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High Performance Computing

Welcome to the High Performance Computing course repository for Term 1. This repository contains materials related to the course, including lecture notes, assignments, and additional resources.

Course Overview

Lessons

  1. Lesson 1: Languages and Tools for Scientific Programming

    • Introduction to programming languages and tools commonly used in scientific computing.

  2. Lesson 2: Python Introduction

    • Overview of Python and its applications in high-performance computing.

  3. Lesson 3: Computational Efficiency

    • Understanding strategies for achieving computational efficiency in scientific programming.

  4. Lesson 4: Data Structures

    • Exploring fundamental data structures and their relevance in high-performance computing.

  5. Lesson 5: Problem-Solving Algorithms

    • Introduction to problem-solving algorithms and their implementation in scientific computing.

  6. Lesson 6: Scientific Computation with Python

    • Practical aspects of scientific computation using Python.

  7. Lesson 7: Concurrent Programming

    • Overview of concurrent programming concepts and techniques.

  8. Lesson 8: Parallel and Distributed Programming

    • Understanding parallel and distributed programming for high-performance computing.

  9. Lesson 9: Heterogeneous Programming

    • Exploring programming approaches for heterogeneous computing environments.

  10. Lesson 10: Cloud Computing

    • Introduction to cloud computing and its relevance in high-performance computing.

How to Navigate

  • To access specific lesson materials, click on the corresponding link above.
  • Feel free to explore the course directory to find related documents, code, and assignments.

If you have any questions or need clarification on any topic, don't hesitate to reach out!

Happy learning! 🚀

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