这些单元与基准时间寄存器相同，并且两个线程的PURR值的总和等于基准时间寄存器的值。
The units are the same as the time base register and the sum of the PURR values for both threads is equal to time base register.
在编写有效的基准时，要求我们能够“愚弄”编译器，即使它认识到代码没有用处，也不能让它将代码砍掉。
Writing effective benchmarks requires that we "fool" the compiler into not pruning away code as dead, even though it really is.
该脚本的初始版本包含队列管理器的本地基准，例如设置死信队列、锁定远程管理访问以及优化通道。
The initial version of the script contains the local baseline for a queue manager, such as setting the dead queue, locking down remote administrative access, and tuning channels.
首先编写一个脚本，遍历一组队列管理器，使用MO72收集队列管理器的安全性设置的细节，并将其与目标基准进行比较。
Starting with a script that iterates through a list of queue managers, I use MO72 to gather details of the security Settings on the queue managers and compare these to a target baseline.
当比较TPC - H10TB结果时，您将注意到，DB 2V8.2.2(在8 8 -路p 5 575服务器上)交付了历史上最高的TPC - h基准(在本文编写之际)。
When comparing the TPC-H 10 TB results, you'll note that DB2 V8.2.2 (on 8 8-way p5 575 servers) delivers the highest performing TPC-H benchmark ever (as of the time this article was written).
结合测试或基准的结果，这将告诉您用以支持正常操作所必需的服务器容量。
This, combined with the results of testing or benchmarks, will tell you the server capacity required to support normal operations.
目的不是运行一个典型的、具有大量内存和存储服务器需求的数据库基准，而是测试CPU和进程的可伸缩性。
The purpose was not to run a typical database benchmark with huge memory and storage server requirements, but rather to test CPU and process scalability.
如果这些其他任务没有一个得到改进，则25%的基准测试节省将变成在您的服务器上的12.5%的节省。
If none of these other tasks shows any improvements, the 25 percent benchmark savings would become a 12.5 percent savings on your server.
在基准测试环境中，您可以控制安装，正确地设置哪些程序运行在服务器上，从基准测试客户端以某个特定的比率。
In a benchmark environment, you have control over the setup, and you establish exactly what is running on your server, at what specific rates, from your benchmark clients.
这些小基准测试也阐明了存在动态编译器的情况下解释性能结果所面临的挑战。
These small benchmarks also illustrate the challenge of interpreting performance results in the presence of dynamic compilers.
负载测试需要较多的资源，所有资源都来自同一个物理服务器，所以这些基准测试不应该在经过了操作系统虚拟化的系统上执行。
The load tests require more resources, and all will share from the same physical server, so these benchmark tests should not be performed on operating system-virtualized systems.
由于虚拟机将使用与主机相同的处理器作为基准，因此要求我们克隆的主机环境和物理服务器具有兼容的处理器类型。
Because the virtual machine will use the same processor as the host as a baseline, it requires that the host environment and the cloned physical server have compatible types of processors.
为了成功地实现更高的服务器可伸缩性目标，我们必须确保客户端基准测试系统能够承受大量用户。
To successfully meet the high server scalability goals, we have to make sure our client benchmark systems are sufficient to support many, many users.
表1展示了各种解析器技术在基准测试侧边栏中描述的计算机上测试版权数据使用的时间。
Table 1 shows timings of various parser techniques as measured against the copyright data on the computer described in the benchmarks sidebar.
由于这个原因，如果装载上一组用户令处理器的负载达到极限，基准测试往往缩短装载时间，留出一段时间用于评测稳定状态。
For this reason, benchmarks tend to scale back the timing for loading the last set of users if they are pushing the processor to its limit and to allow some time before measuring the steady state.
但是，这样做得到的往往是一个不做任何事的基准，在您不知情的情况下，编译器可能将此操作部分地或者完全地优化掉，使得测试运行起来比预期更快。
But often, the result is a do-nothing benchmark, which the compiler can optimize away partially or completely without you realizing it, making the test run faster than expected.
如果您的系统已有一个首选和备用DNS服务器，要对另外4全球DNS服务器进行测试，则只有最好的4个区域DNS会被用在基准测试里面。
If your system has a primary and secondary DNS server, and 4 global DNS servers to test, only the best 4 regional DNS servers will be used in the benchmark.
接下来，做处理器和磁盘基准测试，然后是两节点（并行）基准测试，再执行多节点（并行）基准测试。
Next, work your way up to processor and disk benchmarks, then two-node (parallel) benchmarks, then multi-node (parallel) benchmarks.
表 1 到表4 所示的用户数只是运行基准脚本的实例，它们不一定与服务器上部署的实际用户数相关。
The users shown in tables 1-4 are only instances of the benchmark script running, and they do not necessarily correlate to the number of actual users deployed on a server.
而当这些驱动器快速地从某个容量基准点增长时，它们的RPM并没有相应地增加。
And while these drives are growing very quickly from a capacity standpoint, they are not getting much faster in terms of RPMs.
存在各种各样的基准，什么样的工作量可以被支持，什么样的服务器可以运行在什么样的平台上，这里面有很强的应用程序依赖性。
While various benchmarks exist for what workload can be supported by what servers on which platforms, overall this area is highly application-dependent.
在用户应用程序受限于CPU的情况下，建立一个基准比较处理器的分配和合理的并发用户数非常理想。
In a very simplistic situation where a user-base application is CPU bound, it would be ideal to create a matrix that compares processor allocation to a reasonable number of concurrent users.
制作服务器和配置信息的基准。
理解基准测试服务器的作用。
在填充完账单表后，立即利用以下命令来清除状态计数器：onstat -z并重启动基准。
Immediately, after the bills table is populated, we then clear the status counters with: onstat -z and restart the benchmark.
为这些测试开发的基准实用程序使用HTML解析器来处理Web内容，更新有关链接、表单和表等元素的信息。
The benchmarking utility developed for these tests USES an HTML parser to process Web content, updating information about links, forms, tables, and so on.
本文描述了针对TPC - h基准测试公布，与在基于IntelItanium2处理器的平台上安装和配置IBMDB 2UniversalDatabase相关的关键问题。
This paper described the key setup and configuration of the IBM DB2 Universal Database on an Intel Itanium 2 processor-based platform for a TPC-H Benchmark publication.
即使不想让您的生产服务器承受像我们的基准测试中那么重的负担，也应该知道Domino现在的版本与6.5版本相比，能够处理的用户数量增加了50%。
While you probably would not want to push a production server as hard as we do during a benchmark, it is good to know that Domino can now handle 50 percent more users than it could in release 6.5.
这个基准测试工具将连接到您的Web服务器，然后模拟多个用户。
This benchmarking tool will launch connections to your Web server to simulate multiple users.
例如，IBMPower 5服务器(和它们的基准)在官方是按核心数量报告的。
For example, IBM Power5 servers (and their benchmarks) are officially reported by the number of cores.
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