Parallel Computing 2020/21 fall

Lectures

MON 12:15, Delta 2047

Lectures get web-casted and are video-recorded; past lectures appear here! NB! Link to live WebCast appears in the same directory as soon the lecture video-recording starts.

Course syllabus:

Lecture 1-9 slides (pdf) by Eero Vainikko

1. Introduction to parallel computing
2. What is parallel computing
3. Parallel computer architectures
4. Analytical modelling of parallel algorithms
5. Parallel Algorithm Design Principles
6. Techniques for Load Balancing
7. Parallel programming models; Shared memory; Message passing
8. Computer Benchmarks
9. Domain Decomposition Method
10. General Purpose GPU Programming
    • GPGPU with OpenCL (pdf) by Mohammad Anagreh
11. MapReduce model
    • MapReduce slides (pdf) by Pelle Jakovits
12. Parallel data structures and Apache Spark
    • Apache Spark slides (pdf) by Pelle Jakovits
13. Distributed DataFrames and Parallel Machine Learning
    • Distributed DataFrame slides (pdf) by Pelle Jakovits
14. Parallel computing models for Graph processing
    • Parallel Graph processing (pdf) by Pelle Jakovits
15. Consultation for final exam