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.

Walter Bright的《optimization Immutable and Purity》可能值得一看，它不是一个概要测试，但向您展示了手写和编译器生成ASM之间的区别。Walter Bright写优化编译器，所以值得一看他的其他博客文章。

Actually you can build large scale programs in a large model mode segaments may be restricted to 64kb code but you can write many segaments, people give the argument against ASM as it is an old language and we don't need to preserve memory anymore, If that were the case why would we be packing our PC's with memory, the only Flaw I can find with ASM is that it is more or less Processor based so most programs written for the intel architecture Most likely would not run on An AMD Architecture. As for C being faster than ASM there is no language faster than ASM and ASM can do many thing's C and other HLL's can not do at processor level. ASM is a difficult language to learn but once you learn it no HLL can translate it better than you. If you could only see some of the things HLL's Do to you code, and understand what it is doing, you would wonder why More people don't use ASM and why assembers are no longer being updated ( For general public use anyway). So no C is not faster than ASM. Even experiences C++ programmers still use and write code Chunks in ASM added to there C++ code for speed. Other Languages Also that some people think are obsolete or possibly no good is a myth at times for instance Photoshop is written in Pascal/ASM 1st release of souce has been submitted to the technical history museum, and paintshop pro is written still written in Python,TCL and ASM ... a common denominator of these to "Fast and Great image processors is ASM, although photoshop may have Upgraded to delphi now it is still pascal. and any speed problems are comming from pascal but this is because we like the way programs look and not what they do now days. I would like to make a Photoshop Clone in pure ASM which I have been working on and its comming along rather well. not code,interpret,arange,rewwrite,etc.... Just code and go process complete.

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。

如今，考虑到像英特尔c++这样的编译器对C代码进行了极大的优化，它很难与编译器的输出竞争。

C语言常常需要做一些从汇编编码员的角度看来不必要的事情，这只是因为C标准这么说。

例如，整数提升。如果你想在C语言中移动一个char变量，人们通常会期望代码实际上只做一个比特的移动。

然而，标准强制编译器在移位之前将符号扩展为int，然后将结果截断为char，这可能会使代码复杂化，这取决于目标处理器的架构。