很多年前，我教别人用c语言编程。练习是将图形旋转90度。他得到了一个花了几分钟才能完成的解，主要是因为他使用了乘法和除法等。

我向他展示了如何使用位移位重定义问题，在他拥有的非优化编译器上，处理时间缩短到大约30秒。

我刚刚得到了一个优化编译器，相同的代码在< 5秒内旋转图形。我看着编译器生成的汇编代码，从我所看到的，我决定我写汇编程序的日子结束了。

使用SIMD指令的矩阵操作可能比编译器生成的代码更快。

以下是我个人经历中的几个例子:

Access to instructions that are not accessible from C. For instance, many architectures (like x86-64, IA-64, DEC Alpha, and 64-bit MIPS or PowerPC) support a 64 bit by 64 bit multiplication producing a 128 bit result. GCC recently added an extension providing access to such instructions, but before that assembly was required. And access to this instruction can make a huge difference on 64-bit CPUs when implementing something like RSA - sometimes as much as a factor of 4 improvement in performance. Access to CPU-specific flags. The one that has bitten me a lot is the carry flag; when doing a multiple-precision addition, if you don't have access to the CPU carry bit one must instead compare the result to see if it overflowed, which takes 3-5 more instructions per limb; and worse, which are quite serial in terms of data accesses, which kills performance on modern superscalar processors. When processing thousands of such integers in a row, being able to use addc is a huge win (there are superscalar issues with contention on the carry bit as well, but modern CPUs deal pretty well with it). SIMD. Even autovectorizing compilers can only do relatively simple cases, so if you want good SIMD performance it's unfortunately often necessary to write the code directly. Of course you can use intrinsics instead of assembly but once you're at the intrinsics level you're basically writing assembly anyway, just using the compiler as a register allocator and (nominally) instruction scheduler. (I tend to use intrinsics for SIMD simply because the compiler can generate the function prologues and whatnot for me so I can use the same code on Linux, OS X, and Windows without having to deal with ABI issues like function calling conventions, but other than that the SSE intrinsics really aren't very nice - the Altivec ones seem better though I don't have much experience with them). As examples of things a (current day) vectorizing compiler can't figure out, read about bitslicing AES or SIMD error correction - one could imagine a compiler that could analyze algorithms and generate such code, but it feels to me like such a smart compiler is at least 30 years away from existing (at best).

On the other hand, multicore machines and distributed systems have shifted many of the biggest performance wins in the other direction - get an extra 20% speedup writing your inner loops in assembly, or 300% by running them across multiple cores, or 10000% by running them across a cluster of machines. And of course high level optimizations (things like futures, memoization, etc) are often much easier to do in a higher level language like ML or Scala than C or asm, and often can provide a much bigger performance win. So, as always, there are tradeoffs to be made.

第一点不是答案。 即使你从来没有用它编程，我发现至少知道一个汇编指令集是有用的。这是程序员永无止境的追求的一部分，他们想知道得更多，从而变得更好。当你进入一个没有源代码的框架时，它也很有用，至少对正在发生的事情有一个粗略的了解。它还可以帮助您理解JavaByteCode和. net IL，因为它们都类似于汇编程序。

To answer the question when you have a small amount of code or a large amount of time. Most useful for use in embedded chips, where low chip complexity and poor competition in compilers targeting these chips can tip the balance in favour of humans. Also for restricted devices you are often trading off code size/memory size/performance in a way that would be hard to instruct a compiler to do. e.g. I know this user action is not called often so I will have small code size and poor performance, but this other function that look similar is used every second so I will have a larger code size and faster performance. That is the sort of trade off a skilled assembly programmer can use.

