In computing, a compiler is a computer program that translates computer code written in one programming language into another language. The name "compiler" is primarily used for programs that translate source code from a high-level programming language to a lower level language to create an executable program.
In 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 requirement, and power consumption.
In computing, inline expansion, or inlining, is a manual or compiler optimization that replaces a function call site with the body of the called function. Inline expansion is similar to macro expansion, but occurs during compilation, without changing the source code, while macro expansion occurs prior to compilation, and results in different text that is then processed by the compiler.
In computer science, program optimization or software optimization is the process of modifying a software system to make some aspect of it work more efficiently or use fewer resources. In general, a computer program may be optimized so that it executes more rapidly, or to make it capable of operating with less memory storage or other resources, or draw less power.
In compiler theory, common subexpression elimination (CSE) is a compiler optimization that searches for instances of identical expressions, and analyzes whether it is worthwhile replacing them with a single variable holding the computed value.
In computer science, a loop invariant is a property of a program loop that is true before each iteration. It is a logical assertion, sometimes checked within the code by an assertion call. Knowing its invariant(s) is essential in understanding the effect of a loop.
In computer programming, loop-invariant code consists of statements or expressions which can be moved outside the body of a loop without affecting the semantics of the program. Loop-invariant code motion is a compiler optimization which performs this movement automatically.
Loop unrolling, also known as loop unwinding, is a loop transformation technique that attempts to optimize a program's execution speed at the expense of its binary size, which is an approach known as space–time tradeoff. The transformation can be undertaken manually by the programmer or by an optimizing compiler.
In mathematics, an invariant is a property of a mathematical object which remains unchanged, after operations or transformations of a certain type are applied to the objects. The particular class of objects and type of transformations are usually indicated by the context in which the term is used. For example, the area of a triangle is an invariant with respect to isometries of the Euclidean plane. The phrases "invariant under" and "invariant to" a transformation are both used. More generally, an invariant with respect to an equivalence relation is a property that is constant on each equivalence class.
In compiler theory, loop optimization is the process of increasing execution speed and reducing the overheads associated with loops. It plays an important role in improving cache performance and making effective use of parallel processing capabilities. Most execution time of a scientific program is spent on loops; as such, many compiler optimization techniques have been developed to make them faster.
In compiler theory, loop interchange is the process of exchanging the order of two iteration variables used by a nested loop. The variable used in the inner loop switches to the outer loop, and vice versa. It is often done to ensure that the elements of a multi-dimensional array are accessed in the order in which they are present in memory, improving locality of reference.
In computer science, loop inversion is a compiler optimization and loop transformation in which a while loop is replaced by an if block containing a do..while loop. When used correctly, it may improve performance due to instruction pipelining.
In compiler theory, partial redundancy elimination (PRE) is a compiler optimization that eliminates expressions that are redundant on some but not necessarily all paths through a program. PRE is a form of common subexpression elimination.
Automatic 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 :
In computer science, an induction variable is a variable that gets increased or decreased by a fixed amount on every iteration of a loop or is a linear function of another induction variable.
The polyhedral model is a mathematical framework for programs that perform large numbers of operations -- too large to be explicitly enumerated -- thereby requiring a compact representation. Nested loop programs are the typical, but not the only example, and the most common use of the model is for loop nest optimization in program optimization. The polyhedral method treats each loop iteration within nested loops as lattice points inside mathematical objects called polyhedra, performs affine transformations or more general non-affine transformations such as tiling on the polytopes, and then converts the transformed polytopes into equivalent, but optimized, loop nests through polyhedra scanning.
vbcc is a portable and retargetable ANSI C compiler. It supports C89 as well as parts of C99.
Use of the polyhedral model within a compiler requires software to represent the objects of this framework and perform operations upon them.
For several years parallel hardware was only available for distributed computing but recently it is becoming available for the low end computers as well. Hence it has become inevitable for software programmers to start writing parallel applications. It is quite natural for programmers to think sequentially and hence they are less acquainted with writing multi-threaded or parallel processing applications. Parallel programming requires handling various issues such as synchronization and deadlock avoidance. Programmers require added expertise for writing such applications apart from their expertise in the application domain. Hence programmers prefer to write sequential code and most of the popular programming languages support it. This allows them to concentrate more on the application. Therefore, there is a need to convert such sequential applications to parallel applications with the help of automated tools. The need is also non-trivial because large amount of legacy code written over the past few decades needs to be reused and parallelized.
Tracing just-in-time compilation is a technique used by virtual machines to optimize the execution of a program at runtime. This is done by recording a linear sequence of frequently executed operations, compiling them to native machine code and executing them. This is opposed to traditional just-in-time (JIT) compilers that work on a per-method basis.
