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Loop-level parallelism is a form of parallelism in software programming that is concerned with extracting parallel tasks from loops.The opportunity for loop-level parallelism often arises in computing programs where data is stored in random access data structures.
Parallel task scheduling (also called parallel job scheduling [1] [2] or parallel processing scheduling [3]) is an optimization problem in computer science and operations research. It is a variant of optimal job scheduling .
oneAPI Threading Building Blocks (oneTBB; formerly Threading Building Blocks or TBB) is a C++ template library developed by Intel for parallel programming on multi-core processors. Using TBB, a computation is broken down into tasks that can run in parallel. The library manages and schedules threads to execute these tasks.
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.
The scheduler will generate a list of all the tasks and the details of the cores on which they will execute along with the time that they will execute for. The code Generator will insert special constructs in the code that will be read during execution by the scheduler.
Query by Slice, Parallel Execute, and Join: A Thread Pool Pattern in Java" by Binildas C. A. "Thread pools and work queues" by Brian Goetz "A Method of Worker Thread Pooling" by Pradeep Kumar Sahu "Work Queue" by Uri Twig: C++ code demonstration of pooled threads executing a work queue. "Windows Thread Pooling and Execution Chaining"
It is a C++ template library with six data-parallel and one task-parallel skeletons, two container types, and support for execution on multi-GPU systems both with CUDA and OpenCL. Recently, support for hybrid execution, performance-aware dynamic scheduling and load balancing is developed in SkePU by implementing a backend for the StarPU runtime ...
Fork–join is the main model of parallel execution in the OpenMP framework, although OpenMP implementations may or may not support nesting of parallel sections. [6] It is also supported by the Java concurrency framework, [7] the Task Parallel Library for .NET, [8] and Intel's Threading Building Blocks (TBB). [1]