Automated parallelization of a program for modeling intraparticle diffusion and adsorption in heterogeneous nanoporous media

Abstract

Heterogeneous media consisting of thin layers of particles of forked porous structure with different physical-chemical properties are widely used in science-intensive technologies and priority sectors of industry, medicine, ecology, etc. Such layers are distributed systems of pores consisting of two main spaces: micro- and nanopores of particles and macropores and cavities between particles. Mass transfer in the system of heterogeneous media causes two types of mass transfer: diffusion in macropores, owing to interparticle space, and diffusion in the system of micro- and nanopores inside particles of the heterogeneous medium. Intraparticle space has a higher level of adsorptive capacity, and at the same time, has a lower velocity of diffusion intrusion in comparison with interparticle space. In modeling concentra- tion and gradient fields for various diffusible components, an important scientific problem is the identification of kinetic parameters of a transfer, predetermining mass transfer velocity on macro- and micro levels, and also equilibrium conditions. The results of designing and parallelization of a program implementing a Crank-Nicolson scheme using algebra-algorithmic specifications represented in a natural- linguistic form are given. The tools for automated design, synthesis and auto-tuning of programs were applied that provided the translation of algebra-algorithmic schemes into source code in a target programming language and its tuning for execution environment to increase the program performance. Numerical distributions of values of diffusion coefficients for intraparticle transfer along coordinate of medium thickness for various time snapshots were obtained. Based on the results of the identification, the models were checked for adequacy and numerical modeling and analysis of concentration and gradient fields of mass transfer were carried out. The experiment results of auto- tuning the software implementation demonstrated high multiprocessor speedup on test data input.