Control the number of concurrent applications for a resource.
控制同时访问一个资源的应用程序数量。
The ship design process model is basic for developing the concurrent a nd cooperative ship design system.
船舶设计过程模型是在网络环境下开展船舶并行和协同设计系统的基础。
A simple modification of the presented approach allows you to control the number of concurrent applications for a set of resources
对以上方式做一项简单的修改，就可以控制同时访问一个资源集的应用程序数量
In large applications with many users and many concurrent tasks, a user needs the ability to arrange his or her task list according to criteria.
在具有很多用户和很多并发任务的大型应用程序中，用户需要能够根据相关标准对其任务列表进行排列。
These classes will work cooperatively in a concurrent manner.
这些类将以一种并发方式协同工作。
The actor model is a different way of modeling concurrent processes.
角色模型是一种不同的并发进程建模方式。
Because your browser limits the number of concurrent connections to a single domain, whenever a page loads, it's easy to occupy all the threads.
因为您的浏览器将并发连接的数量限制到一个单一的域，因此无论何时加载一个页面，都很容易占满所有线程。
While the target variable is guaranteed to be only assigned once, the delegate may be called by multiple concurrent threads unless a synchronization object is passed in.
这保证了目标变量只会设置一次。不过，如果没有使用同步对象的话，委托可能会被几个并发线程调用多次。
This degradation indicates that, for that particular system, a load of 350 concurrent users is near the optimal load for a repository with 100,000 resources.
这种性能上的降低，意味着拥有 350 个并发用户的负荷，已经是一个拥有 100,000资源的存储库的最佳负荷了。
A contact task contains concurrent or asynchronous operations is a long-running process, and progress at every step needs to be saved to a database.
包含并发或异步操作的联系任务是一个长期运行的进程，每一步进展都要被保存到数据库。
Based on this idea, let's look at the concept of a concurrent queue where push and pop operations come with timeouts.
根据这个概念，我们来看看如何给并发队列的添加和取出操作增加超时限制。
The following class is a model of a common concurrent utility: a work queue.
下面的类是一种常见的并行实用程序模型：任务队列。
With a traditional concurrent environment, you might use a solution such as a semaphore that allows processes to determine whether a variable is 'in use' or can be updated.
在传统并行环境中，您可以使用信号量这样的解决方案，允许进程确定一个变量是否 “处于使用中”，还是可更新。
This queue type is similar to a concurrent blocking queue except that the size of the queue is bounded.
这种队列与并发阻塞队列相似，但是对队列的大小有限制。
When this threshold approaches, a concurrent GC begins.
达到这个阈值时，就会启动一个并发gc。
For instance, a scalable system with a response of 3 seconds for 100 concurrent users should have a 3-second response time for 1 million concurrent users.
例如，3秒钟对100个并发用户作出响应的可伸缩的系统应该也可以3秒钟对100万并发用户作出响应。
Databases are not good at executing lots of concurrent transactions with a small number of records per transaction.
数据库并不擅于执行大量处理少量记录的并发事务。
Because multiple concurrent XML HTTP requests can be scheduled in parallel, our application essentially becomes a concurrent program — and concurrency is hard.
由于可能同时调度多个并发的XMLHTTP请求，应用程序本质上变成了一个并发程序，而并发很难实现。
Now that you have some understanding of CAS, let's design a concurrent stack.
既然了解了CAS，现在就来设计一个并发堆栈。
Since each thread performs a task, each concurrent thread needs a database connection.
由于每个线程都需要执行一个任务，因此各并发线程都需要一个数据库连接。
Designing a concurrent blocking queue with timeouts.
设计有超时限制的并发阻塞队列。
If you use a language like Scheme there are some examples of a concurrent extension.
如果您使用像Scheme的语言，那么有一些并行扩展的实例。
Designing a concurrent blocking bounded queue.
设计有大小限制的并发阻塞队列。
It's written in Erlang, a concurrent programming language that supports building distributed, fault-tolerant, nonstop applications (see Resources).
它是使用并发编程语言erlang编写的，它支持绑定分布式、容错、不间断应用程序(参见参考资料)。
Other possibilities are for a concurrent collection or for a collection forced by System.gc .
其他可能性包括针对并发收集的或针对由System . gc强制执行的收集的。
It's efficient and proven to scale to millions of concurrent users on a single service (such as Google's GTalk).
它很高效，并且被证明可以在一个单独的服务上扩展到数百万的并发用户(比如Google的GTalk)。
There's a module for manipulating lists, a module for concurrent programming, a module for dealing with complex numbers, etc.
有处理List的模块, 有处理并发的模块, 也有处理复数(complex number, 感谢roy_hu大牛提醒)的模块, 等等.
For the latter topic, I have chosen to implement a concurrent stack and highlight some of the issues in designing such a data structure.
对于后一个主题，我选择实现一个并发堆栈并解释设计这种数据结构涉及的一些问题。
This article, the first in a two-part series, discusses the design of concurrent data structures in a multithreaded environment.
本文是两篇系列文章的第一篇，讨论如何在多线程环境中设计并发数据结构。
Because it enables concurrent processing in a very neat way it would be a good candidate for building Grid Solutions on a multi-core environment.
因为它能用非常简洁的方式进行并发处理，这可能是在多核环境下构建网格方案很好的备选方法。
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