这都是时间和努力的问题。

给予无限的时间和努力:

汇编程序比用C语言编写的程序要快。 C程序将比用c++编写的程序更快。

固定的:给定一定的时间和努力:

c++程序比用C编写的程序要快。 C语言的程序比用汇编语言编写的程序要快。

为什么?因为你做的抽象越多，你就可以花更多的时间来优化真正重要的代码关键部分。这里的几个假设是，一个开发人员对这三种语言都有同样的能力，你不关心二进制大小、内存使用情况等。

每种抽象都有其成本效益，但应该使代码更容易、更快地编写。

我猜你忘了汇编语言也是一种语言:)

但是说真的，只有当程序员知道自己在做什么的时候，C程序才会更快。你可以很容易地编写一个C程序，它比用其他语言编写的程序运行得更慢。

C语言之所以更快，是因为它就是这样设计的。它允许你做很多“低级”的事情，帮助编译器优化代码。或者，我们可以说，你程序员负责优化代码。但这通常相当棘手，而且容易出错。

其他语言，就像前面提到的其他语言一样，更关注程序员的生产力。人们普遍认为程序员的时间比机器的时间要昂贵得多(即使在过去)。因此，尽量减少程序员花在编写和调试程序上的时间，而不是减少程序的运行时间，是很有意义的。为了做到这一点，您将牺牲一些可以使程序更快的事情，因为许多事情都是自动化的。

里面有很多问题——大部分是我没有资格回答的问题。但对于最后一个:

有什么能阻止其他语言编译成运行速度和C一样快的二进制呢?

一句话，抽象。

C语言只比机器语言高出一到两个抽象层次。Java和. net语言距离汇编程序至少有3个抽象级别。Python和Ruby我不太确定。

通常，程序员的玩具越多(复杂的数据类型等)，你离机器语言的距离就越远，需要做的翻译就越多。

我在这里和那里都偏离了，但这是基本的要点。

更新-------这篇文章有一些很好的评论，有更多的细节。

撇开诸如热点优化、预编译元算法和各种形式的并行等高级优化技术不提，语言的基本速度与支持通常在内部循环中指定的操作所需的隐含的幕后复杂性密切相关。

也许最明显的方法是对间接内存引用进行有效性检查——比如检查指针是否为空，检查索引是否符合数组边界。大多数高级语言隐式地执行这些检查，但C不这样做。然而，这并不一定是这些其他语言的基本限制——一个足够聪明的编译器可能能够通过某种形式的循环不变代码运动，从算法的内部循环中删除这些检查。

C语言(在类似程度上与c++密切相关)更基本的优势是严重依赖基于堆栈的内存分配，这本质上是快速的分配、回收和访问。在C(和c++)中，主调用堆栈可用于分配原语、数组和聚合(结构/类)。

虽然C语言确实提供了动态分配任意大小和生命周期的内存的能力(使用所谓的“堆”)，但默认情况下是避免这样做的(而是使用堆栈)。

诱人的是，有时可以在其他编程语言的运行时环境中复制C内存分配策略。asm.js已经证明了这一点，它允许用C或c++编写的代码被翻译成JavaScript的子集，并以接近本机的速度安全地运行在web浏览器环境中。

As somewhat of an aside, another area where C and C++ outshine most other languages for speed is the ability to seamlessly integrate with native machine instruction sets. A notable example of this is the (compiler and platform dependent) availability of SIMD intrinsics which support the construction of custom algorithms that take advantage of the now nearly ubiquitous parallel processing hardware -- while still utilizing the data allocation abstractions provided by the language (lower-level register allocation is managed by the compiler).

在过去，只有两种类型的语言:编译型和解释型。

编译语言利用“编译器”读取语言语法并将其转换为相同的汇编语言代码，这可以直接在CPU上进行。解释型语言使用了几种不同的方案，但从本质上讲，语言语法被转换成一种中间形式，然后在“解释器”(用于执行代码的环境)中运行。

因此，在某种意义上，在代码和机器之间存在另一个“层”——解释器。而且，在计算机中，越多就意味着使用更多的资源。翻译速度较慢，因为他们必须执行更多的操作。

More recently, we've seen more hybrid languages like Java, that employ both a compiler and an interpreter to make them work. It's complicated, but a JVM is faster, more sophisticated and way more optimized than the old interpreters, so it stands a much better change of performing (over time) closer to just straight compiled code. Of course, the newer compilers also have more fancy optimizing tricks so they tend to generate way better code than they used to as well. But most optimizations, most often (although not always) make some type of trade-off such that they are not always faster in all circumstances. Like everything else, nothing comes for free, so the optimizers must get their boast from somewhere (although often times it using compile-time CPU to save runtime CPU).

Getting back to C, it is a simple language, that can be compiled into fairly optimized assembly and then run directly on the target machine. In C, if you increment an integer, it's more than likely that it is only one assembler step in the CPU, in Java however, it could end up being a lot more than that (and could include a bit of garbage collection as well :-) C offers you an abstraction that is way closer to the machine (assembler is the closest), but you end up having to do way more work to get it going and it is not as protected, easy to use or error friendly. Most other languages give you a higher abstraction and take care of more of the underlying details for you, but in exchange for their advanced functionality they require more resources to run. As you generalize some solutions, you have to handle a broader range of computing, which often requires more resources.

保罗。

这实际上是一个长期存在的谎言。虽然C程序确实经常更快，但情况并非总是如此，特别是当C程序员不太擅长它的时候。

人们往往会忘记的一个明显的漏洞是，当程序必须为某种IO阻塞时，比如任何GUI程序中的用户输入。在这些情况下，使用什么语言并不重要，因为您受到数据传入速度的限制，而不是处理数据的速度。在这种情况下，不管你使用的是C、Java、c#甚至Perl;你不能比数据进入的速度更快。

The other major thing is that using garbage collection and not using proper pointers allows the virtual machine to make a number of optimizations not available in other languages. For instance, the JVM is capable of moving objects around on the heap to defragment it. This makes future allocations much faster since the next index can simply be used rather than looking it up in a table. Modern JVMs also don't have to actually deallocate memory; instead, they just move the live objects around when they GC and the spent memory from the dead objects is recovered essentially for free.

This also brings up an interesting point about C and even more so in C++. There is something of a design philosophy of "If you don't need it, you don't pay for it." The problem is that if you do want it, you end up paying through the nose for it. For instance, the vtable implementation in Java tends to be a lot better than C++ implementations, so virtual function calls are a lot faster. On the other hand, you have no choice but to use virtual functions in Java and they still cost something, but in programs that use a lot of virtual functions, the reduced cost adds up.