For the final lab, you will complete a project of your choice. This should be about the size of one of the other labs.
The project for this course is very open-ended. You are welcome to propose any topic that is related to the class material. A few options include:
- Implementing and optimizing an algorithm of your choice in HLS.
- Implementing an HLS core and incorporating it into a larger system related to your research.
- Exploring, improving, or evaluating some aspect of HLS tools (open-source or commercial).
- Exploring, improving, or evaluating the growing space of DSL to HLS compilers.
- (One group) Work on LLM prompts for HLS, and evaluate how well ChatGPT or other models can generate HLS code.
You can work alone, or in a group of two or more with permission from the instructor. If you are working in a group, the project scope should be scaled accordingly. Your class presentation will also be longer.
Project Deliverables
There will be three deliverables for the project:
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An in-class presentation. You will present your project in a 5 minute presentation in class on Apr 8th or 10th. Prepare a few slides about: 1) what you are working on 2) challenges or anticipated challenges, and you and how you plan to mitigate them, and 3) what results you plan to collect, or any preliminary results you have.
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Your code or other work products in a lab_project folder in your Github repo, which should be submitted using the tag lab6_submission.
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A 1-2 page report, included in the lab-project folder, describing what you accomplished, challenges, and results.