RRepoGEO

REPOGEO REPORT · LITE

NVIDIA/cccl

Default branch main · commit c3ae0c9b · scanned 6/24/2026, 4:37:00 AM

GitHub: 2,395 stars · 414 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
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 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 NVIDIA/cccl, 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
    Reposition README opening to emphasize unification

    Why:

    CURRENT
    Welcome to the CUDA Core Compute Libraries (CCCL) where our mission is to make CUDA more delightful.
    COPY-PASTE FIX
    The CUDA Core Compute Libraries (CCCL) is the unified home for essential CUDA C++ libraries, including Thrust, CUB, and libcudacxx, designed to make CUDA development more delightful and efficient.
  • mediumabout#2
    Update repository description to reflect unification

    Why:

    CURRENT
    CUDA Core Compute Libraries
    COPY-PASTE FIX
    The unified NVIDIA CUDA C++ Core Compute Libraries (CCCL), bringing together Thrust, CUB, and libcudacxx for high-performance GPU programming.
  • lowlicense#3
    Clarify license information in README

    Why:

    COPY-PASTE FIX
    CCCL is licensed under [Specify License(s) here, e.g., a custom NVIDIA license or a combination of licenses for its components]. Please see the LICENSE file for full details.

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 NVIDIA/cccl
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
CUDA C++
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. CUDA C++ · recommended 2×
  2. Kokkos · recommended 2×
  3. Thrust · recommended 2×
  4. OpenCL C++ API · recommended 2×
  5. SYCL · recommended 1×
  • CATEGORY QUERY
    What C++ libraries simplify writing high-performance parallel algorithms for GPU acceleration?
    you: not recommended
    AI recommended (in order):
    1. CUDA C++
    2. SYCL
    3. Intel oneAPI DPC++
    4. hipSYCL
    5. OpenMP
    6. Kokkos
    7. Thrust
    8. ROCm
    9. HIP
    10. OpenCL C++ API

    AI recommended 10 alternatives but never named NVIDIA/cccl. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Recommendations for C++ abstractions to build efficient and safe GPU compute applications?
    you: not recommended
    AI recommended (in order):
    1. CUDA C++
    2. SYCL (oneAPI DPC++)
    3. Kokkos
    4. Thrust
    5. alpaka
    6. OpenCL C++ API

    AI recommended 6 alternatives but never named NVIDIA/cccl. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 NVIDIA/cccl?
    pass
    AI named NVIDIA/cccl explicitly

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

  • If a team adopts NVIDIA/cccl in production, what risks or prerequisites should they evaluate first?
    pass
    AI named NVIDIA/cccl 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 NVIDIA/cccl solve, and who is the primary audience?
    pass
    AI named NVIDIA/cccl explicitly

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

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NVIDIA/cccl — 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