Topic 1. Fundamentals of parallel and distributed computing: system architectures, Flynn’s taxonomy, Amdahl’s and Gustafson’s laws; .NET 10 and JetBrains Rider

Goal: become familiar with parallel computing architectures, Flynn’s taxonomy, and parallel program metrics; learn to estimate speedup and efficiency using Amdahl’s law, the Gustafson–Barsis law, and the Karp–Flatt metric; master a method for measuring the execution time of C# programs on .NET 10 in JetBrains Rider.

Lecture contents

1. Why parallel computing — Why we need parallel computing · Basic concepts
2. Parallel system architectures — Shared-memory systems · Distributed-memory systems · Flynn’s taxonomy
3. Models, metrics, and scaling laws — Parallelism models · Parallel program metrics · Amdahl’s law · The Gustafson–Barsis law and scalability
4. Measurement, .NET 10, and Rider — Measurement methodology · The .NET 10 platform · The JetBrains Rider environment
5. Examples and common mistakes — Program examples · Common mistakes

Practice and review

• Practice — 3 worked examples with complete code and output
• Tasks — 30 variants, each with tasks at three difficulty levels
• Summary — conclusions, self-check questions, and useful links