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。

当使用gpu或其他协处理器时，以特殊的方式在主存中分配数据结构有时是有益的。这种特殊的内存分配方式可以在自定义分配器中以一种方便的方式实现。

在使用加速器时，通过加速器运行时进行自定义分配是有益的，原因如下:

through custom allocation the accelerator runtime or driver is notified of the memory block in addition the operating system can make sure that the allocated block of memory is page-locked (some call this pinned memory), that is, the virtual memory subsystem of the operating system may not move or remove the page within or from memory if 1. and 2. hold and a data transfer between a page-locked memory block and an accelerator is requested, the runtime can directly access the data in main memory since it knows where it is and it can be sure the operating system did not move/remove it this saves one memory copy that would occur with memory that was allocated in a non-page-locked way: the data has to be copied in main memory to a page-locked staging area from with the accelerator can initialize the data transfer (through DMA)

I personally use Loki::Allocator / SmallObject to optimize memory usage for small objects — it show good efficiency and satisfying performance if you have to work with moderate amounts of really small objects (1 to 256 bytes). It can be up to ~30 times more efficient than standard C++ new/delete allocation if we talk about allocating moderate amounts of small objects of many different sizes. Also, there's a VC-specific solution called "QuickHeap", it brings best possible performance (allocate and deallocate operations just read and write the address of the block being allocated/returned to heap, respectively in up to 99.(9)% cases — depends on settings and initialization), but at a cost of a notable overhead — it needs two pointers per extent and one extra for each new memory block. It's a fastest possible solution for working with huge (10 000++) amounts of objects being created and deleted if you don't need a big variety of object sizes (it creates an individual pool for each object size, from 1 to 1023 bytes in current implementation, so initialization costs may belittle the overall performance boost, but one can go ahead and allocate/deallocate some dummy objects before the application enters it's performance-critical phase(s)).

标准的c++ new/delete实现的问题是，它通常只是C malloc/free分配的包装器，它适用于较大的内存块，比如1024+字节。它在性能方面有显著的开销，有时还会占用额外的内存用于映射。因此，在大多数情况下，自定义分配器的实现方式是最大化性能和/或最小化分配小对象(≤1024字节)所需的额外内存量。

我正在研究一个mmap-分配器，它允许向量使用内存 内存映射文件。我们的目标是让向量使用这样的存储 直接在由mmap映射的虚拟内存中。我们的问题是 提高真正大的文件(>10GB)的读取到内存，而不复制 开销，因此我需要这个自定义分配器。

到目前为止，我已经有了一个自定义分配器的骨架 (它来源于std::allocator)，我认为这是一个很好的开始 指向写自己的分配器。请随意使用这段代码 以任何你想要的方式:

#include <memory>
#include <stdio.h>

namespace mmap_allocator_namespace
{
        // See StackOverflow replies to this answer for important commentary about inheriting from std::allocator before replicating this code.
        template <typename T>
        class mmap_allocator: public std::allocator<T>
        {
public:
                typedef size_t size_type;
                typedef T* pointer;
                typedef const T* const_pointer;

                template<typename _Tp1>
                struct rebind
                {
                        typedef mmap_allocator<_Tp1> other;
                };

                pointer allocate(size_type n, const void *hint=0)
                {
                        fprintf(stderr, "Alloc %d bytes.\n", n*sizeof(T));
                        return std::allocator<T>::allocate(n, hint);
                }

                void deallocate(pointer p, size_type n)
                {
                        fprintf(stderr, "Dealloc %d bytes (%p).\n", n*sizeof(T), p);
                        return std::allocator<T>::deallocate(p, n);
                }

                mmap_allocator() throw(): std::allocator<T>() { fprintf(stderr, "Hello allocator!\n"); }
                mmap_allocator(const mmap_allocator &a) throw(): std::allocator<T>(a) { }
                template <class U>                    
                mmap_allocator(const mmap_allocator<U> &a) throw(): std::allocator<T>(a) { }
                ~mmap_allocator() throw() { }
        };
}

为了使用它，像下面这样声明一个STL容器:

using namespace std;
using namespace mmap_allocator_namespace;

vector<int, mmap_allocator<int> > int_vec(1024, 0, mmap_allocator<int>());

例如，每当分配内存时，就可以使用它记录日志。什么是必要的 是重新绑定结构，否则向量容器使用超类分配/释放 方法。

更新:内存映射分配器现在可以在https://github.com/johannesthoma/mmap_allocator上获得，并且是LGPL。您可以在项目中使用它。

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”。

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。