CP/M-86版本的PolyPascal (Turbo Pascal的兄弟)的一个可能性是用机器语言例程取代“使用生物将字符输出到屏幕上”的功能，本质上是给定x、y和字符串放在那里。

这使得更新屏幕的速度比以前快得多!

二进制文件中有足够的空间来嵌入机器代码(几百个字节)，也有其他的东西，所以尽可能多地压缩是必要的。

事实证明，由于屏幕是80x25，这两个坐标都可以容纳每个字节，所以都可以容纳两个字节的单词。这允许在更少的字节内完成所需的计算，因为单个添加可以同时操作两个值。

据我所知，没有C编译器可以在一个寄存器中合并多个值，对它们执行SIMD指令，然后再将它们分开(而且我不认为机器指令会更短)。

我曾经和一个人一起工作过，他说“如果编译器笨到不能弄清楚你要做什么，并且不能优化它，那么你的编译器就坏了，是时候换一个新的了”。我确信在某些情况下汇编程序会打败你的C代码，但是如果你发现自己经常使用汇编程序来“赢得”编译器，那么你的编译器就完蛋了。

对于编写试图强制查询计划器执行操作的“优化”SQL也是如此。如果您发现自己重新安排查询以让计划器执行您想要的操作，那么您的查询计划器就完蛋了——请更换一个新的计划器。

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.

在历史上插话。

当我还年轻的时候(20世纪70年代)，根据我的经验，汇编是很重要的，更重要的是代码的大小，而不是代码的速度。

如果一个高级语言的模块是1300字节的代码，但该模块的汇编版本是300字节，那么当您试图将应用程序装入16K或32K的内存时，这1K字节就非常重要。

那时候编译器还不是很好。

在老式的Fortran中

X = (Y - Z)
IF (X .LT. 0) THEN
 ... do something
ENDIF

当时的编译器在X上执行了一个SUBTRACT指令，然后是一个TEST指令。 在汇编程序中，您只需在减法之后检查条件代码(LT零，零，GT零)。

对于现代系统和编译器来说，这些都不是问题。

我认为理解编译器在做什么仍然很重要。 当您使用高级语言编写代码时，您应该了解什么允许或阻止编译器执行循环展开。

当编译器执行“类似分支”的操作时，使用管道内衬和包含条件的前瞻计算。

当执行高级语言不允许的事情时，仍然需要汇编程序，比如读取或写入处理器特定的寄存器。

但在很大程度上，普通程序员不再需要它，除非对代码如何编译和执行有基本的了解。

我已经阅读了所有的答案(超过30个)，并没有找到一个简单的原因:如果你读过并练习过Intel®64和IA-32架构优化参考手册，汇编程序比C更快，所以汇编程序可能更慢的原因是编写这种慢汇编程序的人没有阅读优化手册。

In the good old days of Intel 80286, each instruction was executed at a fixed count of CPU cycles. Still, since Pentium Pro, released in 1995, Intel processors became superscalar, utilizing Complex Pipelining: Out-of-Order Execution & Register Renaming. Before that, on Pentium, produced in 1993, there were U and V pipelines. Therefore, Pentium introduced dual pipelines that could execute two simple instructions at one clock cycle if they didn't depend on one another. However, this was nothing compared with the Out-of-Order Execution & Register Renaming that appeared in Pentium Pro. This approach introduced in Pentium Pro is practically the same nowadays on most recent Intel processors.

Let me explain the Out-of-Order Execution in a few words. The fastest code is where instructions do not depend on previous results, e.g., you should always clear whole registers (by movzx) to remove dependency from previous values of the registers you are working with, so they may be renamed internally by the CPU to allow instruction execute in parallel or in a different order. Or, on some processors, false dependency may exist that may also slow things down, like false dependency on Pentium 4 for inc/dec, so you may wish to use add eax, 1 instead or inc eax to remove dependency on the previous state of the flags.

如果时间允许，您可以阅读更多无序执行和注册重命名。因特网上有大量的信息。

There are also many other essential issues like branch prediction, number of load and store units, number of gates that execute micro-ops, memory cache coherence protocols, etc., but the crucial thing to consider is the Out-of-Order Execution. Most people are simply not aware of the Out-of-Order Execution. Therefore, they write their assembly programs like for 80286, expecting their instructions will take a fixed time to execute regardless of the context. At the same time, C compilers are aware of the Out-of-Order Execution and generate the code correctly. That's why the code of such uninformed people is slower, but if you become knowledgeable, your code will be faster.

除了乱序执行之外，还有很多优化技巧和技巧。请阅读上面提到的优化手册:-)

However, assembly language has its own drawbacks when it comes to optimization. According to Peter Cordes (see the comment below), some of the optimizations compilers do would be unmaintainable for large code-bases in hand-written assembly. For example, suppose you write in assembly. In that case, you need to completely change an inline function (an assembly macro) when it inlines into a function that calls it with some arguments being constants. At the same time, a C compiler makes its job a lot simpler—and inlining the same code in different ways into different call sites. There is a limit to what you can do with assembly macros. So to get the same benefit, you'd have to manually optimize the same logic in each place to match the constants and available registers you have.

GCC已经成为广泛使用的编译器。它的优化通常不是很好。比编写汇编程序的普通程序员好得多，但就实际性能而言，并没有那么好。有些编译器产生的代码简直令人难以置信。所以一般来说，有很多地方你可以进入编译器的输出，调整汇编器的性能，和/或简单地从头重写例程。