPU is also incorporated because, due to its design, it can perform certain graphics operations more efficiently than the more general-purpose CPU. According to Denny Atkin, “Over 90% of new desktop and notebook computers have integrated GPUs.” There are generally two forms of GPUs, integrated and non-integrated. Integrated GPUs are located directly on a computer's motherboard. Integrated GPUs are often cheaper than their non-integrated counterparts, but that advantage is offset by performance. Integrated GPUs are often less powerful than non-integrated GPUs which are usually in the form of a graphics card. A recent example of a graphics card is the ATI Radeon HD 5970. A graphics card is mainly made up of two parts, memory and GPU. Memory is usually 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 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, classification of computer architectures. In general, the most common CPUs can be classified as single instruction, single data stream, or SISD. Commonly SIMD is faster but less diverse, SISD is probably slower but more diverse. Therefore it is often worth running certain tasks on a GPU rather than a CPU, rather based on graphics or ...... middle of paper ...... position sorting), and then running said algorithm in parallel, very good performance improvements can be achieved. Therefore a graphics processing unit is not only a valid platform for sorting algorithms, but can excel at sorting. A valid argument can be made that there are many non-parallel algorithms that outperform Bubble Sort in terms of computation time. While Heap Sort, Quick Sort, Radix Sort and other advanced sorting algorithms can actually, like GPU-based odd-even transpose sorting, destroy Bubble Sort sorting times. This begs the question: How does GPU-based OETS perform compared to these advanced types? The purpose of this article, however, is not to demonstrate a superior sorting technique, rather, its purpose is to suggest that sorting algorithms can be run on the GPU optimally. success. This suggests that GPUs have many applications beyond simple graphics operations.