Name
Abstract | ||
|---|---|---|
Google Colab is a cloud Jupyter notebook widespread used to teach machine learning by writing text explanations and Python codes through the browser. This work introduces new Colab extensions to teach logic circuit design, Verilog language, processor, and GPU architectures. Colab allows us to share reproducible experiments on the Web. The students become motivated to do laboratory assignments without download/configure software packages and dependencies on their computers. Furthermore, almost all universities had to shut down due to the COVID-19 pandemic, forcing us to adapt to virtual learning scenarios. Colab provides portability and accessibility since it can even run on smartphones. The lab assignments include intermediate guided exercises, text explanations, figures, online quizzes, problem sets, and basic hands-on tasks. We develop a simple setup for Icarus Verilog, PyEDA, CUDA, Valgrind, and Gem5 frameworks. This work presents Verilog teaching and computer architecture simulation insights by using Valgrind and Gem5, and GPU computer architecture profiling at the thread and instruction assembly level. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ISCAS51556.2021.9401151 | 2021 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS) |
DocType | ISSN | Citations |
Conference | 0271-4302 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael Canesche | 1 | 1 | 2.71 |
| Lucas Braganca | 2 | 0 | 0.68 |
| Omar Paranaiba Vilela Neto | 3 | 0 | 0.34 |
| Jose A. Nacif | 4 | 0 | 0.68 |
| Ricardo Ferreira | 5 | 49 | 13.81 |