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GPU-Computing-WS2025-26

This repository contains my assignments and project work for the course GPU Computing taught by Prof. Dr. Holger Fröning at Heidelberg University.


📘 Course Overview

The course introduces GPU architecture and programming with CUDA, focusing on performance optimization, memory consistency, and advanced GPU concepts. It also explores alternatives to CUDA through lectures and practical programming exercises.


🗓 Course Schedule

Date Lecture Exercise
16.10.2025 1. Intro Reading / Amdahl
23.10.2025 2. CUDA Kernel launch, data movement
30.10.2025 Traveling
06.11.2025 3. Basic Architecture Global memory
13.11.2025 4. Shared Memory MMULT
20.11.2025 Traveling
27.11.2025 5. Scheduling Optimizations MMULT GPU + Optimizations (Bonus)
04.12.2025 6. Profiling
11.12.2025 7. Particle Methods Reduction
18.12.2025 8. Host Optimizations
25.12.2025 XMAS n-Body + Optimizations (Bonus)
01.01.2026 XMAS
08.01.2026 9. Stencil Codes / OpenACC
15.01.2026 10. Consistency / Coherence Stencil + Optimizations
22.01.2026 11. Advanced GPU Features Exam examples
29.01.2026 12. Future
05.02.2026 Exam

⚙️ Environment

Hardware

  • CPU: AMD EPYC 7302P
  • GPU: NVIDIA RTX 2080

Software

  • OS: Debian 12
  • NVIDIA Driver: 580.65.06
  • CUDA: 13.0

Python

  • Python: 3.12.1
  • NumPy: 2.3.4
  • Pandas: 2.3.3
  • Matplotlib: 3.10.7

📖 Assignment Progress

Week Task Status
01 Reading / Amdahl ✅ Done
02 Kernel launch, data movement ✅ Done
03 Global memory ✅ Done
04 MMULT 🔄 In Progresse
05 MMULT GPU + Optimizations (Bonus)
06 Reduction
07 n-Body + Optimizations (Bonus)
08 Stencil + Optimizations

📜 License

This project is released under the BSD 2-Clause License.
You are free to use, modify, and redistribute this software, with or without modifications, as long as the copyright notice and this disclaimer are retained.

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Course exercises of GPU Computing @ Heidelberg University.

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