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Algorithmic Skeleton
In computing, algorithmic skeletons, or parallelism patterns, are a high-level parallel programming model for parallel and distributed computing. Algorithmic skeletons take advantage of common programming patterns to hide the complexity of parallel and distributed applications. Starting from a basic set of patterns (skeletons), more complex patterns can be built by combining the basic ones. Overview The most outstanding feature of algorithmic skeletons, which differentiates them from other high-level parallel programming models, is that orchestration and synchronization of the parallel activities is implicitly defined by the skeleton patterns. Programmers do not have to specify the synchronizations between the application's sequential parts. This yields two implications. First, as the communication/data access patterns are known in advance, cost models can be applied to schedule skeletons programs. Second, that algorithmic skeleton programming reduces the number of errors when com ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computing
Computing is any goal-oriented activity requiring, benefiting from, or creating computing machinery. It includes the study and experimentation of algorithmic processes, and development of both hardware and software. Computing has scientific, engineering, mathematical, technological and social aspects. Major computing disciplines include computer engineering, computer science, cybersecurity, data science, information systems, information technology and software engineering. The term "computing" is also synonymous with counting and calculating. In earlier times, it was used in reference to the action performed by mechanical computing machines, and before that, to human computers. History The history of computing is longer than the history of computing hardware and includes the history of methods intended for pen and paper (or for chalk and slate) with or without the aid of tables. Computing is intimately tied to the representation of numbers, though mathematical conc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Evolutionary Algorithm
In computational intelligence (CI), an evolutionary algorithm (EA) is a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm. An EA uses mechanisms inspired by biological evolution, such as reproduction, mutation, recombination, and selection. Candidate solutions to the optimization problem play the role of individuals in a population, and the fitness function determines the quality of the solutions (see also loss function). Evolution of the population then takes place after the repeated application of the above operators. Evolutionary algorithms often perform well approximating solutions to all types of problems because they ideally do not make any assumption about the underlying fitness landscape. Techniques from evolutionary algorithms applied to the modeling of biological evolution are generally limited to explorations of microevolutionary processes and planning models based upon cellular processes. In most real applications of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Concurrent Programming Languages
Concurrent computing is a form of computing in which several computations are executed '' concurrently''—during overlapping time periods—instead of ''sequentially—''with one completing before the next starts. This is a property of a system—whether a program, computer, or a network—where there is a separate execution point or "thread of control" for each process. A ''concurrent system'' is one where a computation can advance without waiting for all other computations to complete. Concurrent computing is a form of modular programming. In its paradigm an overall computation is factored into subcomputations that may be executed concurrently. Pioneers in the field of concurrent computing include Edsger Dijkstra, Per Brinch Hansen, and C.A.R. Hoare. Introduction The concept of concurrent computing is frequently confused with the related but distinct concept of parallel computing, Pike, Rob (2012-01-11). "Concurrency is not Parallelism". ''Waza conference'', 11 January ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Parallel Programming Model
In computing, a parallel programming model is an abstraction of parallel computer architecture, with which it is convenient to express algorithms and their composition in programs. The value of a programming model can be judged on its ''generality'': how well a range of different problems can be expressed for a variety of different architectures, and its ''performance'': how efficiently the compiled programs can execute. The implementation of a parallel programming model can take the form of a library invoked from a sequential language, as an extension to an existing language, or as an entirely new language. Consensus around a particular programming model is important because it leads to different parallel computers being built with support for the model, thereby facilitating portability of software. In this sense, programming models are referred to as '' bridging'' between hardware and software.Leslie G. Valiant, "A bridging model for parallel computation", Communications of the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cuneiform (programming Language)
Cuneiform is an open-source workflow language for large-scale scientific data analysis. It is a statically typed functional programming language promoting parallel computing. It features a versatile foreign function interface allowing users to integrate software from many external programming languages. At the organizational level Cuneiform provides facilities like conditional branching and general recursion making it Turing-complete. In this, Cuneiform is the attempt to close the gap between scientific workflow systems like Taverna, KNIME, or Galaxy and large-scale data analysis programming models like MapReduce or Pig Latin while offering the generality of a functional programming language. Cuneiform is implemented in distributed Erlang. If run in distributed mode it drives a POSIX-compliant distributed file system like Gluster or Ceph (or a FUSE integration of some other file system, e.g., HDFS). Alternatively, Cuneiform scripts can be executed on top of HTCondor or Hadoop ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Halide (programming Language)
