RRepoGEO

REPOGEO REPORT · LITE

PaddleJitLab/CUDATutorial

Default branch develop · commit 640ff87f · scanned 5/31/2026, 3:57:46 PM

GitHub: 1,001 stars · 104 forks

AI VISIBILITY SCORE
22 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
1 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface PaddleJitLab/CUDATutorial, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Add a concise English summary to the top of the README

    Why:

    CURRENT
    # CUDATutorial 
   
从零开始学习 CUDA 高性能编程，从入门到放弃，哦不！一起来边学习，边打笔记，日拱一卒！
    COPY-PASTE FIX
    # CUDATutorial

This repository provides a comprehensive, self-paced tutorial for learning CUDA high-performance programming, from fundamental concepts to advanced kernel optimization techniques. It's designed for beginners and developers looking to master GPU computing.

从零开始学习 CUDA 高性能编程，从入门到放弃，哦不！一起来边学习，边打笔记，日拱一卒！
  • mediumabout#2
    Add the project homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://cuda.keter.top/
  • mediumtopics#3
    Expand repository topics to include more specific keywords

    Why:

    CURRENT
    cuda-programming, deep-learning
    COPY-PASTE FIX
    cuda-programming, deep-learning, gpu-optimization, high-performance-computing, cuda-tutorials, kernel-optimization, parallel-programming

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface PaddleJitLab/CUDATutorial
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Stack Overflow
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Stack Overflow · recommended 2×
  2. NVIDIA Developer Forums · recommended 2×
  3. NVIDIA CUDA Toolkit · recommended 1×
  4. Udacity's "Intro to Parallel Programming" (CS344) · recommended 1×
  5. "Professional CUDA C Programming" · recommended 1×
  • CATEGORY QUERY
    How to begin learning CUDA programming for high-performance computing from scratch?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA CUDA Toolkit
    2. Udacity's "Intro to Parallel Programming" (CS344)
    3. "Professional CUDA C Programming"
    4. "CUDA by Example: An Introduction to General-Purpose GPU Programming"
    5. NVIDIA Deep Learning Institute (DLI)
    6. Stack Overflow
    7. NVIDIA Developer Forums

    AI recommended 7 alternatives but never named PaddleJitLab/CUDATutorial. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find tutorials on optimizing CUDA kernel performance for deep learning applications?
    you: not recommended
    AI recommended (in order):
    1. cuDNN
    2. TensorRT
    3. NVIDIA Deep Learning Examples
    4. NVIDIA GTC
    5. CUDA by Example
    6. Udacity
    7. Coursera
    8. NVIDIA Developer Blog
    9. Medium
    10. Towards Data Science
    11. PyTorch
    12. TensorFlow
    13. Stack Overflow
    14. NVIDIA Developer Forums

    AI recommended 14 alternatives but never named PaddleJitLab/CUDATutorial. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of PaddleJitLab/CUDATutorial?
    pass
    AI did not name PaddleJitLab/CUDATutorial — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts PaddleJitLab/CUDATutorial in production, what risks or prerequisites should they evaluate first?
    pass
    AI named PaddleJitLab/CUDATutorial explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo PaddleJitLab/CUDATutorial solve, and who is the primary audience?
    pass
    AI did not name PaddleJitLab/CUDATutorial — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of PaddleJitLab/CUDATutorial. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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HTML
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PaddleJitLab/CUDATutorial — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite