GPU-accelerated Exact K-Nearest Neighobor with Cosine as distance metric

• No external libraries (cuBLAS, cuGRAPH, etc.)
• You can either use Unified Memory or Unmanaged Memory (classic way)
• Copy from existing knn projects will result in immediate reject (better to do less, but do it yourself! :D )
• Submission to the contest must contain:
  • Running source-code
  • Presentation slides (pdf/pptx)
  • Project report (we like graphs, tables, figures! aka. no screenshots of the runtimes from the terminal) explain:
    • your reasoning,
    • the design that you have employed,
    • the options that you evaluated (you could have multiple version of your algorthims for the differnt optimizations that you have developed),
    • data structures
• Show your results for all the settings in the main() function
• You can decide to explore reduced or mixed precision arithmetic operations --> only as an addition to the exact solution
• Download this repository locally and upload it as a private repository, invite me to the private one: ian-ofgod

• 17.11.2023 @23:59 Milan

  • Subscribe to the contest by sending an email to: [email protected] with your name and possibily your teammate.
  • Object: [hpdga-fall23] subscription fullname1 - fullname2
  • Group of max 2 people (you can do it alone if you wish)
  • If you want to be assinged a teammate just drop me an email and we will se if someone has expressed the same desire.

• 31.12.2023 @23.59 Milan

  • send an email with the overall submission (slides + report + source-code)
  • naming convetion for the files:
    • hpdga-fall23-report-name1surname1-name2surname2
    • hpdga-fall23-slides-name1surname1-name2surname2
    • hpdga-fall23-code-name1surname1-name2surname2