blocks|key|4066274|text|维基百科有一个相当全面的here优化技术列表。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|4066275|entityMap|0|LINK|mutability|MUTABLE|url|http://en.wikipedia.org/wiki/Compiler_optimization^0|C|4|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

Wikipedia has a fairly comprehensive list of optimization techniques <a href="http://en.wikipedia.org/wiki/Compiler_optimization" rel="nofollow noreferrer">here</a>.

blocks|key|868631|text|最重要的一个是内存访问重新排序。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|868632|在没有内存围栏或序列化指令的情况下，处理器可以自由地重新排序内存访问。一些处理器架构对它们可以重新排序的数量有限制；Alpha是众所周知的最弱的(即可以重新排序最多的)。|868633|在Documentation/memory-barriers.txt上的Linux内核源代码文档中可以找到这个主题的一个很好的解决方案。|offset|length|868634|大多数情况下，最好使用编译器或标准库中的锁定原语；这些原语经过了良好的测试，应该具有所有必要的内存屏障，并且可能是非常优化的(优化锁定原语是很棘手的；即使是专家有时也会出错)。|868635|entityMap|0|LINK|mutability|MUTABLE|url|http://git.kernel.org/?p=linux/kernel/git/torvalds/linux-2.6.git;a=blob;f=Documentation/memory-barriers.txt;hb=HEAD^0|0|0|1|X|0|0|0^^$0|@$1|2|3|4|5|6|7|R|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|S|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|T|8|@]|9|@$F|U|G|V|1|W]]|A|$]]|$1|H|3|I|5|6|7|X|8|@]|9|@]|A|$]]|$1|J|3|-4|5|6|7|Y|8|@]|9|@]|A|$]]]|K|$L|$5|M|N|O|A|$P|Q]]]]

The most important one would be memory access reordering.

Absent memory fences or serializing instructions, the processor is free to reorder memory accesses. Some processor architectures have restrictions on how much they can reorder; Alpha is known for being the weakest (i.e., the one which can reorder the most).

A very good treatment of the subject can be found in the Linux kernel source documentation, at <a href="http://git.kernel.org/?p=linux/kernel/git/torvalds/linux-2.6.git;a=blob;f=Documentation/memory-barriers.txt;hb=HEAD" rel="noreferrer">Documentation/memory-barriers.txt</a>.

Most of the time, it's best to use locking primitives from your compiler or standard library; these are well tested, should have all the necessary memory barriers in place, and are probably quite optimized (optimizing locking primitives is tricky; even the experts can get them wrong sometimes).

blocks|key|4066197|text|是的，但你的问题到底是什么？|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4066198|然而，由于这是一个有趣的话题:编译器和处理器用来优化代码的技巧不应该破坏代码，即使在代码中没有竞争条件的情况下，使用多个处理器也是如此。这就是所谓的顺序一致性保证:如果您的程序没有任何争用条件，并且所有数据在访问之前都被正确锁定，则代码的行为将如同它是按顺序执行的一样。|4066199|Herb+Sutter在这里谈到了一个非常好的视频：|4066200|http://video.google.com/videoplay?docid=-4714369049736584770|offset|length|4066201|每个人都应该看看这个:)|4066202|entityMap|0|LINK|mutability|MUTABLE|url^0|0|0|0|0|1O|0|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|T|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|U|8|@]|9|@]|A|$]]|$1|F|3|G|5|6|7|V|8|@]|9|@$H|W|I|X|1|Y]]|A|$]]|$1|J|3|K|5|6|7|Z|8|@]|9|@]|A|$]]|$1|L|3|-4|5|6|7|10|8|@]|9|@]|A|$]]]|M|$N|$5|O|P|Q|A|$R|G]]]]

Yes, but what exactly is your question?

However, since this is an interesting topic: tricks that compilers and processors use to optimize code should not break code, even with multiple processors, in the absence of race conditions in that code. This is called the guarantee of sequential consistency: if your program does not have any race conditions, and all data is correctly locked before accessing, the code will behave as if it were executed sequentially.

There is a really good video of Herb Sutter talking about this here:

<a href="http://video.google.com/videoplay?docid=-4714369049736584770" rel="nofollow noreferrer">http://video.google.com/videoplay?docid=-4714369049736584770</a>

Everyone should watch this :)

blocks|key|3220113|text|DavidK的答案是正确的，但是了解您的语言/运行时的内存模型也是非常重要的。即使没有竞争条件，在顺序一致性和互斥使用的情况下，当数据被运行在cpu的不同内核中的不同线程缓存时，您的代码仍然可能崩溃。一些语言，例如Java，在使用互斥锁时确保线程之间的数据状态，但仅仅确保没有两个线程可以同时访问数据几乎是不够的。您需要以正确的方式使用互斥锁，以确保语言运行库同步两个线程之间的数据状态。在java中，这是通过让两个线程在同一对象上同步来实现的。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3220114|这里有一个很好的页面，解释了这个问题以及它是如何在javas内存模型中处理的。|3220115|http://gee.cs.oswego.edu/dl/cpj/jmm.html|offset|length|3220116|entityMap|0|LINK|mutability|MUTABLE|url^0|0|0|0|14|0|0^^$0|@$1|2|3|4|5|6|7|O|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|P|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|Q|8|@]|9|@$F|R|G|S|1|T]]|A|$]]|$1|H|3|-4|5|6|7|U|8|@]|9|@]|A|$]]]|I|$J|$5|K|L|M|A|$N|E]]]]

DavidK's answer is correct, however it is also very important to be aware of the memory model for your language/runtime. Even without race conditions and with sequential consistency and mutex usage your code can still break when data is being cached by different threads running in the different cores of the cpu. Some languages, Java is one example, ensure the state of data between threads when a mutex lock is used, but it is rarely enough to simply ensure that no two threads can access the data at the same time. You need to use the mutex in a correct way to ensure that the language runtime synchronizes the data state between the two threads. In java this is done by having the two threads synchronize on the same object.

Here is a good page explaining the problem and how it's dealt with in javas memory model.

<a href="http://gee.cs.oswego.edu/dl/cpj/jmm.html" rel="nofollow noreferrer"><a href="http://gee.cs.oswego.edu/dl/cpj/jmm.html" rel="nofollow noreferrer">http://gee.cs.oswego.edu/dl/cpj/jmm.html</a></a>

I am looking for things like reordering of code that could even break the code in the case of a multiple processor.

What are some tricks that a processor does to optimize code?

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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我正在寻找像代码重新排序这样的东西，在多处理器的情况下甚至可能破坏代码。

问处理器在优化代码时有哪些技巧？
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