One example of I time I have used these was working with very resource constrained embedded systems. Lets say you have 2k of ram free and your program has to use some of that memory. You need to store say 4-5 sequences somewhere that's not on the stack and additionally you need to have very precise access over where these things get stored, this is a situation where you might want to write your own allocator. The default implementations can fragment the memory, this might be unacceptable if you don't have enough memory and cannot restart your program.

One project I was working on was using AVR-GCC on some low powered chips. We had to store 8 sequences of variable length but with a known maximum. The standard library implementation of the memory management is a thin wrapper around malloc/free which keeps track of where to place items with by prepending every allocated block of memory with a pointer to just past the end of that allocated piece of memory. When allocating a new piece of memory the standard allocator has to walk over each of the pieces of memory to find the next block that is available where the requested size of memory will fit. On a desktop platform this would be very fast for this few items but you have to keep in mind that some of these microcontrollers are very slow and primitive in comparison. Additionally the memory fragmentation issue was a massive problem that meant we really had no choice but to take a different approach.

So what we did was to implement our own memory pool. Each block of memory was big enough to fit the largest sequence we would need in it. This allocated fixed sized blocks of memory ahead of time and marked which blocks of memory were currently in use. We did this by keeping one 8 bit integer where each bit represented if a certain block was used. We traded off memory usage here for attempting to make the whole process faster, which in our case was justified as we were pushing this microcontroller chip close to it's maximum processing capacity.

在嵌入式系统上下文中，我还可以看到编写自己的自定义分配器的其他情况，例如，如果序列的内存不在主ram中，而在这些平台上可能经常出现这种情况。

我正在使用一个MySQL存储引擎，它的代码使用c++。我们使用一个自定义分配器来使用MySQL内存系统，而不是与MySQL竞争内存。它允许我们确保我们使用的内存是用户配置MySQL使用的内存，而不是“额外的”。

我正在使用一个自定义分配器来计算程序的一部分中的分配/释放的数量，并测量它需要多长时间。还有其他方法可以达到这个目的，但这个方法对我来说非常方便。特别有用的是，我只能对容器的一个子集使用自定义分配器。

自定义分配器是在释放内存之前安全地擦除内存的合理方法。

template <class T>
class allocator
{
public:
    using value_type    = T;

    allocator() noexcept {}
    template <class U> allocator(allocator<U> const&) noexcept {}

    value_type*  // Use pointer if pointer is not a value_type*
    allocate(std::size_t n)
    {
        return static_cast<value_type*>(::operator new (n*sizeof(value_type)));
    }

    void
    deallocate(value_type* p, std::size_t) noexcept  // Use pointer if pointer is not a value_type*
    {
        OPENSSL_cleanse(p, n);
        ::operator delete(p);
    }
};
template <class T, class U>
bool
operator==(allocator<T> const&, allocator<U> const&) noexcept
{
    return true;
}
template <class T, class U>
bool
operator!=(allocator<T> const& x, allocator<U> const& y) noexcept
{
    return !(x == y);
}

推荐使用Hinnant的allocator样板: https://howardhinnant.github.io/allocator_boilerplate.html)

前一段时间我发现这个解决方案对我非常有用:STL容器的快速c++ 11分配器。它略微加快了VS2017上的STL容器(~5倍)以及GCC上的STL容器(~7倍)。它是一种基于内存池的特殊用途的分配器。它可以与STL容器一起使用，这多亏了您所要求的机制。

使用自定义分配器来使用内存池而不是堆可能会很有用。这只是众多例子中的一个。

对于大多数情况，这肯定是一个不成熟的优化。但它在某些情况下(嵌入式设备、游戏等)非常有用。