不过，如果您的应用程序是部署在多处理器系统上或者使用非常大的堆，那么改变收集器选项可能会有巨大的性能提升。
However, if your application is deployed on a multiprocessor system or USES a very large heap, you may get some performance boost from changing collector options.
在多处理器的系统中，它们确实可以同时运行。
On a multiprocessor system, they really can run simultaneously.
这在多处理器系统中是一项特别重要的技术，(原则上)可在其中进行并发处理而无需降低响应时间。
This is an especially important technique on multi-processor systems, where concurrency can (in principle) be used without degrading response time.
在多处理器系统中，Linux试图模拟分派到可用处理器的单个全局RT线程队列的行为。
On multiprocessor systems, Linux tries to emulate the behavior of a single global queue of RT threads that are dispatched to available processors.
subpool：加速多处理器系统的对象分配。
Subpool: Speeds up object allocation on systems with very large Numbers of processors.
在带有三个或更多处理器的系统上，程序运行至完成并生成一个结果。
The program runs to completion and produces a result on a system with three or more processors.
分配组还有助于在多处理器系统上优化并行io性能，因为可以同时有多个元数据更新处于“在传输中”。
Allocation groups also help to optimize parallel IO performance on multiprocessor systems, because more than one metadata update can be "in transit" at the same time.
这些新收集器是为了解决在多处理器系统中垃圾收集器成为伸缩性瓶颈这一问题的。
These new collectors address the problem of the garbage collector being a scalability bottleneck on multiprocessor systems.
JD K 1.4.1通过增加新的针对多处理器系统和非常大的堆的多线程收集选项，进一步改进了垃圾收集的效率。
The 1.4.1 JDK further improves the effectiveness of garbage collection by adding new multithreaded collection options for multiprocessor systems and very large heaps.
从很低端的桌面系统到大型的、企业级的、多处理器的系统，新的内存管理代码已经在它们上面都已经进行了测试和优化。
The new memory management code has been tested and optimized on everything from very low end desktop systems to large, enterprise-class, multi-processor systems.
要使用多处理器系统的功能，通常需要使用多线程构造应用程序。
To exploit the power of multiprocessor systems, applications are generally structured using multiple threads.
现在，多处理器系统很便宜，而且数量很多，几乎每个主要微处理器都内置了多处理支持，其中许多系统支持数十个或数百个处理器。
Today, multiprocessor systems are cheap and plentiful, nearly every major microprocessor has built-in support for multiprocessing, and many support dozens or hundreds of processors.
考虑一下如下事实：今天的多核、多处理器系统与昨日的单核的庞然大物相较而言已是相去甚远。
Consider this: Today's multicore, multiprocessor systems are a far cry from yesterday's single-core behemoths.
十五年前，多处理器系统是高度专用系统，要花费数十万美元(大多数具有两个到四个处理器)。
Fifteen years ago, multiprocessor systems were highly specialized systems costing hundreds of thousands of dollars (and most of them had two to four processors).
如果某个远程计算机是一个多处理器系统，HostSelector可能会不止一次地返回该主机名。
If a remote machine is a multiprocessor system, the HostSelector may return the name of this host more than once.
同样的过滤器可以在不同的GPU和CPU架构上高效运行，包括多核与多处理器系统。
Allows the same filter to run efficiently on different GPU and CPU architectures, including multi-core and multiprocessor systems.
现在呢，我却正在一台具有RAID磁盘、32GB内存（对我来说这可真大）并运行了2个月的8 路多处理器系统上使用一个shell提示符。
And yet, here I am with a shell prompt on an eight-way multiprocessor system with RAID drives, 32GB of memory (hey, it looks huge to me), and two months of uptime.
Linux用于嵌入式的因特网设备也是很合适的，原因是它支持多处理器系统，该特性使Linux具有了伸缩性。
Linux is also well-suited for embedded Internet devices, because of its support of multiprocessor systems, which lends it scalability.
由 -XX:+UseParallelGC启用的并行清除收集器是年轻代收集器，针对多处理器系统上非常大(吉字节以及更大的)堆进行了优化。
The parallel scavenging collector, enabled by -XX:+UseParallelGC, is a young-generation collector optimized for very large (gigabyte and larger) heaps on multiprocessor systems.
被叫作“多处理器系统”的一般有公用的内存空间，处理器通过它们进行通讯和共用数据。
So-called "multiprocessor systems" usually have a common memory space through which the processors can communicate and share data.
为了更有效率地应用多处理器系统，复制以及压缩也可以平行地实行。
To utilize multiprocessor systems more efficiently, copying and compression can also be performed in parallel.
另外，一些多处理器系统支持并行处理。
In addition, some multiprocessor systems support parallel processing.
引言多处理器系统作为红外成像探测系统的重要组成部分，主要完成红外图像处理和目标检测。
The multiprocessing system is one of the most important parts of infrared imaging and detecting systems.
文章在分析已有并行关联规则挖掘算法的基础上，讨论了多处理器系统中影响并行关联规则挖掘算法性能的主要问题。
The current algorithms of parallel association rules mining are analyzed, and the main factors affecting the performance of the mining algorithm in the multi-processor system are discussed.
包含概述在多处理器系统中生成时的注意事项的主题，例如并行生成以及有效使用内存。
Contains topics that outline what to consider when you are building on a multi-processor system, for example, building in parallel and using memory efficiently.
这尤其是在多处理器系统方面的一个问题，超过程序可能存取一个资料项目哪里。
This is especially a problem on multiprocessor systems where more than one process may be accessing a datum.
这尤其是在多处理器系统方面的一个问题，超过程序可能存取一个资料项目哪里。
This is especially a problem on multiprocessor systems where more than one process may be accessing a datum.
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