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HIGH PERFORMANCE COMPUTATIONAL MECHANICS (MCAP)

Credits Dept.
7.5 (6.0 ECTS) BSC

Instructors

Person in charge:  (-)
Others:(-)

General goals

The main goal of the course is to provide a general view of what do we mean by a computer simulation, how and why important it is and at what extent HPC facilities are becoming decisive in this field. Both industrial and scientific applications will be reviewed and analyzed. The student will learn the basic concepts of CM and their implementation strategies in HPC architectures, pinpointing at efficiency, robustness and scalability issues.

Specific goals

Knowledges

  1. To learn the basic concepts of Computational Mechanics (CM).
  2. To understand the influence of HPC facilities in running computer simulations of physical processes.
  3. To know the main domains of applications in industry and science.
  4. To know the basic structure and needs of an HPCM tools.

Abilities

  1. To identify application problems where HPCM is decisive.
  2. To communicate with users of HPCM tools from different fields.
  3. To trace the difficulties that can arise, foreseeing solutions to them.

Competences

  1. To support HPCM users in industry and science.
  2. To work integrated in teams with both HPCM users of different backgrounds and computer scientists.

Contents

Estimated time (hours):

T P L Alt Ext. L Stu A. time
Theory Problems Laboratory Other activities External Laboratory Study Additional time

1. High Performance Computational Mechanics: Introduction, range, application examples.
T      P      L      Alt    Ext. L Stu    A. time Total 
6,0 0 0 0 0 4,0 0 10,0

2. Simulations and Numerical Methods I: Introduction, basic concepts, goals and importance, basic physical models.
T      P      L      Alt    Ext. L Stu    A. time Total 
10,0 10,0 5,0 0 0 6,0 0 31,0

3. Simulations and Numerical Methods II: Types of methods, discretization, solution strategies.
T      P      L      Alt    Ext. L Stu    A. time Total 
10,0 10,0 5,0 0 0 6,0 0 31,0

4. Simulations and HPC: Parallelization paradigms, strategies and tools.
T      P      L      Alt    Ext. L Stu    A. time Total 
10,0 10,0 10,0 0 0 6,0 0 36,0

5. HPCM revisited: Tools review, examples, importance.
T      P      L      Alt    Ext. L Stu    A. time Total 
6,0 0 10,0 0 0 4,0 0 20,0


Total per kind T      P      L      Alt    Ext. L Stu    A. time Total 
42,0 30,0 30,0 0 0 26,0 0 128,0
Avaluation additional hours 0
Total work hours for student 128,0

Docent Methodolgy

Classes building up concepts in a structured fashion and setting out the commitment required for their practical application. Introductory and descriptive classes to give perspective and future trends. Laboratory classes focusing on co-operative work in order to consolidate concepts, skills and competencies.

Evaluation Methodgy

The evaluation of the course will be based on the implementation and/or technical report presented for a set of practical assignments and a presentation and discussion of a bibliographical item.

Basic Bibliography

  • K. Eriksson, D. Estep, P. Hansbo and C. Johnson, Computational differential equations, Cambridge University Press, 1996.
  • J.M. Ortega, Introduction to Parallel & Vector Solution of Linear Systems, Plenum, 1988.

Complementary Bibliography

(no available informacion)

Web links

(no available informacion)

Previous capacities

-  Basic algebra and mathematical analysis courses.
-  Notions of MPI and OpenMP.
-  Notions of parallel architectures.
-  Basic physics course (optional, but useful).


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