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.


  • 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


Basic C programming skills are necessary. The bachelor lecture "Konzepte paralleler Programmierung" is recommended.


Prof. Dr. Bettina Schnor
Max Schrötter


  • Master Computational Science: 7010
    • 552511 - Vorlesung
    • 552521 - Übung
    • 552501 - Prüfung

  • Master Data Science
    • INF-DSAM4B: Advanced Infrastructures and Software Engineering B


The seminar takes place on Wednesdays from 10 a.m. to 12 p.m. in room

First lecture 27.10.2021, 10 a.m. to 12 p.m. Universität Potsdam, room