只要有合适的程序员，汇编程序总是可以比C程序快(至少稍微快一点)。如果不能从汇编器中取出至少一条指令，则很难创建一个C程序。

不需要给出任何具体的示例或分析器证据，当您比编译器知道的更多时，您可以编写比编译器更好的汇编程序。

In the general case, a modern C compiler knows much more about how to optimize the code in question: it knows how the processor pipeline works, it can try to reorder instructions quicker than a human can, and so on - it's basically the same as a computer being as good as or better than the best human player for boardgames, etc. simply because it can make searches within the problem space faster than most humans. Although you theoretically can perform as well as the computer in a specific case, you certainly can't do it at the same speed, making it infeasible for more than a few cases (i.e. the compiler will most certainly outperform you if you try to write more than a few routines in assembler).

另一方面，有些情况下编译器没有那么多的信息——我想说主要是在使用不同形式的外部硬件时，编译器不知道这些信息。主要的例子可能是设备驱动程序，其中汇编程序结合人类对相关硬件的熟悉知识可以产生比C编译器更好的结果。

其他人提到了特殊用途指令，这就是我在上面一段中所说的——编译器可能对这些指令了解有限或根本不了解，这使得人类可以编写更快的代码。

http://cr.yp.to/qhasm.html有很多例子。

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.

The question is a bit misleading. The answer is there in your post itself. It is always possible to write assembly solution for a particular problem which executes faster than any generated by a compiler. The thing is you need to be an expert in assembly to overcome the limitations of a compiler. An experienced assembly programmer can write programs in any HLL which performs faster than one written by an inexperienced. The truth is you can always write assembly programs executing faster than one generated by a compiler.

在处理器速度以MHz为单位，屏幕尺寸低于100万像素的时代，一个众所周知的更快显示的技巧是展开循环:为屏幕的每个扫描行写操作。它避免了维护循环索引的开销!再加上检测屏幕刷新，它非常有效。 这是C编译器不会做的事情……(虽然通常可以在速度优化和规模优化之间进行选择，但我认为前者使用了一些类似的技巧。)

我知道有些人喜欢用汇编语言编写Windows应用程序。他们声称他们更快(很难证明)和更小(确实如此!)。 显然，虽然这样做很有趣，但可能会浪费时间(当然，学习目的除外!)，特别是对于GUI操作…… 现在，也许某些操作(比如在文件中搜索字符串)可以通过精心编写的汇编代码进行优化。