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Thread Level Parallelism
Task parallelism (also known as function parallelism and control parallelism) is a form of parallelization of computer code across multiple processors in parallel computing environments. Task parallelism focuses on distributing tasks—concurrently performed by processes or threads—across different processors. In contrast to data parallelism which involves running the same task on different components of data, task parallelism is distinguished by running many different tasks at the same time on the same data. A common type of task parallelism is pipelining, which consists of moving a single set of data through a series of separate tasks where each task can execute independently of the others. Description In a multiprocessor system, task parallelism is achieved when each processor executes a different thread (or process) on the same or different data. The threads may execute the same or different code. In the general case, different execution threads communicate with one an ...
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Parallelization
Parallel computing is a type of computation in which many calculations or processes are carried out simultaneously. Large problems can often be divided into smaller ones, which can then be solved at the same time. There are several different forms of parallel computing: bit-level, instruction-level, data, and task parallelism. Parallelism has long been employed in high-performance computing, but has gained broader interest due to the physical constraints preventing frequency scaling.S.V. Adve ''et al.'' (November 2008)"Parallel Computing Research at Illinois: The UPCRC Agenda" (PDF). Parallel@Illinois, University of Illinois at Urbana-Champaign. "The main techniques for these performance benefits—increased clock frequency and smarter but increasingly complex architectures—are now hitting the so-called power wall. The computer industry has accepted that future performance increases must largely come from increasing the number of processors (or cores) on a die, rather than m ...
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Pseudocode
In computer science, pseudocode is a plain language description of the steps in an algorithm or another system. Pseudocode often uses structural conventions of a normal programming language, but is intended for human reading rather than machine reading. It typically omits details that are essential for machine understanding of the algorithm, such as variable declarations and language-specific code. The programming language is augmented with natural language description details, where convenient, or with compact mathematical notation. The purpose of using pseudocode is that it is easier for people to understand than conventional programming language code, and that it is an efficient and environment-independent description of the key principles of an algorithm. It is commonly used in textbooks and scientific publications to document algorithms and in planning of software and other algorithms. No broad standard for pseudocode syntax exists, as a program in pseudocode is not an executa ...
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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 ...
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VHDL
The VHSIC Hardware Description Language (VHDL) is a hardware description language (HDL) that can model the behavior and structure of digital systems at multiple levels of abstraction, ranging from the system level down to that of logic gates, for design entry, documentation, and verification purposes. Since 1987, VHDL has been standardized by the Institute of Electrical and Electronics Engineers (IEEE) as IEEE Std 1076; the latest version of which is IEEE Std 1076-2019. To model analog and mixed-signal systems, an IEEE-standardized HDL based on VHDL called VHDL-AMS (officially IEEE 1076.1) has been developed. VHDL is named after the United States Department of Defense program that created it, the Very High-Speed Integrated Circuits Program (VHSIC). In the early 1980s, the VHSIC Program sought a new HDL for use in the design of the integrated circuits it aimed to develop. The product of this effort was VHDL Version 7.2, released in 1985. The effo ...
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Verilog
Verilog, standardized as IEEE 1364, is a hardware description language (HDL) used to model electronic systems. It is most commonly used in the design and verification of digital circuits at the register-transfer level of abstraction. It is also used in the verification of analog circuits and mixed-signal circuits, as well as in the design of genetic circuits. In 2009, the Verilog standard (IEEE 1364-2005) was merged into the SystemVerilog standard, creating IEEE Standard 1800-2009. Since then, Verilog is officially part of the SystemVerilog language. The current version is IEEE standard 1800-2017. Overview Hardware description languages such as Verilog are similar to software programming languages because they include ways of describing the propagation time and signal strengths (sensitivity). There are two types of assignment operators; a blocking assignment (=), and a non-blocking (>>. A generate–endgenerate construct (similar to VHDL's generate–endgenerate) allows Verilog ...
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Hardware Description Language
In computer engineering, a hardware description language (HDL) is a specialized computer language used to describe the structure and behavior of electronic circuits, and most commonly, digital logic circuits. A hardware description language enables a precise, formal description of an electronic circuit that allows for the automated analysis and simulation of an electronic circuit. It also allows for the synthesis of an HDL description into a netlist (a specification of physical electronic components and how they are connected together), which can then be placed and routed to produce the set of masks used to create an integrated circuit. A hardware description language looks much like a programming language such as C or ALGOL; it is a textual description consisting of expressions, statements and control structures. One important difference between most programming languages and HDLs is that HDLs explicitly include the notion of time. HDLs form an integral part of electr ...
