MATH-454 / 4 credits

Teacher: Antolin Sanchez Pablo

Language: English


Summary

This course provides insight into a broad variety of High Performance Computing (HPC) concepts and the majority of modern HPC architectures. Moreover, the student will learn to have a feeling about what architectures are suited for several types of algorithms.

Content

Keywords

HPC, Parallelization, MPI, GPU

 

Learning Prerequisites

Required courses

  • Analysis, bachelor level
  • Numerical analysis for engineers
  • Matrix algebra

Recommended courses

  • Programming concepts in scientific computing

Learning Outcomes

By the end of the course, the student must be able to:

  • Classify the types of HPC architecture
  • Identify codes suited for parallelizing
  • Apply the most commont parallelization techniques
  • Implement algorithms in parallel
  • Investigate the performances of parallel code
  • Argue about the differences in performances between theory and practice
  • Optimize the usage of hardware and software resources depending on the type of algorithm to parallelize

Transversal skills

  • Set objectives and design an action plan to reach those objectives.
  • Communicate effectively with professionals from other disciplines.
  • Access and evaluate appropriate sources of information.
  • Write a scientific or technical report.

Teaching methods

Lectures, exercises, project work

Expected student activities

Attendance at lectures, completing exercises, writing a project

 

Assessment methods

Oral defense of project work

 

Dans le cas de l'art. 3 al. 5 du Règlement de section, l'enseignant décide de la forme de l'examen qu'il communique aux étudiants concernés.

 

Supervision

Office hours Yes
Assistants Yes
Forum Yes

In the programs

  • Semester: Fall
  • Exam form: Oral (winter session)
  • Subject examined: Parallel and high-performance computing
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 1 Hour(s) per week x 14 weeks
  • Practical work: 1 Hour(s) per week x 14 weeks
  • Semester: Fall
  • Exam form: Oral (winter session)
  • Subject examined: Parallel and high-performance computing
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 1 Hour(s) per week x 14 weeks
  • Practical work: 1 Hour(s) per week x 14 weeks

Reference week

 MoTuWeThFr
8-9 CO6   
9-10    
10-11 CO6   
11-12 CO6   
12-13     
13-14     
14-15     
15-16     
16-17     
17-18     
18-19     
19-20     
20-21     
21-22     

Tuesday, 8h - 10h: Lecture CO6

Tuesday, 10h - 11h: Exercise, TP CO6

Tuesday, 11h - 12h: Exercise, TP CO6