Purdue-SoCET/tensor-core
Jan 2026 – Jan 2026
1 Month active
Languages Used
MarkdownVerilog
Technical Skills
Verilogcoding standardsdocumentationhardware designstyle guide adherence
Malcolm desktop OVF
PROFILE
Malcolm Desktop Ovf
Contributed to the Purdue-SoCET/tensor-core repository by developing and delivering a comprehensive AI Hardware SystemVerilog Style Guide aimed at standardizing coding practices across the hardware design team. The work focused on improving code readability, maintainability, and team collaboration by establishing clear guidelines and documentation. Using Verilog and Markdown, the developer ensured the style guide was both technically robust and accessible, facilitating faster onboarding and more consistent code reviews. Minor refinements, including typo corrections, were incorporated to enhance accuracy and clarity. This foundational documentation supports scalable contributions and sets a baseline for coding standards within the AI hardware development workflow.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
1
Lines of code
346
Activity Months1
Your Network
25 peopleShared Repositories
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Joseph Alan GhanemMember
Haejune KwonMember
Nicha MuninnimitMember
Pierce Yungjoon JohnsonMember
Work History
January 2026
2 Commits • 1 Features
Jan 1, 2026January 2026 — Monthly summary focusing on key accomplishments for Purdue-SoCET/tensor-core. Delivered a comprehensive AI Hardware SystemVerilog Style Guide to standardize coding practices, improve readability, maintainability, and collaboration across the AI Hardware team. This foundation supports faster onboarding, more consistent reviews, and scalable contributions. Minor polish completed via typo fixes to ensure accuracy.
2 Commits • 1 Features
Jan 1, 2026January 2026 — Monthly summary focusing on key accomplishments for Purdue-SoCET/tensor-core. Delivered a comprehensive AI Hardware SystemVerilog Style Guide to standardize coding practices, improve readability, maintainability, and collaboration across the AI Hardware team. This foundation supports faster onboarding, more consistent reviews, and scalable contributions. Minor polish completed via typo fixes to ensure accuracy.
January 2026
Activity
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance100.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownVerilog
Technical Skills
Verilogcoding standardsdocumentationhardware designstyle guide adherence
Repositories Contributed To
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