Loop Scheduling
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Loop Scheduling
In parallel computing, loop scheduling is the problem of assigning proper iterations of parallelizable loops among ''n'' processors to achieve load balancing and maintain data locality with minimum dispatch overhead. Typical loop scheduling methods are: * static even scheduling: evenly divide loop iteration space into n chunks and assign each chunk to a processor * dynamic scheduling: a chunk of loop iteration is dispatched at runtime by an idle processor. When the chunk size is 1 iteration, it is also called self-scheduling. * guided scheduling: similar to dynamic scheduling, but the chunk sizes per dispatch keep shrinking until reaching a preset value. References * {{cite book, author1=Thomas Rauber, author2=Gudula Rünger, title=Parallel Programming: for Multicore and Cluster Systems, url=https://books.google.com/books?id=UbpAAAAAQBAJ&q=%22Loop+scheduling%22, date=13 June 2013, publisher=Springer Science & Business Media, isbn=978-3-642-37801-0 See also * OpenMP * Automatic p ...
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Parallel Computing
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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Load Balancing (computing)
In computing, load balancing is the process of distributing a set of tasks over a set of resources (computing units), with the aim of making their overall processing more efficient. Load balancing can optimize the response time and avoid unevenly overloading some compute nodes while other compute nodes are left idle. Load balancing is the subject of research in the field of parallel computers. Two main approaches exist: static algorithms, which do not take into account the state of the different machines, and dynamic algorithms, which are usually more general and more efficient but require exchanges of information between the different computing units, at the risk of a loss of efficiency. Problem overview A load-balancing algorithm always tries to answer a specific problem. Among other things, the nature of the tasks, the algorithmic complexity, the hardware architecture on which the algorithms will run as well as required error tolerance, must be taken into account. Therefore c ...
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Locality Of Reference
In computer science, locality of reference, also known as the principle of locality, is the tendency of a processor to access the same set of memory locations repetitively over a short period of time. There are two basic types of reference locality temporal and spatial locality. Temporal locality refers to the reuse of specific data and/or resources within a relatively small time duration. Spatial locality (also termed ''data locality''"NIST Big Data Interoperability Framework: Volume 1"urn:doi:10.6028/NIST.SP.1500-1r2) refers to the use of data elements within relatively close storage locations. Sequential locality, a special case of spatial locality, occurs when data elements are arranged and accessed linearly, such as traversing the elements in a one-dimensional Array data structure, array. Locality is a type of predictability, predictable behavior that occurs in computer systems. Systems that exhibit strong ''locality of reference'' are great candidates for performance optimiza ...
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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 ...
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Automatic Parallelization
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Loop Nest Optimization
In computer science and particularly in compiler design, loop nest optimization (LNO) is an optimization technique that applies a set of loop transformations for the purpose of locality optimization or parallelization or another loop overhead reduction of the loop nests. (Nested loops occur when one loop is inside of another loop.) One classical usage is to reduce memory access latency or the cache bandwidth necessary due to cache reuse for some common linear algebra algorithms. The technique used to produce this optimization is called loop tiling, also known as loop blocking or strip mine and interchange. Overview Loop tiling partitions a loop's iteration space into smaller chunks or blocks, so as to help ensure data used in a loop stays in the cache until it is reused. The partitioning of loop iteration space leads to partitioning of a large array into smaller blocks, thus fitting accessed array elements into cache size, enhancing cache reuse and eliminating cache size requir ...
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