{'fraction_non_alphanumeric': 0.01256281407035176, 'fraction_numerical': 0.011725293132328308, 'mean_word_length': 5.638888888888889, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
PARALLEL PERFORMANCE OF PRECONDITIONED DOMAIN DECOMPOSITION METHOD FOR LARGE SCALE HEAT TRANSFER PROBLEM

Domain decomposition is a well known parallel finite element method for distributed parallel computing environment. Incorporation of a suitable preconditioner like balancing domain decomposition (BDD) method makes the method more efficient due to its excellent convergence rate. Several studies have considered applications of the BDD method to various phenomena and improvement of its convergence rate. However, in applying the BDD method to large-scale problems, it is difficult to solve the coarse problem since the size of the coarse problem increases in proportion to the number of subdomains. In this work, domain decomposition technique with an incomplete balancing preconditioner has been adapted to the distributed parallel environment of networked workstations and the supercomputer. Using the developed code, several heat transfer model problems are solved and the parallel performances are analyzed on the network of eight Pentium IV PC cluster and GP7000F workstations. Finally, very large size of problem over 11 million DOFs has been solved using 1024 SR8000 supercomputer.