In addition, some multiprocessor systems support parallel processing.
另外，一些多处理器系统支持并行处理。
It is important for Cache Coherence Protocol in Multiprocessor Systems.
在多处理嚣系统中，高速缓存的一致性协议是很重要的。
In this thesis, we study some variants of diagnosis problems on multiprocessor systems.
在这篇论文当中，我们针对多处理机系统研究了一些不同的诊断问题。
To exploit the power of multiprocessor systems, applications are generally structured using multiple threads.
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。
Consider this: Today's multicore, multiprocessor systems are a far cry from yesterday's single-core behemoths.
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。
Multithreading can also improve the speed of performing some tasks, especially on multiprocessor systems.
多线程同样能够提高一些任务的执行速度，特别是在多处理器系统中。
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。
To utilize multiprocessor systems more efficiently, copying and compression can also be performed in parallel.
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。
These new collectors address the problem of the garbage collector being a scalability bottleneck on multiprocessor systems.
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。
As one of the most important issues in multiprocessor systems, data locality is a main direction of studies on such systems.
数据局部性是多处理器系统中的重要研究方向之一。
Allows the same filter to run efficiently on different GPU and CPU architectures, including multi-core and multiprocessor systems.
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。
Based on local-memory multiprocessor systems, a study is made of two models of parallel processing: multitask and master-worker.
基于自带存储器的多处理机系统，对多任务模式和农场主-雇员模式都作了探讨。
Linux is also well-suited for embedded Internet devices, because of its support of multiprocessor systems, which lends it scalability.
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。
This is actually the case on multiprocessor systems, where the executable threads are distributed among the available processors.
这实际上就是多处理器系统中发生的情形，在此类系统中，可执行线程分布在多个可用处理器中。
So-called "multiprocessor systems" usually have a common memory space through which the processors can communicate and share data.
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。
RTEMS (real-time Executive for Multiprocessor systems) is a free open source real-time operating system designed for embedded systems.
(多处理系统实时可执行体)一个自由的为嵌入式系统而设计的开源实时操作系统。
RTEMS (real-time Executive for Multiprocessor systems) is a free open source real-time operating system designed for embedded systems.
RTEMS(多处理系统实时可执行体)一个自由的为嵌入式系统而设计的开源实时操作系统。
On multiprocessor systems, Linux tries to emulate the behavior of a single global queue of RT threads that are dispatched to available processors.
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。
In the multiprocessor systems, an efficient scheduling of a parallel program onto the processors that minimizes the entire execution time is vital.
在多处理器系统中，寻求一个有效的并行任务设计安排使得整个执行时间达到最小是至关重要的环节。
Many techniques have been proposed to reduce power consumption for uniprocessor systems, while less work have taken multiprocessor systems into account.
然而目前一些有效降低能量消耗的技术大多针对单处理器系统，较少考虑多处理器系统。
Parallel preconditioning algorithm based on multiprocessor systems with local memory is stressed, so that two kinds of PPCG. PPCG1 and PPCG2 are proposed.
着重讨论了基于自带存储器的多处理机系统的并行预处理算法问题，并由此提出了两种PPCG法：PPCG1和PPCG2法。
In order to develop the performance of the multiprocessor systems, the support software is essential, of which the operating system is the most important.
多处理机系统是实现并行处理的高效低价的选择，要发挥多处理机系统的性能必须要有相应的软件支撑，这中间最为重要的就是操作系统。
Fifteen years ago, multiprocessor systems were highly specialized systems costing hundreds of thousands of dollars (and most of them had two to four processors).
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)。
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.
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”。
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.
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 parallel scavenging collector, enabled by -XX:+UseParallelGC, is a young-generation collector optimized for very large (gigabyte and larger) heaps on multiprocessor systems.
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。
All of these optimizations are to aid in higher performance, and are generally transparent to the user, but on multiprocessor systems, these complexities may sometimes show through.
所有的这些优化是为了帮助实现更高的性能，通常这对于用户来说是透明的，但是对多处理系统来说，这些复杂的事情可能有时会完全显现出来。
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.
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.
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。
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