Halide is a computer programming language designed for writing digital image processing code that takes advantage of memory locality, vectorized computation and multi-core CPUs and GPUs. Halide is implemented as an internal domain-specific language (DSL) in C++. Language The main innovation Halide brings is the separation of the algorithm being implemented from its execution schedule, i.e. code specifying the loop nesting, parallelization, loop unrolling and vector instruction. These two are usually interleaved together and experimenting with changing the schedule requires the programmer to rewrite large portions of the algorithm with every change. With Halide, changing the schedule does not require any changes to the algorithm and this allows the programmer to experiment with scheduling and finding the most efficient one. Sample source code The following function defines and sets the schedule for a 3×3 box filter defined as a series of two 3×1 passes: Func blur_3x3( ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
OpenMP
OpenMP (Open Multi-Processing) is an application programming interface (API) that supports multi-platform shared-memory multiprocessing programming in C, C++, and Fortran, on many platforms, instruction-set architectures and operating systems, including Solaris, AIX, FreeBSD, HP-UX, Linux, macOS, and Windows. It consists of a set of compiler directives, library routines, and environment variables that influence run-time behavior. OpenMP is managed by the nonprofit technology consortium ''OpenMP Architecture Review Board'' (or ''OpenMP ARB''), jointly defined by a broad swath of leading computer hardware and software vendors, including Arm, AMD, IBM, Intel, Cray, HP, Fujitsu, Nvidia, NEC, Red Hat, Texas Instruments, and Oracle Corporation. OpenMP uses a portable, scalable model that gives programmers a simple and flexible interface for developing parallel applications for platforms ranging from the standard desktop computer to the supercomputer. An application built wi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Algorithmic Skeleton
In computing, algorithmic skeletons, or parallelism patterns, are a high-level parallel programming model for parallel and distributed computing. Algorithmic skeletons take advantage of common programming patterns to hide the complexity of parallel and distributed applications. Starting from a basic set of patterns (skeletons), more complex patterns can be built by combining the basic ones. Overview The most outstanding feature of algorithmic skeletons, which differentiates them from other high-level parallel programming models, is that orchestration and synchronization of the parallel activities is implicitly defined by the skeleton patterns. Programmers do not have to specify the synchronizations between the application's sequential parts. This yields two implications. First, as the communication/data access patterns are known in advance, cost models can be applied to schedule skeletons programs. Second, that algorithmic skeleton programming reduces the number of errors when com ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
PCIe
PCI Express (Peripheral Component Interconnect Express), officially abbreviated as PCIe or PCI-e, is a high-speed serial computer expansion bus standard, designed to replace the older PCI, PCI-X and AGP bus standards. It is the common motherboard interface for personal computers' graphics cards, hard disk drive host adapters, SSDs, Wi-Fi and Ethernet hardware connections. PCIe has numerous improvements over the older standards, including higher maximum system bus throughput, lower I/O pin count and smaller physical footprint, better performance scaling for bus devices, a more detailed error detection and reporting mechanism (Advanced Error Reporting, AER), and native hot-swap functionality. More recent revisions of the PCIe standard provide hardware support for I/O virtualization. The PCI Express electrical interface is measured by the number of simultaneous lanes. (A lane is a single send/receive line of data. The analogy is a highway with traffic in both directions.) T ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
OpenCL
OpenCL (Open Computing Language) is a framework for writing programs that execute across heterogeneous platforms consisting of central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), field-programmable gate arrays (FPGAs) and other processors or hardware accelerators. OpenCL specifies programming languages (based on C99, C++14 and C++17) for programming these devices and application programming interfaces (APIs) to control the platform and execute programs on the compute devices. OpenCL provides a standard interface for parallel computing using task- and data-based parallelism. OpenCL is an open standard maintained by the non-profit technology consortium Khronos Group. Conformant implementations are available from Altera, AMD, ARM, Creative, IBM, Imagination, Intel, Nvidia, Qualcomm, Samsung, Vivante, Xilinx, and ZiiLABS. Overview OpenCL views a computing system as consisting of a number of ''compute devices'', which migh ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Genetic Algorithm
In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on biologically inspired operators such as mutation, crossover and selection. Some examples of GA applications include optimizing decision trees for better performance, solving sudoku puzzles, hyperparameter optimization, etc. Methodology Optimization problems In a genetic algorithm, a population of candidate solutions (called individuals, creatures, organisms, or phenotypes) to an optimization problem is evolved toward better solutions. Each candidate solution has a set of properties (its chromosomes or genotype) which can be mutated and altered; traditionally, solutions are represented in binary as strings of 0s and 1s, but other encodings are also possible. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
