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===Parallel programming languages=== {{main|List of concurrent and parallel programming languages}} [[List of concurrent and parallel programming languages|Concurrent programming languages]], [[Library (computing)|libraries]], [[Application programming interface|APIs]], and [[parallel programming model]]s (such as [[algorithmic skeleton]]s) have been created for programming parallel computers. These can generally be divided into classes based on the assumptions they make about the underlying memory architecture—shared memory, distributed memory, or shared distributed memory. Shared memory programming languages communicate by manipulating shared memory variables. Distributed memory uses [[message passing]]. [[POSIX Threads]] and [[OpenMP]] are two of the most widely used shared memory APIs, whereas [[Message Passing Interface]] (MPI) is the most widely used message-passing system API.<ref>The [http://awards.computer.org/ana/award/viewPastRecipients.action?id=16 Sidney Fernbach Award given to MPI inventor Bill Gropp] {{Webarchive|url=https://web.archive.org/web/20110725191103/http://awards.computer.org/ana/award/viewPastRecipients.action?id=16 |date=2011-07-25 }} refers to MPI as "the dominant HPC communications interface"</ref> One concept used in programming parallel programs is the [[Futures and promises|future concept]], where one part of a program promises to deliver a required datum to another part of a program at some future time. Efforts to standardize parallel programming include an open standard called [[OpenHMPP]] for hybrid multi-core parallel programming. The OpenHMPP directive-based programming model offers a syntax to efficiently offload computations on hardware accelerators and to optimize data movement to/from the hardware memory using [[remote procedure call]]s. The rise of consumer GPUs has led to support for [[compute kernel]]s, either in graphics APIs (referred to as [[compute shader]]s), in dedicated APIs (such as [[OpenCL]]), or in other language extensions.
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