这不仅仅是堆栈分配更快。您还可以在使用堆栈变量方面获得很多好处。它们有更好的参考位置。最后，折价也便宜得多。

堆栈要快得多。它在大多数架构上只使用一条指令，在大多数情况下，例如在x86上:

sub esp, 0x10

(将堆栈指针向下移动0x10个字节，从而“分配”这些字节供变量使用。)

当然，堆栈的大小是非常非常有限的，因为你很快就会发现你是否过度使用堆栈分配或尝试进行递归:-)

同样，没有什么理由去优化那些不需要它的代码的性能，比如通过分析来证明。“过早的优化”通常会导致比它本身价值更多的问题。

我的经验法则:如果我知道我将在编译时需要一些数据，并且它的大小在几百字节以下，我就会对它进行堆栈分配。否则我进行堆分配。

我不认为堆栈分配和堆分配通常是可以互换的。我也希望它们的性能都足以用于一般用途。

我强烈推荐小件物品，哪种更适合分配范围。对于较大的项，堆可能是必要的。

在有多个线程的32位操作系统上，堆栈通常是相当有限的(尽管通常至少是几mb)，因为需要分割地址空间，迟早一个线程堆栈会碰到另一个线程堆栈。在单线程系统(至少是Linux glibc单线程)上，限制要小得多，因为堆栈可以不断增长。

在64位操作系统上，有足够的地址空间使线程堆栈相当大。

c++语言特有的关注点

首先，c++中没有所谓的“堆栈”或“堆”分配。如果你谈论的是块作用域中的自动对象，它们甚至没有被“分配”。(顺便说一下，C语言中的自动存储时间肯定与“分配”不一样;后者在c++中是“动态的”。)动态分配的内存在自由存储区上，而不一定在“堆”上，尽管后者通常是(默认的)实现。

Although as per the abstract machine semantic rules, automatic objects still occupy memory, a conforming C++ implementation is allowed to ignore this fact when it can prove this does not matter (when it does not change the observable behavior of the program). This permission is granted by the as-if rule in ISO C++, which is also the general clause enabling the usual optimizations (and there is also an almost same rule in ISO C). Besides the as-if rule, ISO C++ also has copy elision rules to allow omission of specific creations of objects. The constructor and destructor calls involved are thereby omitted. As a result, the automatic objects (if any) in these constructors and destructors are also eliminated, compared to naive abstract semantics implied by the source code.

另一方面，免费商店的分配绝对是设计上的“分配”。在ISO c++规则下，这样的分配可以通过调用分配函数来实现。然而，自ISO c++ 14以来，有一个新的(非as-if)规则允许在特定情况下合并全局分配函数(即::operator new)调用。因此，部分动态分配操作也可以像自动对象一样是无操作的。

分配函数用于分配内存资源。可以使用分配器根据分配进一步分配对象。对于自动对象，它们是直接呈现的——尽管底层内存可以被访问，并被用来为其他对象提供内存(通过放置new)，但这作为自由存储没有太大意义，因为没有办法将资源移动到其他地方。

所有其他问题都超出了c++的范围。尽管如此，它们仍然是重要的。

c++的实现

C++ does not expose reified activation records or some sorts of first-class continuations (e.g. by the famous call/cc), there is no way to directly manipulate the activation record frames - where the implementation need to place the automatic objects to. Once there is no (non-portable) interoperations with the underlying implementation ("native" non-portable code, such as inline assembly code), an omission of the underlying allocation of the frames can be quite trivial. For example, when the called function is inlined, the frames can be effectively merged into others, so there is no way to show what is the "allocation".

However, once interops are respected, things are getting complex. A typical implementation of C++ will expose the ability of interop on ISA (instruction-set architecture) with some calling conventions as the binary boundary shared with the native (ISA-level machine) code. This would be explicitly costly, notably, when maintaining the stack pointer, which is often directly held by an ISA-level register (with probably specific machine instructions to access). The stack pointer indicates the boundary of the top frame of the (currently active) function call. When a function call is entered, a new frame is needed and the stack pointer is added or subtracted (depending on the convention of ISA) by a value not less than the required frame size. The frame is then said allocated when the stack pointer after the operations. Parameters of functions may be passed onto the stack frame as well, depending on the calling convention used for the call. The frame can hold the memory of automatic objects (probably including the parameters) specified by the C++ source code. In the sense of such implementations, these objects are "allocated". When the control exits the function call, the frame is no longer needed, it is usually released by restoring the stack pointer back to the state before the call (saved previously according to the calling convention). This can be viewed as "deallocation". These operations make the activation record effectively a LIFO data structure, so it is often called "the (call) stack". The stack pointer effectively indicates the top position of the stack.

Because most C++ implementations (particularly the ones targeting ISA-level native code and using the assembly language as its immediate output) use similar strategies like this, such a confusing "allocation" scheme is popular. Such allocations (as well as deallocations) do spend machine cycles, and it can be expensive when the (non-optimized) calls occur frequently, even though modern CPU microarchitectures can have complex optimizations implemented by hardware for the common code pattern (like using a stack engine in implementing PUSH/POP instructions).

