With ps or similar tools you will only get the amount of memory pages allocated by that process. This number is correct, but:
does not reflect the actual amount of memory used by the application, only the amount of memory reserved for it
can be misleading if pages are shared, for example by several threads or by using dynamically linked libraries
If you really want to know what amount of memory your application actually uses, you need to run it within a profiler. For example, Valgrind can give you insights about the amount of memory used, and, more importantly, about possible memory leaks in your program. The heap profiler tool of Valgrind is called 'massif':
Massif is a heap profiler. It performs detailed heap profiling by taking regular snapshots of a program's heap. It produces a graph showing heap usage over time, including information about which parts of the program are responsible for the most memory allocations. The graph is supplemented by a text or HTML file that includes more information for determining where the most memory is being allocated. Massif runs programs about 20x slower than normal.
As explained in the Valgrind documentation, you need to run the program through Valgrind:
valgrind --tool=massif <executable> <arguments>
Massif writes a dump of memory usage snapshots (e.g. massif.out.12345). These provide, (1) a timeline of memory usage, (2) for each snapshot, a record of where in your program memory was allocated. A great graphical tool for analyzing these files is massif-visualizer. But I found ms_print, a simple text-based tool shipped with Valgrind, to be of great help already.
To find memory leaks, use the (default) memcheck tool of valgrind.
Using C++11:
#include <map>
using namespace std;
map<int, char> m = {{1, 'a'}, {3, 'b'}, {5, 'c'}, {7, 'd'}};
Using Boost.Assign:
#include <map>
#include "boost/assign.hpp"
using namespace std;
using namespace boost::assign;
map<int, char> m = map_list_of (1, 'a') (3, 'b') (5, 'c') (7, 'd');
Best Solution
The estimate would be closer to
There is an overhead for each element you add, and there is also a fixed overhead for maintaining the data structure used for the data structure storing the map. This is typically a binary tree, such as a Red-Black Tree. For instance, in the GCC C++ STL implementation
ELEMENT_OVERHEADwould besizeof(_Rb_tree_node_base)andCONTAINER_OVERHEADwould besizeof(_Rb_tree). To the above figure you should also add the overhead of memory management structures used for storing the map's elements.It's probably easier to arrive at an estimate by measuring your code's memory consumption for various large collections.