一般来说，FORTRAN比C慢。C可以使用硬件级指针，允许程序员手动优化。FORTRAN(在大多数情况下)不能访问硬件内存寻址黑客。(VAX FORTRAN是另一回事。)我从70年代开始断断续续地使用FORTRAN。(真的)。

然而，从90年代开始，FORTRAN已经发展到包括特定的语言结构，可以优化成内在的并行算法，真正可以在多核处理器上运行。例如，自动矢量化允许多个处理器同时处理数据向量中的每个元素。16个处理器——16个元素向量——处理需要1/16的时间。

在C语言中，您必须管理自己的线程并为多处理仔细设计算法，然后使用一堆API调用来确保并行性正确发生。

在FORTRAN中，您只需要为多处理仔细设计算法。编译器和运行时可以为您处理其余的工作。

您可以阅读一些关于高性能Fortran的内容，但是您会发现许多死链接。你最好阅读并行编程(比如OpenMP.org)以及FORTRAN如何支持并行编程。

是的，在1980年;在2008年?取决于

当我开始专业编程时，Fortran的速度优势正受到挑战。我记得我在Dr. Dobbs上读到过这篇文章，并把这篇文章告诉了年长的程序员——他们都笑了。

所以我对此有两种观点，理论上的和实际的。从理论上讲，今天的Fortran与C/ c++甚至任何允许汇编代码的语言相比，并没有内在的优势。在实践中，今天的Fortran仍然享有围绕优化数值代码而建立的历史和文化遗产的好处。

Up until and including Fortran 77, language design considerations had optimization as a main focus. Due to the state of compiler theory and technology, this often meant restricting features and capability in order to give the compiler the best shot at optimizing the code. A good analogy is to think of Fortran 77 as a professional race car that sacrifices features for speed. These days compilers have gotten better across all languages and features for programmer productivity are more valued. However, there are still places where the people are mainly concerned with speed in scientific computing; these people most likely have inherited code, training and culture from people who themselves were Fortran programmers.

当人们开始谈论代码优化时，会有很多问题，了解这一点的最好方法是潜伏在那些工作是快速编写数字代码的人身上。但是请记住，这种高度敏感的代码通常只占整个代码行的一小部分，而且非常专门:许多Fortran代码就像其他语言中的许多其他代码一样“低效”，优化甚至不应该是此类代码的主要关注点。

要开始了解Fortran的历史和文化，维基百科是一个很好的地方。Fortran维基百科的条目是一流的，我非常感谢那些花时间和精力使它对Fortran社区有价值的人。

(这个答案的缩短版本本可以在Nils开始的优秀帖子中发表评论，但我没有这样做的业力。实际上，如果不是因为这个帖子有实际的信息内容和分享，而不是激烈的争吵和语言偏见，我可能根本不会写任何东西，这是我对这个主题的主要经验。我不知所措，不得不分享这份爱。)

这两种语言具有相似的特性集。性能上的差异来自Fortran不允许混淆的事实，除非使用了EQUIVALENCE语句。任何有别名的代码都不是有效的Fortran，但是它是由程序员而不是编译器来检测这些错误的。因此，Fortran编译器忽略了可能的内存指针别名，并允许它们生成更有效的代码。看一下C语言中的这个小例子:

void transform (float *output, float const * input, float const * matrix, int *n)
{
    int i;
    for (i=0; i<*n; i++)
    {
        float x = input[i*2+0];
        float y = input[i*2+1];
        output[i*2+0] = matrix[0] * x + matrix[1] * y;
        output[i*2+1] = matrix[2] * x + matrix[3] * y;
    }
}

这个函数在优化后会比Fortran函数运行得慢。为什么如此?如果你在输出数组中写入值，你可能会改变矩阵的值。毕竟，指针可以重叠并指向相同的内存块(包括int指针!)C编译器被迫从内存中重新加载所有计算的四个矩阵值。

在Fortran中，编译器只加载一次矩阵值，并将它们存储在寄存器中。它可以这样做是因为Fortran编译器假定指针/数组在内存中不重叠。

Fortunately, the restrict keyword and strict-aliasing have been introduced to the C99 standard to address this problem. It's well supported in most C++ compilers these days as well. The keyword allows you to give the compiler a hint that the programmer promises that a pointer does not alias with any other pointer. The strict-aliasing means that the programmer promises that pointers of different type will never overlap, for example a double* will not overlap with an int* (with the specific exception that char* and void* can overlap with anything).

