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The purpose of this paper is to describe the parallelization of PragTic - a fatigue damage simulator. There is a discussion about the former version inefficiency (caused by frequent I/O operations), parallel implementation and parallelized PragTic scalability testing. The parallelization is done at the node level where the nodes are defined in the context of the finite element mesh. We also ran a simple model example (hundreds of nodes), real world example (millions of nodes) and our approach is to test using numerical experiments where we achieve weak parallel scalability. At the end of the article, the results of numerical experiments are depicted in tables and graphs.

The paper deals with the energy consumption evaluation of selected Sparse and Dense BLAS Level 1, 2 and 3 routines. Authors employed AXPY, Sparse Matrix-Vector, Sparse Matrix-Matrix, Dense Matrix-Vector, Dense Matrix-Matrix and Sparse Matrix-Dense Matrix multiplication routines from Intel Math Kernel Library (MKL). The measured characteristics illustrate the different energy consumption of BLAS routines, as some operations are memory-bounded and others are compute-bounded. Based on their recommendations one can explore dynamic frequency switching to achieve significant energy savings up to 23%.

In this paper, we discuss and present our progress toward a project, which is focused on fatigue life prediction under multiaxial loading in the domain of low-cycle fatigue, i.e. cases, where the plasticity cannot be neglected. First, the elastic-plastic solution in the finite element analysis is enhanced and verified on own experiments. Second, the method by Jiang describing the instantaneous damage increase by analyses of load time by time, is in implementation phase. In addition, simplified routines for conversion of elastic stresses-strains to elastic-plastic ones as proposed by Firat and Ye et.al. are evaluated on the basis of data gathered from external sources. In order to produce high quality complex analyses, which could be feasible in an acceptable time, and allow the period for next analyses of results to be expanded; the core of PragTic fatigue solver used for all fatigue computations are being re-implemented to get the fully parallelized scalable solution.

PERMON toolbox makes use of theoretical results in discretization techniques, quadratic programming algorithms, and domain decomposition methods. It is built on top of the PETSc framework for numerical computations. This paper describes its packages, and shows case of their application for a contact problem of linear elasticity decomposed by TFETI non-overlapping domain decomposition method. We end with the inequality constrained quadratic programming problems that can be solved by our PermonQP package with the PermonIneq extension.