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Task Parallel Library
Parallel Extensions was the development name for a managed concurrency library developed by a collaboration between Microsoft Research and the CLR team at Microsoft. The library was released in version 4.0 of the .NET Framework. It is composed of two parts: ''Parallel LINQ'' (PLINQ) and ''Task Parallel Library'' (TPL). It also consists of a set of ''coordination data structures'' (CDS) – sets of data structures used to synchronize and co-ordinate the execution of concurrent tasks. Parallel LINQ PLINQ, or Parallel LINQ, parallelizing the execution of queries on objects (LINQ to Objects) and XML data (LINQ to XML). PLINQ is intended for exposing data parallelism by use of queries. Any computation on objects that has been implemented as queries can be parallelized by PLINQ. However, the objects need to implement the IParallelEnumerable interface, which is defined by PLINQ itself. Internally it uses TPL for execution. Task Parallel Library The Task Parallel Library (TPL) is the ...
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Java Concurrency
The Java programming language and the Java virtual machine (JVM) have been designed to support concurrent programming, and all execution takes place in the context of threads. Objects and resources can be accessed by many separate threads; each thread has its own path of execution but can potentially access any object in the program. The programmer must ensure read and write access to objects is properly coordinated (or " synchronized") between threads. Thread synchronization ensures that objects are modified by only one thread at a time and that threads are prevented from accessing partially updated objects during modification by another thread. The Java language has built-in constructs to support this coordination. Processes and threads Most implementations of the Java virtual machine run as a single process and in the Java programming language, concurrent programming is mostly concerned with threads (also called lightweight processes). Multiple processes can only be realize ...
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Goroutine
Go is a statically typed, compiled programming language designed at Google by Robert Griesemer, Rob Pike, and Ken Thompson. It is syntactically similar to C, but with memory safety, garbage collection, structural typing, and CSP-style concurrency. It is often referred to as Golang because of its former domain name, golang.org, but its proper name is Go. There are two major implementations: * Google's self-hosting "gc" compiler toolchain, targeting multiple operating systems and WebAssembly. * gofrontend, a frontend to other compilers, with the ''libgo'' library. With GCC the combination is gccgo; with LLVM the combination is gollvm. A third-party source-to-source compiler, GopherJS, compiles Go to JavaScript for front-end web development. History Go was designed at Google in 2007 to improve programming productivity in an era of multicore, networked machines and large codebases. The designers wanted to address criticism of other languages in use at Google, but keep t ...
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Fiber (computer Science)
In computer science, a fiber is a particularly lightweight thread of execution. Like threads, fibers share address space. However, fibers use cooperative multitasking while threads use preemptive multitasking. Threads often depend on the kernel's thread scheduler to preempt a busy thread and resume another thread; fibers yield themselves to run another fiber while executing. Threads, fibers and coroutines The key difference between fibers and kernel threads is that fibers use cooperative context switching, instead of preemptive time-slicing. In effect, fibers extend the concurrency taxonomy: * on a single computer, multiple processes can run * within a single process, multiple threads can run * within a single thread, multiple fibers can run Fibers (sometimes called stackful coroutines or user mode cooperatively scheduled threads) and stackless coroutines (compiler synthesized state machines) represent two distinct programming facilities with vast performance and functiona ...
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Grand Central Dispatch
Grand Central Dispatch (GCD or libdispatch), is a technology developed by Apple Inc. to optimize application support for systems with multi-core (computing), multi-core processors and other symmetric multiprocessing systems. It is an implementation of task parallelism based on the thread pool pattern. The fundamental idea is to move the management of the thread pool out of the hands of the developer, and closer to the operating system. The developer injects "work packages" into the pool oblivious of the pool's architecture. This model improves simplicity, portability and performance. GCD was first released with Mac OS X 10.6, and is also available with iOS (Apple), iOS 4 and above. The name "Grand Central Dispatch" is a reference to Grand Central Terminal. The source code for the library that provides the implementation of GCD's services, ''libdispatch'', was released by Apple under the Apache License on September 10, 2009. It has been ported to FreeBSD 8.1+, MidnightBSD 0.3+ ...
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RaftLib
RaftLib is a portable parallel processing system that aims to provide extreme performance while increasing programmer productivity. It enables a programmer to assemble a massively parallel program (both local and distributed) using simple iostream-like operators. RaftLib handles threading, memory allocation, memory placement, and auto-parallelization of compute kernels. It enables applications to be constructed from chains of compute kernels forming a task and pipeline parallel compute graph. Programs are authored in C++ (although other language bindings are planned). Example Here is a Hello World example for demonstration purposes: #include #include #include #include class hi : public raft::kernel ; int main( int argc, char **argv ) References External links The RaftLib Project PageRaftLib User WikiProject GitHub RepositoryCPPNow RaftLib Tutorial SessionParallel BZip2 Implementation Using RaftLib {{Parallel computing C++ programming language family ...
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