“多任务并行是道德上的一个缺憾”，当然这是一句玩笑话。
“ Multi-tasking is a moral weakness”, is of course all in fun.
数据并行与任务并行的结合可以很好地解决这些问题。
Integraing data parallel and task parallel can solve these problems.
任务并行库，又被称为TPL，本质上是一个高级版本的。NET线程池。
The Task Parallel Library, or TPL, is essentially an advanced version of the.net thread pool.
在我的一篇文章中，我将讨论势在必行数据并行而紧迫的任务并行。
In my next article, I will discuss Imperative Data Parallelism and Imperative Task Parallelism.
某些任务并行执行更合理，但是有一些必须串行执行以达到最佳的效率。
Certain tasks make more sense to run in parallel, and some must remain serial for maximum efficiency.
虽然已经有工具可以使并行处理，这些工具主要是致力于任务并行模式。
While there are already tools available that enable parallel processing, these tools are largely dedicated to task parallel models.
并行空间连接处理由三个阶段组成：任务创建，任务分配和任务并行执行。
Generally, parallel spatial processing includes three phases: task creation, task assignment and parallel task execution.
在算法上作了较详细的描述。在程序结构上提出了多任务并行处理的程序设计方法。
It provides a detailed description in algorithm and proposed a multiprogramming approach in program structure.
任务并行模型是建立在并行想法可以提取的建设，每个线程有自己的目标或完成的任务。
The task parallel model is built around the idea that parallelism can be extracted by constructing threads that each have their own goal or task to complete.
就像面向任务并行库的代码一样，PLINQ查询会根据主计算机的能力按比例调整并发程度。
Just like code that targets the Task Parallel Library, PLINQ queries scale in the degree of concurrency based on the capabilities of the host computer.
第四个视频针对并行扩展的核心——任务并行库（TaskParallel Library）。
The fourth video is on the core of Parallel Extensions, the Task Parallel Library.
一个托管编程模型，支持数据并行处理，任务并行处理，并通过一个通用的工作调度器统一协调并行运行的硬件。
A managed programming model for data parallelism, task parallelism, and coordination on parallel hardware unified by a common work scheduler.
本文首先介绍两种典型的并行执行方式：支持数据并行语言的SPMD方式和支持任务并行语言的MPMD方式。
Firstly, this paper introduces two existed parallel execution models: SPMD and MPMD supporting data parallel and task parallel languages, respectively.
微软正在努力改进。NET 4.5中应用程序的性能，特别是使用任务并行类库(TaskParallelLibrary)的那些应用。
Microsoft has been working on ways to improve the performance of parallel applications in.net 4.5, specifically those using the Task parallel Library. Here is a preview of what you can expect to see.
与其他任务并行运行的应用程序部分应该加入Work对象，它是实现com . ibm . websphere . asynchbeans .Work接口的对象。
The application part which is designed to run in parallel to other tasks should go into a Work object, which is an object implementing the com.ibm.websphere.asynchbeans.Work interface.
我们向他们强调了RUP具有允许任务交迭执行的好处；也就是说，不同阶段的任务可以并行的被执行。
We emphasized that the RUP has the advantage of allowing task overlaps; that is, different phases can have tasks taking place in parallel.
如果线程之间不需要协调，那么几乎没有任务可以真正地并行。
Few tasks can be truly parallelized in such a way as to require no coordination between threads.
这些线程是由CSLD任务自动启动的，并且并行地运行。
The threads are automatically started by the CSLD task and will run in parallel.
然而，增加并行CSLD任务的数量，特别是增加它们内部的线程数，并不是件容易的事情。
Increasing the number of parallel CSLD tasks and particularly their internal threads, however, is not as straightforward.
这意味着有5个并行的CSLD任务线程。
这就是说，当执行大型任务时，远程并行执行消耗的时间较少。
This means that remote parallel execution consumed less time on larger tasks.
试图同时着手多个并行项目、或是多个任务，都会损害进度。
Attempting to do too many concurrent projects or multitasking is detrimental to progress.
DSNTIP4上的MAXDEGREE选项决定了最大并行度（并行任务的最大数量）。
The MAX DEGREE option on DSNTIP4 determines the maximum degree of parallelism (maximum number of parallel tasks).
正如之前提到的，并行性指的是任务的并行处理能力，其中任务会分成不同的子任务，它们最后会合并为一个。
As mentioned before, parallelism implies the parallel-processing capability of a task where the task is split to different subtasks with consolidation at the end.
注意：与具有该名称的活动并行的人工任务可用性将是不可预测的，因为并行流程分支是并发的。
Note: the availability in human tasks parallel to the activity with this name would be unpredictable, since parallel process branches are concurrent.
在本文的内容中，并行性指的是能够并行执行多个请求或者将大数据量任务划分成多个并行执行的子任务。
In the content of this article, parallelism is the ability to execute multiple requests in parallel or to split a large dataset task into multiple subtasks which are executed in parallel.
用于选择顺序和并行执行方法的理想阙值是协调并行任务的成本。
The ideal threshold for choosing between sequential and parallel execution is a function of the cost of coordinating the parallel tasks.
依赖性较少的任务通常被描述为“高度平行”，即太容易将它们分成多个并行任务了。
Tasks with few dependencies are often described as "embarrassingly parallel," meaning that they're almost too easy to separate into a number of parallel tasks.
如图2所示，她可以执行西班牙和ANZ任务版本之间的并行的比较。
As illustrated in Figure 2, she can perform a side-by-side comparison between the Spanish and ANZ versions of the task.
如图2所示，她可以执行西班牙和ANZ任务版本之间的并行的比较。
As illustrated in Figure 2, she can perform a side-by-side comparison between the Spanish and ANZ versions of the task.
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