Department of
Computer Science and Engineering

Programming Assignments

• PA0: Hello CUDA
• PA1: Experiments with Matrix Addition
• PA2: Matrix Multiplication
• PA3: Missing Values (KNN)
• PA3: Multiple GPU

Course Projects

• 5 Min Presentation (Week 6 and 8)
  • Intro to the problem
  • Status of Sequential implementation
• 20 Min Presentation (Weeks 10, 11, 12)
  • Background,
  • Review of the Literature
  • Sequential Results (and graphs)
  • Approach to the GPU implementation
• 10 Min Presentations (Weeks 14, 15)
  • Brief Intro to the problem
  • My Parallel Approach (and what may have changed from what I presented last time)
  • Parallel Results
  • Comparsion of Parallel and Sequential
• Paper. (Final Exam Period)

Presentation Numbers - and topics

1. Daniel Lopez - Capsule NN Methods
2. Connor Scully-Allison - Multi Gpu Implementation of Robust and Sparse Fuzzy K-Means Clustering
3. Blanca Miller - Non-linear Model Predictive Control for Autonomous Driving
4. Steven Fisher - Weighted Depth FIrst Search
5. Chad Adams - Maze Generation
6. Syed Zawad - Randomized Quantum Gates Benchmarking on the GPU
7. Janelle Blankenburg - GPU-RRT for Autonomous Navigation
8. Aavaas Gajurel - Accelerate arbitrary feed forward neural networks
10. Eric Li - GPU Norta
11. Hannah Munoz - Snow and Could Cover Estimates