Source-level debugging for hardware generator frameworks
Abstract/Contents
- Abstract
- Historically, hardware was specified manually in hardware description languages such as SystemVerilog and VHDL. Recent progress on high-level hardware generator frameworks has shown to significantly increase the design productivity. These frameworks use software engineering constructs to reduce the repetition required to express complex designs and enable more compossibility. However, these benefits are undermined by a lack of debugging infrastructure, requiring hardware designers to debug generated, usually incomprehensible, RTL code. In this dissertation, I introduce a framework that connects modern software source-level debugging frameworks to RTL created from hardware generators. This framework uses several novel algorithms to minimize the RTL simulation overhead while offering a complete debugging experience at the source-level. I will discuss the insights and lessons learned from building such a framework and show the benefits when using it to debug large hardware systems.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2022; ©2022 |
| Publication date | 2022; 2022 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Zhang, Keyi |
|---|---|
| Degree supervisor | Horowitz, Mark (Mark Alan) |
| Thesis advisor | Horowitz, Mark (Mark Alan) |
| Thesis advisor | Asgar, Zain |
| Thesis advisor | Barrett, Clark |
| Degree committee member | Asgar, Zain |
| Degree committee member | Barrett, Clark |
| Associated with | Stanford University, Computer Science Department |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Keyi Zhang. |
|---|---|
| Note | Submitted to the Computer Science Department. |
| Thesis | Thesis Ph.D. Stanford University 2022. |
| Location | https://purl.stanford.edu/wb864cp0807 |
Access conditions
- Copyright
- © 2022 by Keyi Zhang
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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