我还想补充一点，这里有很多中间地带，您可以用C编译代码并检查生成的程序集，然后更改C代码或调整并作为程序集进行维护。

我的朋友从事微控制器的工作，目前是用于控制小型电动机的芯片。他在低级c和汇编的组合中工作。他曾经告诉我，有一天他在工作中把主循环从48条指令减少到43条。他还面临着各种选择，比如代码已经增长到填满256k芯片，业务需要一个新功能，你呢

删除现有功能 减少部分或全部现有特性的大小，可能会以性能为代价。 提倡改用成本更高、功耗更高、外形更大的更大芯片。

我想补充一点，作为一个商业开发人员，我有很多的投资组合或语言、平台、应用程序类型，我从来没有觉得有必要深入编写程序集。我一直都很感激我所学到的知识。有时会被调试进去。

我知道我已经回答了“为什么我要学习汇编器”这个问题，但我觉得这是一个更重要的问题，而不是什么时候更快。

所以让我们再试一次 你应该考虑组装

致力于底层操作系统功能 在编译器上工作。 工作在一个极其有限的芯片，嵌入式系统等

记住比较你的程序集和生成的编译器，看看哪个更快/更小/更好。

大卫。

尽管C语言“接近”于对8位、16位、32位和64位数据的低级操作，但仍有一些C语言不支持的数学操作通常可以在某些汇编指令集中优雅地执行:

Fixed-point multiplication: The product of two 16-bit numbers is a 32-bit number. But the rules in C says that the product of two 16-bit numbers is a 16-bit number, and the product of two 32-bit numbers is a 32-bit number -- the bottom half in both cases. If you want the top half of a 16x16 multiply or a 32x32 multiply, you have to play games with the compiler. The general method is to cast to a larger-than-necessary bit width, multiply, shift down, and cast back: int16_t x, y; // int16_t is a typedef for "short" // set x and y to something int16_t prod = (int16_t)(((int32_t)x*y)>>16);` In this case the compiler may be smart enough to know that you're really just trying to get the top half of a 16x16 multiply and do the right thing with the machine's native 16x16multiply. Or it may be stupid and require a library call to do the 32x32 multiply that's way overkill because you only need 16 bits of the product -- but the C standard doesn't give you any way to express yourself. Certain bitshifting operations (rotation/carries): // 256-bit array shifted right in its entirety: uint8_t x[32]; for (int i = 32; --i > 0; ) { x[i] = (x[i] >> 1) | (x[i-1] << 7); } x[0] >>= 1; This is not too inelegant in C, but again, unless the compiler is smart enough to realize what you are doing, it's going to do a lot of "unnecessary" work. Many assembly instruction sets allow you to rotate or shift left/right with the result in the carry register, so you could accomplish the above in 34 instructions: load a pointer to the beginning of the array, clear the carry, and perform 32 8-bit right-shifts, using auto-increment on the pointer. For another example, there are linear feedback shift registers (LFSR) that are elegantly performed in assembly: Take a chunk of N bits (8, 16, 32, 64, 128, etc), shift the whole thing right by 1 (see above algorithm), then if the resulting carry is 1 then you XOR in a bit pattern that represents the polynomial.

尽管如此，除非有严重的性能限制，否则我不会求助于这些技术。正如其他人所说，汇编代码比C代码更难记录/调试/测试/维护:性能的提高伴随着一些严重的代价。

编辑:3。溢出检测在汇编中是可能的(在C中不能真正做到)，这使得一些算法更容易。

紧密循环，就像处理图像时一样，因为一张图像可能需要数百万像素。坐下来研究一下如何最好地利用有限的处理器寄存器会有很大的不同。下面是一个真实的例子:

http://danbystrom.se/2008/12/22/optimizing-away-ii/

处理器通常有一些深奥的指令，这些指令对于编译器来说太专业了，但有时汇编程序员可以很好地利用它们。以XLAT指令为例。如果您需要在循环中进行表查找，并且表限制在256字节，那么这非常棒!

更新:哦，当我们谈论一般循环时，最关键的是:编译器通常不知道常见情况下会有多少次迭代!只有程序员知道一个循环会被迭代很多次，因此用一些额外的工作来准备循环是有益的，或者如果它迭代的次数太少，以至于设置实际花费的时间比预期的迭代要长。