If you have to perform many calculations, or analyses that are too large for your own system, clusters and supercomputers provide the necessary computing power. In this training you will get acquainted with parallel processing, machine learning and work with the national Lisa computer cluster, the national supercomputer Snellius and HPC cloud.
HPC Course
Course Description
Course content
In this course you will learn about tools and workflows that you can use in your research to manage big data and/or big computation tasks. The presentations and hands-on workshops are targeted at PhD level students, who would like to get started with HPC. Examples from daily practice will be used. You will learn to use linux computers and supercomputers to deploy computationally intensive tasks. You will have the opportunity to learn from fellow researchers, from experts from different knowledge fields and technical experts. After the course you will have a broader and deeper knowledge and hands-on experience with HPC and data analytics to use in your own research.
Study Characteristics
- Teacher: Various lecturers from VU/UvA & SURF
- Language: English
- ECTS: 3
- Discipline: Computational science (life science, genomics, finance, climate,…)
- Self paced: no
- In class/online: in class
- Academic skill: Research
- Available to: First PhD students VU | Academic staff VU | All VU employees
- Min. number of students: 8
- Max. number of students: 30
- Total course duration in hrs.: 24
- Number of lessons: 6
- Anticipated hrs. of study: 12
- Sign up period: September
- Concluding assessment: no
- With certificate: yes
-
HPC Course
Course Description
Course content
In this course you will learn about tools and workflows that you can use in your research to manage big data and/or big computation tasks. The presentations and hands-on workshops are targeted at PhD level students, who would like to get started with HPC. Examples from daily practice will be used. You will learn to use linux computers and supercomputers to deploy computationally intensive tasks. You will have the opportunity to learn from fellow researchers, from experts from different knowledge fields and technical experts. After the course you will have a broader and deeper knowledge and hands-on experience with HPC and data analytics to use in your own research.
Study Characteristics
- Teacher: Various lecturers from VU/UvA & SURF
- Language: English
- ECTS: 3
- Discipline: Computational science (life science, genomics, finance, climate,…)
- Self paced: no
- In class/online: in class
- Academic skill: Research
- Available to: First PhD students VU | Academic staff VU | All VU employees
- Min. number of students: 8
- Max. number of students: 30
- Total course duration in hrs.: 24
- Number of lessons: 6
- Anticipated hrs. of study: 12
- Sign up period: September
- Concluding assessment: no
- With certificate: yes
Peter Stol
For information about this course, contact Peter Stol