Dynamic Memory De-allocation in Fortran 95/2003 derived type calculus

  • Authors:
  • Damian W. I. Rouson;Karla Morris;Xiaofeng Xu

  • Affiliations:
  • US Naval Research Laboratory, 4555 Overlook Ave. SW, Washington, DC 20375, USA. Tel.: +1 202 767 6965/ Fax: +1 815 572 8203/ E-mail: damian.rouson@nrl.navy.mil;Department of Mechanical Engineering, The Graduate Center of the City University of New York, 365 Fifth Avenue, New York, NY 10016, USA. Tel.: +1 212 650 7134/ Fax: +1 212 650 8013/ E-mail: karla_ ...;Department of Fire Protection Engineering, University of Maryland, College Park, MD 20742, USA. Tel.: +1 571 215 2413/ Fax: +1 301 405 9383/ E-mail: xxf@umd.edu

  • Venue:
  • Scientific Programming
  • Year:
  • 2005

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Abstract

Abstract data types developed for computational science and engineering are frequently modeled after physical objects whose state variables must satisfy governing differential equations. Generalizing the associated algebraic and differential operators to operate on the abstract data types facilitates high-level program constructs that mimic standard mathematical notation. For non-trivial expressions, multiple object instantiations must occur to hold intermediate results during the expression's evaluation. When the dimension of each object's state space is not specified at compile-time, the programmer becomes responsible for dynamically allocating and de-allocating memory for each instantiation. With the advent of allocatable components in Fortran 2003 derived types, the potential exists for these intermediate results to occupy a substantial fraction of a program's footprint in memory. This issue becomes particularly acute at the highest levels of abstraction where coarse-grained data structures predominate. This paper proposes a set of rules for de-allocating memory that has been dynamically allocated for intermediate results in derived type calculus, while distinguishing that memory from more persistent objects. The new rules are applied to the design of a polymorphic time integrator for integrating evolution equations governing dynamical systems. Associated issues of efficiency and design robustness are discussed.