Memory Allocation for High-Dimensional Data Structures

Environment: Windows NT SP5, Windows 95b/98, Visual C++ 6

1. General Methods

For a very large application, dynamic memory allocation is common in C/C++ programming. For example, I ported Basin Modeling application from SUN workstation to PC 486 in 1992, cutting memory usage up to 90%. Generally two types of dynamic memory allocation methods are wildly used to deal with high dimensional data structures. One is to use 1D to represent nD as shown in the follow:
// ignore pointer validation and use malloc and free for instance
Type* p = (Type *)malloc(s1*s2* ... *sn*sizeof(Type));
for(i1 = 0; i1 < s1; i1 ++) 
 for(i2 = 0; i2 < s2; i2 ++)
  //... 
  for(in = 0; in < sn; in ++)
   p[(...((i1*s2+i2)*s3+i3)...)*sn+in] = ...; 
   //do something using p 
free(A);
The other is directly to use nD as shown in the follow:
Type *p1, **p2, ..., **...*pn;
  
p1 = (Type *)malloc(sizeof(Type)*s1*s2*...*sn*sizeof(Type));
p2 = (Type **)malloc(sizeof(Type*)*s1*s2*...*sn-1);
//...
pn = (Type **...*)calloc(sizeof(Type**...*)s1, size);

// need assign address properly
for(i = 0; i < s1*s2*...*sn-1; i ++)
 *(p2+i) = &p1[sn*i*sizeof(Type)];

for(i = 0; i < s1; i ++)
 *(p3+i) = &p2[sn-1*i];
//...

for(i = 0; i < s1*s2*...*sn-2; i ++)
 *(pn+i) = &pn-1[s2*i];

for(i1 = 0; i1 < s1; i1 ++) 
 for(i2 = 0; i2 < s2; i2 ++)
  //...
  for(in = 0; in < sn; in ++)
   pn[i1][i2]...[in] = ...; 
   //do something using pn

free(**...*p);  //(n-1)-dimensional pointer

//...

free(*p);
free(p);

2. Source Code

  1. MemA.h uses C++ template and operator overloading to implement 1D, 2D, and 3D based on method 1. It is easy to extend to high dimension, such as 4D and 5D. It is especially useful to port applications from Fortran to C++.
      Member functions
    • bool CDynArray<Type>::SetSize(int i);
    • bool CDynArray<Type>::SetSize(int i, int j);
    • bool CDynArray<Type>::SetSize(int i, int j, int k);
    • Type& CDynArray<Type>::operator ()(int i);
    • Type& CDynArray<Type>::operator ()(int i, int j);
    • Type& CDynArray<Type>::operator ()(int i, int j, int k);
    • void CDynArray<Type>::Remove();
  2. MemB.h uses C++ template to implement 1D, 2D, and 3D based on method 2.
      Member functions
    • // One dimension
    • Type* CMalloc<Type>::Malloc(int I);
    • void CMalloc<Type>::Free(T*& X);
    • // Two dimension
    • Type** CMalloc<Type>::Malloc(int I, int J);
    • void CMalloc<Type>::Free(T**& X);
    • // Three dimension
    • Type** CMalloc<Type>::Malloc(int I, int J, int K);
      			
    • void CMalloc<Type>::Free(T***& X);
  3. MemC.h and MemC.c only use C to implement 2D and 3D based on method 2.
      Member functions
    • void** Malloc2(int, int, size_t);
    • void*** Malloc3(int, int, int, size_t);
    • void Free2(void**);
    • void Free3(void***);

3. Demo Project

MemDemo.cpp demonstrates how to use memory allocation functions in the above files. It tests both float, double, and data structure types.

Downloads

Download demo project - 6 Kb
Download source - 3 Kb


Comments

  • Wonderfull

    Posted by Legacy on 07/26/2003 12:00am

    Originally posted by: Naresh Prajapati

    I was just handling my data structure as conventional way, got yr artical and made all d.s standard & efficient. Thanks

    Reply
Leave a Comment
  • Your email address will not be published. All fields are required.

Top White Papers and Webcasts

  • Relying on outside companies to manage your network and server environments for your business and applications to meet the needs and demands of your users can be stressful. This is especially true as many Managed Hosting organizations fail to meet their service level agreements. Read this Forrester total economic impact report and learn what makes INetU different and how they exceed their customers' managed hosting expectations.

  • As virtualization becomes the norm throughout organizations of nearly all sizes, and as more organizations look to private cloud solutions, IT decision makers are increasingly in need of ways to keep storage costs and complexity under control in the face of often-runaway virtual machine (VM) sprawl. Application-aware storage is designed to help achieve these important goals. Read this white paper to learn how application-aware storage allows you to gain VM-level visibility into application performance and …

Most Popular Programming Stories

More for Developers

RSS Feeds

Thanks for your registration, follow us on our social networks to keep up-to-date