If you use them you will get the same speed from C and Fortran. However, the ability to use the restrict keyword only with performance critical functions means that C (and C++) programs are much safer and easier to write. For example, consider the invalid Fortran code: CALL TRANSFORM(A(1, 30), A(2, 31), A(3, 32), 30), which most Fortran compilers will happily compile without any warning but introduces a bug that only shows up on some compilers, on some hardware and with some optimization options.

Fortran速度更快有几个原因。然而，它们的重要性是如此无关紧要，或者可以通过任何方式解决，所以它不应该是重要的。现在使用Fortran的主要原因是维护或扩展遗留应用程序。

PURE and ELEMENTAL keywords on functions. These are functions that have no side effects. This allows optimizations in certain cases where the compiler knows the same function will be called with the same values. Note: GCC implements "pure" as an extension to the language. Other compilers may as well. Inter-module analysis can also perform this optimization but it is difficult. standard set of functions that deal with arrays, not individual elements. Stuff like sin(), log(), sqrt() take arrays instead of scalars. This makes it easier to optimize the routine. Auto-vectorization gives the same benefits in most cases if these functions are inline or builtins Builtin complex type. In theory this could allow the compiler to reorder or eliminate certain instructions in certain cases, but likely you'd see the same benefit with the struct { double re; double im; }; idiom used in C. It makes for faster development though as operators work on complex types in Fortran.

大多数帖子已经提出了令人信服的论点，所以我只是在另一个方面加上众所周知的2美分。

在处理能力方面，fortran更快或更慢是有其重要性的，但如果用fortran开发一些东西需要5倍多的时间，因为:

it lacks any good library for tasks different from pure number crunching it lack any decent tool for documentation and unit testing it's a language with very low expressivity, skyrocketing the number of lines of code. it has a very poor handling of strings it has an inane amount of issues among different compilers and architectures driving you crazy. it has a very poor IO strategy (READ/WRITE of sequential files. Yes, random access files exist but did you ever see them used?) it does not encourage good development practices, modularization. effective lack of a fully standard, fully compliant opensource compiler (both gfortran and g95 do not support everything) very poor interoperability with C (mangling: one underscore, two underscores, no underscore, in general one underscore but two if there's another underscore. and just let not delve into COMMON blocks...)

那么这个问题就无关紧要了。如果某样东西很慢，大多数时候你无法在给定的限制范围内改进它。如果你想要更快，改变算法。最后，使用电脑的时间很便宜。人类的时间不是。珍惜减少人类时间的选择。如果它增加了使用电脑的时间，无论如何它都是有成本效益的。

This is more than somewhat subjective, because it gets into the quality of compilers and such more than anything else. However, to more directly answer your question, speaking from a language/compiler standpoint there is nothing about Fortran over C that is going to make it inherently faster or better than C. If you are doing heavy math operations, it will come down to the quality of the compiler, the skill of the programmer in each language and the intrinsic math support libraries that support those operations to ultimately determine which is going to be faster for a given implementation.

编辑:@Nils等人提出了一个很好的观点，即C语言中指针使用的差异，以及可能存在的别名，这可能会使C语言中最简单的实现变慢。然而，在C99中有一些方法可以解决这个问题，比如通过编译器优化标志和/或C语言的实际编写方式。这在@Nils的回答和随后的评论中有很好的介绍。