像 Geekbench 这样的性能统计数据是否代表一般的多任务性能？
我试图比较 i7 双核 2.7Ghz 与 i7 四核 2.0Ghz 在多任务环境中的性能。四核得分约为 9000，双核得分约为 7500（Geekbench）。同时，Geekbench 明确指出测试显示了所有核心的全部性能潜力。然而，在现实世界中，日常使用中，我运行的应用程序几乎都不是多线程的（Ruby 运行时、Java IDE、Mac 上的 Windows VM、应用程序服务器）。
这台机器将作为网络开发机器。在此用例中，就响应时间而言，哪种 CPU 最“敏捷”？
I am trying to compare how an i7 dual core 2.7Ghz would perform vs. an i7 quad core 2.0Ghz in a multitasking environment. The quad core scores at around 9000 while the dual comes in at around 7500 (for Geekbench). At the same time, Geekbench explicity specifies that the tests show the full performance potential of all the cores. However, in real world, everyday use, almost none of the application I would be running are multi-threaded (Ruby runtime, Java IDE, Windows VM on mac, app server).
This machine would server as a web development machine. Which cpu would be most "snappy" in terms of response time in this use case?
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仅当基准测试非常接近您的典型工作负载时，基准测试结果才具有实际意义。
您应该考虑您的典型开发环境是否经常需要并行性。例如，如果我开发一个 C/C++/Java 应用程序，头文件（或 Java 源代码）更改通常会导致重新编译其他几个文件并重新链接一些二进制文件 - 这是高度并行的工作负载和多核CPU 可能具有优势。
另一方面，如果我要更改一些 Python 或 Javascript 源，我怀疑当我尝试执行和测试更改时是否会创建任何并行工作负载。
然而，这些都是理论上的考虑。
我不认为机器的速度是任何开发工作的瓶颈。人类是。
Results of a benchmark have any practical meaning only if the benchmark very closely approximates your typical workload.
You should consider whether your typical development environment regularly calls for parallelism. For example, if I develop a C/C++/Java app it's common that a header file (or Java source) change to cause several other files to be recompiled and a few binaries to be relinked - that's a highly parallel workload and many-core CPU may prove advantageous.
On the other hand, if I'm changing a few Python or Javascript sources, I doubt I will create any parallel workload when I try to execute and test the changes.
However, these are theoretical considerations.
I don't think the speed of the machine is a bottleneck in any development effort. The human is.