Teaching Scientific Computing: A Model-Centered Approach to Pipeline and Parallel Programming with C

Abstract

The aim of this study is to present an approach to the introduction into pipeline and parallel computing, using a model of the multiphase queueing system. Pipeline computing, including software pipelines, is among the key concepts in modern computing and electronics engineering. The modern computer science and engineering education requires a comprehensive curriculum, so the introduction to pipeline and parallel computing is the essential topic to be included in the curriculum. At the same time, the topic is among the most motivating tasks due to the comprehensive multidisciplinary and technical requirements. To enhance the educational process, the paper proposes a novel model-centered framework and develops the relevant learning objects. It allows implementing an educational platform of constructivist learning process, thus enabling learners' experimentation with the provided programming models, obtaining learners' competences of the modern scientific research and computational thinking, and capturing the relevant technical knowledge. It also provides an integral platform that allows a simultaneous and comparative introduction to pipelining and parallel computing. The programming language C for developing programming models and message passing interface (MPI) and OpenMP parallelization tools have been chosen for implementation. Background and IntroductionTeaching of scientific and parallel computing, and advanced programming are under permanent attention of scientists and educators. Different approaches, models, and solutions for teaching, assessments, and evaluation are proposed. The constructivist model for advanced programming education is one out of the presented approaches [1,2]. In the model, a learner constructs the relevant knowledge, experiments with the provided environment, observes the results, and draws conclusions. The constructivist approach incorporates the model-centered learning as well as comparative programming teaching methods. Experimenting with the provided model, "turning" the model and observing it from different sides, comparing different solutions, and analysing and drawing conclusions, the learner improves the relevant knowledge and competences.Modern technologies widely involve parallel computing, and plenty of scientific and industrial applications use parallel programming techniques. Teaching of parallel computing is one of the most important and challenging topics in the scientific computing and advanced programming education. In this research, we present a methodology for the introduction to scientific and parallel computing. This methodology is based on the constructivist technology and uses a modelcentered approach and learning by comparison.

Methodological Guidelines for the Design and Integration of Software Learning Objects for Scientific Programming Education

“…is study continues the previous works of the authors [1,2] and presents methodological generalizations that enable the creation of an SI-centred educational environment for scientific computing and scientific programming education.…”

“…Design science research (DSR) [3][4][5] is used as a research methodology for design and implementation of learning resources (LR) presented in this research. ere are several major problems to be solved: (A) ere is a need to specify SP courses: SP courses (1) are too technical, (2) are mainly oriented to mathematical and algorithmic foundations, (3) require many prerequisites, (4) cannot easily motivate students. (B) ere is a need to specify SP educational technology: (1) there is no vision of suitable educational technology (including the lack of solutions of how to develop the content and teach SP); (2) there is no vision of how to integrate SP into a broader curriculum.…”

“…From the perspectives of the educational content design, (1) the DP of EC design are provided; the DP are based on the presented approaches and requirements enabling development of the learning content providing constructionist educational environment and co-mediated learning technology; (2) practical examples of LR including SLOs are designed.…”

Scientific computing to foster student research: overview and conceptual framework for STEM curricula

“…Python for modelbased and simulation-centred education is presented in (Dolgopolovas et al, 2014). The model of Stochastic simulations of queueing systems using the C is presented in (Dolgopolovas et al, 2015).…”

Mapeamento Sistemático do Ensino Teórico e Prático de Programação Paralela

“…[ Dolgopolovas et al 2015] apresentam uma metodologia baseada em uma abordagem construtivista. Esta abordagemé centrada em modelo e aprendizagem comparativa, que utiliza modelos de programação baseados em simulações estocásticas fornecidas por um sistema de filas multi-fase.…”