Why do creating pointer to instances beyond certain number(30) of a 'Structure' with 'stxxl:Vector' as one of its DataType fails?

I am using STXXL Library's stxxl::vector in my code as :

struct B
{
    typedef stxxl::VECTOR_GENERATOR<float>::result vector;
    vector content; 
};

And then creating many instances of the above declared Structure in a loop using the following code snippet :

 for(i=0;i<50;i++)
 {
     B* newVect= new B();
     // Passing the above '*newVect' to some other function
 }

But this snippet will not create 'newVect' beyond certain number(30: in this case)

However, I tried the same thing by just replacing "stxxl:Vector" with some other In Memory datatypes as :

struct B
{
    float a,b,c;
    int  f,g,h;
};

Above created Structure works fine even for "100000" new instances as:

for(i=0;i<100000;i++)
{
    B* newVect= new B();
    // Passing the above '*newVect' to some other function
}

with every system resource remaining same.

Please help me with this.

Can "stxxl:Iterators" help here or work as an alternative?

What kind of behavior do 'stxxl:vector' have in this case?

UPDATE

Tried removing the function call from each iteration and putting it altogether outside the loop but no help. Example Code:

#include <stxxl/vector>
#include <iostream>
using namespace std;

struct buff
{
    typedef stxxl::VECTOR_GENERATOR<float>::result vector;

    vector content; 
};

struct par
{
    buff* b[35];
};

void f(par *p)
{
    for(int h=0;h<35;h++)
    {
        std::cout<<endl<<"In func: "<<(*p).b[h];    
    }
}

int main()
{
    par parent;
    for(int h=0;h<35;h++)
    {
        buff* b=new buff();

        parent.b[h]=b;
        cout<<endl<<"IN main: "<<parent.b[h];
    }

    cout << endl << endl;
    f(&parent);

    return 0;
}

Each stxxl::vector costs a specific amount of internal memory, since it is basically a paging system for blocks in external memory.

With the default settings, this is 8 (CachePages) * 4 (PageSize) * 2 MiB (BlockSize) = 64 MiB of RAM per stxxl::vector.

So, you are basically running out of RAM.