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Memory model (programming)

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In computing, a memory model describes the interactions of threads through memory and their shared use of the data. History and significanceA memory model allows a compiler to perform many important optimizations. Compiler optimizations like loop fusion move statements in the program, which can influence the order of read and write operations of potentially shared variables. Changes in the ordering of reads and writes can cause race conditions.

Race conditionRace conditionA race condition or race hazard is the condition of an electronics, software, or other system where the system's substantive behavior is dependent on the sequence or timing of uncontrollable events, leading to unexpected or inconsistent results. It becomes a bug when one or more of the possible behaviors is undesirable. The term race condition was in use by 1954, for example in David A. Huffman's doctoral thesis "The synthesis of sequential switching circuits".C (programming language)C (programming language)C is a general-purpose programming language created in 1972 by Dennis Ritchie. By design, C gives programmers relatively direct access to the features of typical CPU architectures, customized for the target instruction set. It has been and continues to be used to implement operating systems (especially kernels), device drivers, and protocol stacks, though its use in application software is decreasing.Java memory modelThe Java memory model describes how threads in the Java programming language interact through memory. Together with the description of single-threaded execution of code, the memory model provides the semantics of the Java programming language. The original Java memory model developed in 1995 was widely perceived as broken preventing many runtime optimizations and not providing strong enough guarantees for code safety.Program optimizationProgram optimizationImproving the efficiency of software In computer science, program optimization, code 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.Java (programming language)Java (programming language)Object-oriented programming languageJava is a high-level, general-purpose, memory-safe, object-orientedprogramming language. It is intended to let programmerswrite once, run anywhere (WORA), meaning that compiled Java code can run on all platforms that support Java without the need to recompile. Java applications are usually compiled to bytecode that can run on any Java virtual machine (JVM) regardless of the underlying computer architecture.C++C++General-purpose programming languageC++ is a high-level, general-purpose programming language created by Danish computer scientist Bjarne Stroustrup. First released in 1985 as an extension of the C programming language, adding object-oriented (OOP) functionality and later expanding significantly with the addition of functional programming features.Library (computing)Library (computing)In computing, a library is a collection of resources that can be used during software development to implement a computer program. Commonly, a library consists of executable code such as compiled functions and classes, or a library can be a collection of source code. A resource library may contain data such as images and text. A library can be used by multiple, independent consumers (programs and other libraries).Variable (high-level programming language)In some high-level programming languages, a variable is an abstract storage or indirection location paired with an associated symbolic name, which contains some known or unknown quantity of data or object referred to as a value; or in simpler terms, a variable is a named container for a particular set of bits or type of data (like integer, float, string, etc...) or undefined.Optimizing compilerOptimizing compilerAn optimizing compiler is a compiler designed to generate code that is optimized in aspects such as minimizing program execution time, memory usage, storage size, and power consumption. Optimization is generally implemented as a sequence of optimizing transformations, a.k.a. compiler optimizations – algorithms that transform code to produce semantically equivalent code optimized for some aspect. Optimization is limited by a number of factors.Thread (computing)Thread (computing)In computer science, a thread of execution is the smallest sequence of programmed instructions that can be managed independently by a scheduler, which is typically a part of the operating system. In many cases, a thread is a component of a process. The multiple threads of a given process may be executed concurrently (via multithreading capabilities), sharing resources such as memory, while different processes do not share these resources.Barrier (computer science)In parallel computing, a barrier is a synchronization method. A barrier for a group of threads or processes in the source code means that all thread/process stop at that point and do not proceed until all other threads/processes reach this barrier. Many collective routines and directive-based parallel languages impose implicit barriers. For example, a parallel do loop in Fortran with OpenMP will not be allowed to continue on any thread until the last iteration is completed.Computer memoryComputer memoryComputer memory stores information, such as data and programs, for immediate use in the computer; instructions fetched by the computer, and data fetched and stored by those instructions, are located in computer memory. The terms memory, main memory, and primary storage are also used for computer memory. Computer memory is often referred to as RAM, meaning random-access memory, although some older forms of computer memory, such as drum memory, are not random-access.Loop fission and fusionLoop fission (or loop distribution) is a compiler optimization in which a loop is broken into multiple loops over the same index range with each taking only a part of the original loop's body. The goal is to break down a large loop body into smaller ones to achieve better utilization of locality of reference. This optimization is most efficient in multi-core processors that can split a task into multiple tasks for each processor.

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