But anyway, in general, it is true that the cost of stack frame allocation is significantly less than a call to an allocation function operating the free store (unless it is totally optimized away), which itself can have hundreds of (if not millions of :-) operations to maintain the stack pointer and other states. Allocation functions are typically based on API provided by the hosted environment (e.g. runtime provided by the OS). Different to the purpose of holding automatic objects for functions calls, such allocations are general-purpose, so they will not have frame structure like a stack. Traditionally, they allocate space from the pool storage called the heap (or several heaps). Different from the "stack", the concept "heap" here does not indicate the data structure being used; it is derived from early language implementations decades ago. (BTW, the call stack is usually allocated with fixed or user-specified size from the heap by the environment in program/thread startup.) The nature of use cases makes allocations and deallocations from a heap far more complicated (than pushing/poppoing of stack frames), and hardly possible to be directly optimized by hardware.

对内存访问的影响

The usual stack allocation always puts the new frame on the top, so it has a quite good locality. This is friendly to the cache. OTOH, memory allocated randomly in the free store has no such property. Since ISO C++17, there are pool resource templates provided by <memory_resource>. The direct purpose of such an interface is to allow the results of consecutive allocations being close together in memory. This acknowledges the fact that this strategy is generally good for performance with contemporary implementations, e.g. being friendly to cache in modern architectures. This is about the performance of access rather than allocation, though.

并发性

Expectation of concurrent access to memory can have different effects between the stack and heaps. A call stack is usually exclusively owned by one thread of execution in a typical C++ implementation. OTOH, heaps are often shared among the threads in a process. For such heaps, the allocation and deallocation functions have to protect the shared internal administrative data structure from the data race. As a result, heap allocations and deallocations may have additional overhead due to internal synchronization operations.

空间效率

由于用例和内部数据结构的性质，堆可能会受到内部内存碎片的影响，而堆栈则不会。这对内存分配的性能没有直接影响，但在虚拟内存的系统中，低空间效率可能会降低内存访问的整体性能。当HDD被用作物理内存交换时，这种情况尤其糟糕。它会导致相当长的延迟——有时是数十亿个周期。

堆栈分配的限制

尽管在现实中，堆栈分配在性能上通常优于堆分配，但这并不意味着堆栈分配总是可以取代堆分配。

首先，在ISO c++中无法以可移植的方式在运行时指定大小的堆栈上分配空间。诸如alloca和g++的VLA(变长数组)等实现提供了扩展，但是有理由避免使用它们。(IIRC, Linux源代码最近删除了VLA的使用)(还要注意ISO C99确实有强制的VLA，但ISO C11是可选的支持。)

Second, there is no reliable and portable way to detect stack space exhaustion. This is often called stack overflow (hmm, the etymology of this site), but probably more accurately, stack overrun. In reality, this often causes invalid memory access, and the state of the program is then corrupted (... or maybe worse, a security hole). In fact, ISO C++ has no concept of "the stack" and makes it undefined behavior when the resource is exhausted. Be cautious about how much room should be left for automatic objects.

如果堆栈空间用完，则堆栈中分配的对象太多，这可能是由于过多的活动函数调用或不恰当地使用自动对象造成的。这种情况可能表明存在错误，例如没有正确退出条件的递归函数调用。

Nevertheless, deep recursive calls are sometimes desired. In implementations of languages requiring support of unbound active calls (where the call depth only limited by total memory), it is impossible to use the (contemporary) native call stack directly as the target language activation record like typical C++ implementations. To work around the problem, alternative ways of the construction of activation records are needed. For example, SML/NJ explicitly allocates frames on the heap and uses cactus stacks. The complicated allocation of such activation record frames is usually not as fast as the call stack frames. However, if such languages are implemented further with the guarantee of proper tail recursion, the direct stack allocation in the object language (that is, the "object" in the language does not stored as references, but native primitive values which can be one-to-one mapped to unshared C++ objects) is even more complicated with more performance penalty in general. When using C++ to implement such languages, it is difficult to estimate the performance impacts.

关于这种优化有一个普遍的观点。

您得到的优化与程序计数器实际在该代码中的时间成正比。

如果您对程序计数器进行采样，您将发现它在哪里花费时间，这通常是在代码的一小部分，并且通常是在您无法控制的库例程中。

只有当你发现在对象的堆分配上花费了大量时间时，才会明显地更快地进行堆栈分配。

堆栈分配是一对指令，而我所知道的最快的rtos堆分配器(TLSF)平均使用150条指令。此外，堆栈分配不需要锁，因为它们使用线程本地存储，这是另一个巨大的性能优势。因此，堆栈分配可以快2-3个数量级，这取决于您的多线程环境有多严重。

通常，如果关心性能，堆分配是最后的选择。一个可行的中间选项可以是一个固定池分配器，它也只有几个指令，每次分配开销很小，所以它非常适合固定大小的小对象。缺点是它只适用于固定大小的对象，本质上不是线程安全的，并且有块碎片问题。