Editing Central processing unit (section)

====Data parallelism====
{{Main|Vector processor|SIMD}}
A less common but increasingly important paradigm of processors (and indeed, computing in general) deals with data parallelism. The processors discussed earlier are all referred to as some type of scalar device.{{Efn|Earlier the term ''scalar'' was used to compare the IPC count afforded by various ILP methods. Here the term is used in the strictly mathematical sense to contrast with vectors. See [[scalar (mathematics)]] and [[vector (geometric)]].}} As the name implies, vector processors deal with multiple pieces of data in the context of one instruction. This contrasts with scalar processors, which deal with one piece of data for every instruction. Using [[Flynn's taxonomy]], these two schemes of dealing with data are generally referred to as ''single instruction'' stream, ''multiple data'' stream ([[Single instruction, multiple data|SIMD]]) and ''single instruction'' stream, ''single data'' stream ([[Single instruction, single data|SISD]]), respectively. The great utility in creating processors that deal with vectors of data lies in optimizing tasks that tend to require the same operation (for example, a sum or a [[dot product]]) to be performed on a large set of data. Some classic examples of these types of tasks include [[multimedia]] applications (images, video and sound), as well as many types of [[Scientific computing|scientific]] and engineering tasks. Whereas a scalar processor must complete the entire process of fetching, decoding and executing each instruction and value in a set of data, a vector processor can perform a single operation on a comparatively large set of data with one instruction. This is only possible when the application tends to require many steps which apply one operation to a large set of data.

Most early vector processors, such as the [[Cray-1]], were associated almost exclusively with scientific research and [[cryptography]] applications. However, as multimedia has largely shifted to digital media, the need for some form of SIMD in general-purpose processors has become significant. Shortly after inclusion of [[floating-point unit]]s started to become commonplace in general-purpose processors, specifications for and implementations of SIMD execution units also began to appear for general-purpose processors in the mid-1990s. Some of these early SIMD specifications – like HP's [[Multimedia Acceleration eXtensions]] (MAX) and Intel's [[MMX (instruction set)|MMX]] – were integer-only. This proved to be a significant impediment for some software developers, since many of the applications that benefit from SIMD primarily deal with [[floating-point arithmetic|floating-point]] numbers. Progressively, developers refined and remade these early designs into some of the common modern SIMD specifications, which are usually associated with one [[instruction set architecture]] (ISA). Some notable modern examples include Intel's [[Streaming SIMD Extensions]] (SSE) and the PowerPC-related [[AltiVec]] (also known as VMX).{{Efn|Although SSE/SSE2/SSE3 have superseded MMX in Intel's general-purpose processors, later [[IA-32]] designs still support MMX. This is usually done by providing most of the MMX functionality with the same hardware that supports the much more expansive SSE instruction sets.}}