首先，正如前面几个回答中提到的，了解是什么影响了您的性能——是内存、处理器、网络、数据库还是其他东西。这取决于…

...if it's memory - find one of the books written long time ago by Knuth, one of "The Art of Computer Programming" series. Most likely it's one about sorting and search - if my memory is wrong then you'll have to find out in which he talks about how to deal with slow tape data storage. Mentally transform his memory/tape pair into your pair of cache/main memory (or in pair of L1/L2 cache) respectively. Study all the tricks he describes - if you don's find something that solves your problem, then hire professional computer scientist to conduct a professional research. If your memory issue is by chance with FFT (cache misses at bit-reversed indexes when doing radix-2 butterflies) then don't hire a scientist - instead, manually optimize passes one-by-one until you're either win or get to dead end. You mentioned squeeze out up to the last few percent right? If it's few indeed you'll most likely win. ...if it's processor - switch to assembly language. Study processor specification - what takes ticks, VLIW, SIMD. Function calls are most likely replaceable tick-eaters. Learn loop transformations - pipeline, unroll. Multiplies and divisions might be replaceable / interpolated with bit shifts (multiplies by small integers might be replaceable with additions). Try tricks with shorter data - if you're lucky one instruction with 64 bits might turn out replaceable with two on 32 or even 4 on 16 or 8 on 8 bits go figure. Try also longer data - eg your float calculations might turn out slower than double ones at particular processor. If you have trigonometric stuff, fight it with pre-calculated tables; also keep in mind that sine of small value might be replaced with that value if loss of precision is within allowed limits. ...if it's network - think of compressing data you pass over it. Replace XML transfer with binary. Study protocols. Try UDP instead of TCP if you can somehow handle data loss. ...if it's database, well, go to any database forum and ask for advice. In-memory data-grid, optimizing query plan etc etc etc.

HTH:)

如果更好的硬件是一个选择，那么一定要去做。否则

Check you are using the best compiler and linker options. If hotspot routine in different library to frequent caller, consider moving or cloning it to the callers module. Eliminates some of the call overhead and may improve cache hits (cf how AIX links strcpy() statically into separately linked shared objects). This could of course decrease cache hits also, which is why one measure. See if there is any possibility of using a specialized version of the hotspot routine. Downside is more than one version to maintain. Look at the assembler. If you think it could be better, consider why the compiler did not figure this out, and how you could help the compiler. Consider: are you really using the best algorithm? Is it the best algorithm for your input size?

你在什么硬件上运行?您是否可以使用特定于平台化的优化(如向量化)? 你能找到更好的编译器吗?比如从GCC换成Intel? 你能让你的算法并行运行吗? 可以通过重新组织数据来减少缓存丢失吗? 可以禁用断言吗? 对编译器和平台进行微优化。在if/else语句中，把最常见的语句放在前面

缓存!要使几乎任何事情都变得更快，一个便宜的方法(在程序员的努力中)是在程序的任何数据移动区域添加缓存抽象层。无论是I/O还是只是传递/创建对象或结构。通常，向工厂类和读取器/写入器添加缓存是很容易的。

有时缓存不会给你带来太多好处，但这是一种简单的方法，只需添加缓存，然后在没有帮助的地方禁用它。我经常发现这样做可以获得巨大的性能，而无需对代码进行微观分析。

当你不能再提高表现时，看看你是否可以提高感知的表现。

您可能无法使您的fooCalc算法更快，但通常有一些方法可以使您的应用程序对用户的响应更快。

举几个例子:

预测用户将要做什么 请求并开始着手这项工作 在那之前 将结果显示为 它们是进来的，而不是同时出现的 在最后 精确的进度计

这些不会让你的程序更快，但可能会让你的用户对你的速度更满意。

有时改变数据的布局会有所帮助。在C语言中，可以从数组或结构切换到数组结构，反之亦然。