Architectures and Middleware for Scientific Computing
The lecture discusses architectures and middleware for scientific computing and big data applications. It consists of two parts: in the first part we focus on GPU programming and in the second part we investigate advanced topics from the field of cluster computing and parallel programming.
Topics
- Part 1: GPU Programming
- GPU hardware
- programming models for GPUs: CUDA, OpenCL, OpenACC
- Part 2: Cluster Computing
- selected MPI functions: MPI one-sided, processor topologies
- parallel file systems
- Architectures for Big Data: From Hadoop to Kafka, Key-Value Stores
Requirements
Basic C programming skills are necessary. The bachelor lecture "Konzepte paralleler Programmierung" is recommended.
Lecturer
Prof. Dr. Bettina Schnor
Modules
- Master Computational Science: 7010
- 552511 - Vorlesung
- 552521 - Übung
- 552501 - Prüfung
- Master Data Science
- INF-DSAM4A: Advanced Infrastructures and Software Engineering A
- INF-DSAM4B: Advanced Infrastructures and Software Engineering B
Room/Dates
The lecture is given in room 03.04.0.02 as a block course at the following dates:
- Monday, 14.10.2019, 16:15 - 17:45 h
- Monday, 21.10.2019, 10:00 - 18:00 h (all the day), room 03.04.1.02
- Tuesday, 22.10.2019, 09:00 - 17:00 h (all the day), room 03.04.1.02
- Monday, 04.11.2019, 16:15 - 17:45 h
- Monday, 11.11.2019, 16:15 - 17:45 h
- Monday, 18.11.2019, 16:15 - 17:45 h
- Monday, 25.11.2019, 16:15 - 17:45 h
- Monday, 02.12.2019, 16:15 - 17:45 h
- Monday, 09.12.2019, 16:15 - 17:45 h
- Monday, 13.01.2020, 16:15 - 17:15 h Exam test, room 03.04.0.02 (as usual)
- Monday, 20.01.2020, 16:15 - 17:45 h Final project presentation, room 03.04.0.02 (as usual)
- Monday, 27.01.2020, 16:15 - 17:45 h Final project presentation