This is a list of all pages, links, etc., we covered from the beginning until the end of our project. This is our in-detail documentation. Our front page on the website and the project abstract (immediately below) explains the What, Why, and How's of our project.

Project Abstract

For our project, our team focused on analyzing the performance of two different Machine Learning algorithms that were designed to run on the CPU and GPU.

To perform these computations our team used CUDA, a closed-source program developed by Nvidia that contains hardware and software support for General-Purpose computing on Nvidia GPUs. The algorithms were ran several times on the CPU vs. the CPU and GPU with sample datasets changing in size. Other variables such as the GPU core temp, the CPU core temp, Power draw, Memory usage, CPU/GPU usage were monitored.

Our findings explain the architectural differences between the CPU and GPU, our complete methodology, the hardware and software support of CUDA, and possible explanations for the runtime differences in both scripts over the CPU vs. the CPU and GPU. We chose to package our most valuable information from our learning into a zine. You can view it here. Commenting is enabled on the zine, so you can add any comments or questions you might have about our work. You can also contribute more information to the zine via commenting or sending us a direct email at [email protected] or [email protected]. We will talk about how to contribute in the paragraph below.

For those who are interested in contributing to this project, you can learn more on how to build on it by clicking here. We will also point out which pages on here are most important for those who are interested in contributing.

In-Detail Documentation

This is the documentation we have beyond what is packaged in our zine. If you've read our zine and are interested in contributing or just want to see what happened behind the scenes to make it, you're in the right place!

Ideation

Kickoff (Project Ideation)

📄 Project Proposal (Link to drive with original and updated project proposals, updated after meeting with Jon)

Resources

• These are the resources we consulted first before our deep dive. List made on Nov 13th.
• If you want to see the resources we consulted during our deep dive, look under 'Caitlin Meeting Prep' and 'Maeve meeting prep' notes. We also have the resources we used in our Zine under our 'references' section here.

Deep Dive

Schedule (Contains project schedule, benchmarks/goals set every week)

Under schedule:

• 11/24 Meeting Plan & Notes
  • Caitlin Meeting Prep
  • Maeve Meeting Prep
    • All of the resources we consulted during our deep dive are under 'Caitlin Meeting Prep' and 'Maeve Meeting Prep'! Look here if you want more information that was not covered in the Zine (PCI-Express Bus information, HSA Architecture)
    • We also have our consolidated notes under '11/24 Meeting Plan & Notes' which you can look at if you want.
• Machine Learning Code
  • This is the code we used to perform our tests! Look at this if you want to contribute.
• Testing Methodology & Results
  • Look at this if you want to see what kinds of variables we kept track of, and our initial results. Also look at this if you want to contribute. Note that this information is also in our Zine under our 'Methodology' Section (link here)
  • Process Ideation
    • Look at this if you're curious about how we constructed our methodology!