HAhack_ml·Nov 18, 2021
You can probably use https://github.com/rapidsai/cudf/tree/main/python/dask_cudf a dask wrapper around cuDF.
In Dask – A flexible library for parallel computing in PythonNVIDIA
cudf
C++2017–2024
NVIDIA / cudf
cudf
cuDF - GPU DataFrame Library
14Distinct people
17Mentions
0Explicit recommenders
9.8KGitHub stars
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What it is
cuDF - GPU DataFrame Library
GitHub
Where it is used
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What people are saying
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Also in these discussions
- nvidia/cuml · linked in 2 of the same discussions
Mentioned in the same Hacker News threads. That is not proof they are substitutes.
This week on Hacker News
Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 6:59:22 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by year17 dated mentions
Observed mentions: 2017-05-08 17:21:53 UTC to 2024-06-02 19:37:01 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2017 | 2017-01-01 00:00:00 UTC | 2018-01-01 00:00:00 UTC | 2 | 1 | 1 |
| 2018 | 2018-01-01 00:00:00 UTC | 2019-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2019 | 2019-01-01 00:00:00 UTC | 2020-01-01 00:00:00 UTC | 8 | 0 | 8 |
| 2020 | 2020-01-01 00:00:00 UTC | 2021-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2021 | 2021-01-01 00:00:00 UTC | 2022-01-01 00:00:00 UTC | 4 | 0 | 4 |
| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 2 | 2 | 0 |
What Hacker News says
4 sourceshttps://github.com/graphistry/pygraphistry + https://github.com/rapidsai/cudf if you're coming from the api / ds side, and GNNs side is more of a "let's chat!" thing for figuring out aligned collaborations (slack/email, all good!)
In An Engineer's View of Venture Capitalists (2001)that project might be abandoned but this strategy is used in nvidia and nvidia adjacent projects (through llvm):
https://github.com/rapidsai/cudf/blob/branch-0.20/python/cud...
https://github.com/gmarkall/numba/blob/master/numba/cuda/com...
>but we also need high level expressibility that doesn't require writing kernels in C
the above are possible because C is actually just a frontend to PTX
https://docs.nvidia.com/cuda/parallel-thread-execution/index...
fundamentally you are not going to ever be able to have a way to write cuda kernels without thinking about cuda architecture anymore so than you'll ever be able to write async code without thinking about concurrency.
In Unifying the CUDA Python EcosystemCudf and Cylon are two execution engines natively supporting Arrow format
https://github.com/rapidsai/cudf
https://github.com/cylondata/cylon
In Apache Arrow 3.0