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。

I think the key point in favor of Fortran is that it is a language slightly more suited for expressing vector- and array-based math. The pointer analysis issue pointed out above is real in practice, since portable code cannot really assume that you can tell a compiler something. There is ALWAYS an advantage to expression computaitons in a manner closer to how the domain looks. C does not really have arrays at all, if you look closely, just something that kind of behaves like it. Fortran has real arrawys. Which makes it easier to compile for certain types of algorithms especially for parallel machines.

在运行时系统和调用约定等方面，C语言和现代的Fortran非常相似，很难看出有什么不同。注意，这里的C实际上是基础C: c++是一个完全不同的问题，具有非常不同的性能特征。

我将Fortran、C和c++的速度与netlib中的经典Levine-Callahan-Dongarra基准进行了比较。使用OpenMP的多语言版本是 http://sites.google.com/site/tprincesite/levine-callahan-dongarra-vectors C语言更丑陋，因为它一开始是自动翻译，加上某些编译器的限制和pragmas插入。 c++就是在适用的地方使用STL模板的C。在我看来，STL在是否能提高可维护性方面好坏参半。

为了了解自动函数内联在多大程度上改进了优化，只需要进行很少的练习，因为示例基于传统的Fortran实践，其中很少依赖内联。

到目前为止使用最广泛的C/ c++编译器缺乏自动向量化，而这些基准测试严重依赖于此。

关于这之前的帖子:在Fortran中使用括号来指示更快或更准确的求值顺序的例子有两个。已知的C编译器没有在不禁用更重要的优化的情况下观察括号的选项。

我是一个业余程序员，在这两种语言上我都是“平均”。 我发现编写快速Fortran代码比编写C(或c++)代码更容易。Fortran和C都是“历史悠久”的语言(按照今天的标准)，被大量使用，并且很好地支持免费和商业编译器。

我不知道这是否是一个历史事实，但Fortran感觉它是为并行/分布式/向量化/多核化而构建的。今天，当我们谈论速度时，它几乎是“标准度量”:“它能缩放吗?”

对于纯粹的cpu计算，我喜欢Fortran。对于任何与IO相关的东西，我发现使用c更容易(无论如何这两种情况都很困难)。

当然，对于并行计算密集型代码，你可能需要使用GPU。C和Fortran都有很多或多或少很好地集成了CUDA/OpenCL接口(现在还有OpenACC)。

我比较客观的回答是:如果你对这两种语言都同样了解或不了解，那么我认为Fortran更快，因为我发现用Fortran写并行/分布式代码比用c更容易(一旦你明白你可以写“自由形式”Fortran，而不仅仅是严格的F77代码)

Here is a 2nd answer for those willing to downvote me because they don't like the 1st answer : Both language have the features required to write high-performance code. So it's dependent of the algorithm you're implementing (cpu intensive ? io intensive ? memory intensive?), the hardware (single cpu ? multi-core ? distribute supercomputer ? GPGPU ? FPGA ?), your skill and ultimately the compiler itself. Both C and Fortran have awesome compiler. (i'm seriously amazed by how advanced Fortran compilers are but so are C compilers).

PS:我很高兴你特别排除了库，因为我有很多关于Fortran GUI库的不好的东西要说。：）

Fortran traditionally doesn't set options such as -fp:strict (which ifort requires to enable some of the features in USE IEEE_arithmetic, a part of f2003 standard). Intel C++ also doesn't set -fp:strict as a default, but that is required for ERRNO handling, for example, and other C++ compilers don't make it convenient to turn off ERRNO or gain optimizations such as simd reduction. gcc and g++ have required me to set up Makefile to avoid using the dangerous combination -O3 -ffast-math -fopenmp -march=native. Other than these issues, this question about relative performance gets more nit-picky and dependent on local rules about choice of compilers and options.

I was doing some extensive mathematics with FORTRAN and C for a couple of years. From my own experience I can tell that FORTRAN is sometimes really better than C but not for its speed (one can make C perform as fast as FORTRAN by using appropriate coding style) but rather because of very well optimized libraries like LAPACK (which can, however, be called from C code as well, either linking against LAPACK directly or using the LAPACKE interface for C), and because of great parallelization. On my opinion, FORTRAN is really awkward to work with, and its advantages are not good enough to cancel that drawback, so now I am using C+GSL to do calculations.