Course

MATH-505: HPC for numerical methods and data analysis

Summary

The objective of this course is to provide the necessary background for designing efficient parallel algorithms in scientific computing as well as in the analysis of large volumes of data. The operations considered are the most costly steps at the heart of many complex numerical simulations.

Lectures

Instructor

Laura Grigori

Expertise Numerical linear algebra, deterministic and randomized algorithmsHigh performance computing for scientific applicationsHigh dimensional problems and tensor computationsApplications in astrophysics, molecular simulations, etcCombinatorial scientific computingMathematical Software Teaching & PhD PhD Students Israa Fakih, Zhipeng Xue, Andrea Di Antonio, Mariana Graciela Martinez Aguilar, Guifré Sánchez i Serra Courses Numerical analysis and computational mathematics MATH-456 The cou

Official source

https://edu.epfl.ch/coursebook/en/hpc-for-numerical-methods-and-data-analysis-MATH-505

Moodle Page

http://go.epfl.ch/MATH-505

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Summary

Lectures

Instructor

Laura Grigori

Official source

https://edu.epfl.ch/coursebook/en/hpc-for-numerical-methods-and-data-analysis-MATH-505

Moodle Page

http://go.epfl.ch/MATH-505

About this result

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