RRepoGEO

REPOGEO REPORT · LITE

Infatoshi/cuda-course

Default branch master · commit 79681bfd · scanned 6/18/2026, 7:27:42 AM

GitHub: 3,773 stars · 655 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
2 / 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 Infatoshi/cuda-course, 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

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

OVERALL DIRECTION
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    A comprehensive, free, and open-source course on NVIDIA CUDA programming, covering GPU kernel optimization, PyTorch extensions, and Triton for high-performance computing.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT License) in the repository root to clearly state the terms under which the course content is distributed.

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 Infatoshi/cuda-course
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
CUDA C/C++ Basics
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. CUDA C/C++ Basics · recommended 1×
  2. Udacity's Intro to Parallel Programming · recommended 1×
  3. Coursera's Parallel Programming in CUDA C/C++ · recommended 1×
  4. OpenACC Fundamentals · recommended 1×
  5. Intel oneAPI DPC++ Essentials · recommended 1×
  • CATEGORY QUERY
    Looking for a structured course to learn optimizing code for graphics processors.
    you: not recommended
    AI recommended (in order):
    1. CUDA C/C++ Basics
    2. Udacity's Intro to Parallel Programming
    3. Coursera's Parallel Programming in CUDA C/C++
    4. OpenACC Fundamentals
    5. Intel oneAPI DPC++ Essentials

    AI recommended 5 alternatives but never named Infatoshi/cuda-course. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I accelerate deep learning operations on parallel computing hardware?
    you: not recommended
    AI recommended (in order):
    1. PyTorch (pytorch/pytorch)
    2. TensorFlow (tensorflow/tensorflow)
    3. JAX (google/jax)
    4. MXNet (apache/mxnet)
    5. cuDNN
    6. OpenVINO (openvinotoolkit/openvino)

    AI recommended 6 alternatives but never named Infatoshi/cuda-course. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 Infatoshi/cuda-course?
    pass
    AI named Infatoshi/cuda-course explicitly

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

  • If a team adopts Infatoshi/cuda-course in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Infatoshi/cuda-course 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 Infatoshi/cuda-course solve, and who is the primary audience?
    pass
    AI did not name Infatoshi/cuda-course — 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?

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Infatoshi/cuda-course — 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