Data parallelism refers to scenarios in which the same operation is performed concurrently (that is, in parallel) on elements in a source collection or array. Data parallelism with imperative syntax is supported by several overloads of the For and ForEach methods in the System.Threading.Tasks....
The Task Parallel Library (TPL) supports data parallelism through the System.Threading.Tasks.Parallel class. This class provides method-based parallel implementations of for and foreach loops (For and For Each in Visual Basic). You write the loop logic for a Parallel.For or Parallel.ForEach loo...
Read how the Task Parallel Library (TPL) supports data parallelism to do the same operation concurrently on a source collection or array's elements in .NET.
For data parallelism this increase is roughly in proportion to increases in dataset size; (b)If a MapReduce implementation is used as part of an ILP system, then benefits for data parallelism can only be expected above some minimal dataset size, and for task parallelism can only be expected ...
(转)Net4.0 Parallel编程 Data Parallelism 首先我们来看下线程局部变量,是的我们也许一直在想我们如何去定义一个线程局部变量呢。先看段顺序执行的代码: 01.[TestMethod()] 02.publicvoidNormalSequenceTest() 03.{ 04.int[] nums = Enumerable.Range(0, 1000000).ToArray();...
数据并行(data parallelism)指多个不同的数据同时被相同的指令、指令集或者算法处理。这与GPU的并行概念是相同的。 book.51cto.com|基于19个网页 2. 数据并行化 同时,这也是数据并行化(data parallelism)技术的一个标准应用。对于并行循环来说,决定它并行度的通常不是代码,而是 … ...
Combining Data Parallelism and Task Parallelism for Efficient Performance on Hybrid CPU and GPU Systems | Aditya Deshpande | Algorithms, Compression, Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 580, nVidia Quadro FX 3700, Package, Sorting, Sparse matrix, Tesla K20, Thesis ...
It is important for anyone writing parallel programs to understand the differences between data and task parallelism and to be able to recognize them when they see them. The type of parallelism involved with your algorithm can have drastic implications on how it can be implemented, both...
For the graphics processor we exploit data parallelism by off-loading the computationally expensive kernels to the accelerator while keeping the numeric semantics of the sequential case. 展开 关键词: Sparse linear systems Reconditioned Conjugate Gradient solver Task and data parallelism Multi-core ...
2.1Data Parallelism 程序运行慢的原因:通常是要处理的数据太多。 Data Parallelism的基础:针对数据重新组织计算,目的是并行地执行独立的计算,以实现快速计算的效果。 Data Parallelism 与Task Parallelism: 任务并行通常是基于目标任务的分解。 举个例子:分子动力学模拟中,任务列表包括振动力,旋转力,非成键力的相邻识别...