Inline assemblerIn computer programming, an inline assembler is a feature of some compilers that allows low-level code written in assembly language to be embedded within a program, among code that otherwise has been compiled from a higher-level language such as C or Ada. The embedding of assembly language code is usually done for one of these reasons: Optimization: Programmers can use assembly language code to implement the most performance-sensitive parts of their program's algorithms, code that is apt to be more efficient than what might otherwise be generated by the compiler.
Automatic vectorizationAutomatic vectorization, in parallel computing, is a special case of automatic parallelization, where a computer program is converted from a scalar implementation, which processes a single pair of operands at a time, to a vector implementation, which processes one operation on multiple pairs of operands at once. For example, modern conventional computers, including specialized supercomputers, typically have vector operations that simultaneously perform operations such as the following four additions (via SIMD or SPMD hardware): However, in most programming languages one typically writes loops that sequentially perform additions of many numbers.
Function (computer programming)In computer programming, a function or subroutine is a sequence of program instructions that performs a specific task, packaged as a unit. This unit can then be used in programs wherever that particular task should be performed. Functions may be defined within programs, or separately in libraries that can be used by many programs. In different programming languages, a function may be called a routine, subprogram, subroutine, or procedure; in object-oriented programming (OOP), it may be called a method.
Automatic parallelizationAutomatic parallelization, also auto parallelization, or autoparallelization refers to converting sequential code into multi-threaded and/or vectorized code in order to use multiple processors simultaneously in a shared-memory multiprocessor (SMP) machine. Fully automatic parallelization of sequential programs is a challenge because it requires complex program analysis and the best approach may depend upon parameter values that are not known at compilation time.
AltiVecAltiVec is a single-precision floating point and integer SIMD instruction set designed and owned by Apple, IBM, and Freescale Semiconductor (formerly Motorola's Semiconductor Products Sector) — the AIM alliance. It is implemented on versions of the PowerPC processor architecture, including Motorola's G4, IBM's G5 and POWER6 processors, and P.A. Semi's PWRficient PA6T. AltiVec is a trademark owned solely by Freescale, so the system is also referred to as Velocity Engine by Apple and VMX (Vector Multimedia Extension) by IBM and P.
Low-level programming languageA low-level programming language is a programming language that provides little or no abstraction from a computer's instruction set architecture—commands or functions in the language map that are structurally similar to processor's instructions. Generally, this refers to either machine code or assembly language. Because of the low (hence the word) abstraction between the language and machine language, low-level languages are sometimes described as being "close to the hardware".
Optimizing compilerIn computing, an optimizing compiler is a compiler that tries to minimize or maximize some attributes of an executable computer program. Common requirements are to minimize a program's execution time, memory footprint, storage size, and power consumption (the last three being popular for portable computers). Compiler optimization is generally implemented using a sequence of optimizing transformations, algorithms which take a program and transform it to produce a semantically equivalent output program that uses fewer resources or executes faster.
Bitwise operationIn computer programming, a bitwise operation operates on a bit string, a bit array or a binary numeral (considered as a bit string) at the level of its individual bits. It is a fast and simple action, basic to the higher-level arithmetic operations and directly supported by the processor. Most bitwise operations are presented as two-operand instructions where the result replaces one of the input operands. On simple low-cost processors, typically, bitwise operations are substantially faster than division, several times faster than multiplication, and sometimes significantly faster than addition.
Single instruction, multiple dataSingle instruction, multiple data (SIMD) is a type of parallel processing in Flynn's taxonomy. SIMD can be internal (part of the hardware design) and it can be directly accessible through an instruction set architecture (ISA), but it should not be confused with an ISA. SIMD describes computers with multiple processing elements that perform the same operation on multiple data points simultaneously. Such machines exploit data level parallelism, but not concurrency: there are simultaneous (parallel) computations, but each unit performs the exact same instruction at any given moment (just with different data).
EndiannessIn computing, endianness is the order or sequence of bytes of a word of digital data in computer memory or data communication which is identified by describing the impact of the "first" bytes, meaning at the smallest address or sent first. Endianness is primarily expressed as big-endian (BE) or little-endian (LE). A big-endian system stores the most significant byte of a word at the smallest memory address and the least significant byte at the largest. A little-endian system, in contrast, stores the least-significant byte at the smallest address.
