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.

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.

Fortran和C语言在特定目的上并没有哪一种语言比另一种更快。对于每种语言的特定编译器，有些编译器比其他编译器更适合某些任务。

多年来，Fortran编译器一直存在，它可以对你的数字例程施黑魔法，使许多重要的计算变得异常快速。当代的C编译器无法做到这一点。因此，在Fortran中出现了许多伟大的代码库。如果您想要使用这些经过良好测试的、成熟的、出色的库，就需要使用Fortran编译器。

我的非正式观察表明，如今人们用任何古老的语言来编码他们繁重的计算内容，如果这需要一段时间，他们就会在一些廉价的计算集群上找到时间。摩尔定律让我们所有人都成了傻瓜。

Fortran可以非常方便地处理数组，特别是多维数组。在Fortran中对多维数组元素进行切片比在C/ c++中容易得多。c++现在有库可以做这项工作，比如Boost或Eigen，但它们毕竟是外部库。在Fortran中，这些函数是固有的。

对于开发来说，Fortran是更快还是更方便主要取决于您需要完成的工作。作为地球物理的科学计算人员，我用Fortran(我指的是现代Fortran， >=F90)进行了大部分计算。

我还没有听说过Fortan比C快得多，但是可以想象在某些情况下它会更快。关键不在于语言特征的存在，而在于那些(通常)不存在的特征。

一个例子是C指针。C指针几乎到处都在使用，但指针的问题是编译器通常无法判断它们是否指向同一个数组的不同部分。

例如，如果你写了一个strcpy例程，看起来像这样:

strcpy(char *d, const char* s)
{
  while(*d++ = *s++);
}

编译器必须在d和s可能是重叠数组的假设下工作。所以当数组重叠时，它不能执行会产生不同结果的优化。正如您所期望的，这在很大程度上限制了可以执行的优化类型。

[我应该注意到，C99有一个“restrict”关键字，显式地告诉编译器指针不重叠。还要注意，Fortran也有指针，语义不同于C语言，但指针不像C语言那样无处不在。

但是回到C与Fortran的问题上，可以想象，Fortran编译器能够执行一些对于(直接编写的)C程序可能无法实现的优化。所以我不会对这种说法感到太惊讶。不过，我确实希望性能差异不会太大。(~ 5 - 10%)

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.