Parallel Computing 2021/22 fall

Lectures

MON 14:15, Delta 1022 (first lecture on 6 September)

& Zoom (log into courses to see link)

Course syllabus:

Lecture 1-9 slides (pdf)

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. Domain Decomposition Method
8. Computer Benchmarks
9. Parallel programming models; General Purpose GPU Programming
   • GPGPU with OpenCL (pdf) by Mohammad Anagreh
10. High-Performance Data Analytics (HPDA) - guest lecture by Feras Awaysheh
    • High-Performance Data Analytics (pdf)
11. MapReduce distributed computing model
    • MapReduce model (pdf)
12. Parallel data structures and Apache Spark
    • Parallel data structures and Apache Spark (pdf)
13. Distributed DataFrames and Parallel Machine Learning
    • Parallel Spark dataframes (pdf)
14. Parallel computing models for Graph processing
    • Parallel Graph Processing (pdf)
15. Consultation for final exam