SaaSHub helps you find the best software and product alternatives Learn more →
Cudf Alternatives
Similar projects and alternatives to cudf
-
chia-blockchain
Chia blockchain python implementation (full node, farmer, harvester, timelord, and wallet)
-
CodeRabbit
CodeRabbit: AI Code Reviews for Developers. Revolutionize your code reviews with AI. CodeRabbit offers PR summaries, code walkthroughs, 1-click suggestions, and AST-based analysis. Boost productivity and code quality across all major languages with each PR.
-
-
-
jax
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
-
Apache Arrow
Apache Arrow is the universal columnar format and multi-language toolbox for fast data interchange and in-memory analytics
-
-
annoy
Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk
-
Nutrient
Nutrient – The #1 PDF SDK Library, trusted by 10K+ developers. Other PDF SDKs promise a lot - then break. Laggy scrolling, poor mobile UX, tons of bugs, and lack of support cost you endless frustrations. Nutrient’s SDK handles billion-page workloads - so you don’t have to debug PDFs. Used by ~1 billion end users in more than 150 different countries.
-
-
Kedro
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
-
-
-
-
-
-
-
-
-
-
PSRayTracing
A (modern) C++ implementation of the Peter Shirley Ray Tracing mini-books (https://raytracing.github.io). Features a clean project structure, perf. improvements (compared to the original code), multi-core rendering, and more.
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
cudf discussion
cudf reviews and mentions
-
Unleashing GPU Power: Supercharge Your Data Processing with cuDF
cuDF Documentation
-
This Week In Python
cudf – GPU DataFrame Library
- cuDF – GPU DataFrame Library
- CuDF – GPU DataFrame Library
-
A Polars exploration into Kedro
The interesting thing about Polars is that it does not try to be a drop-in replacement to pandas, like Dask, cuDF, or Modin, and instead has its own expressive API. Despite being a young project, it quickly got popular thanks to its easy installation process and its “lightning fast” performance.
-
Why we dropped Docker for Python environments
Perhaps the largest for package size is the NVIDIA developed rapids toolkit https://rapids.ai/ . Even still adding things like pandas and some geospatial tools, you rapidly end up with an image well over a gigabyte, despite following cutting edge best practice with docker and python.
-
Introducing TeaScript C++ Library
Yes sure, that is how OpenMP does; but on the other side: you seem to already do some basic type inference, and building an AST, no? Then you know as well the size and type of your vectors, and can execute actions in parallel if there is enough data to be worth parallelizing. Is there anyone who don't want their code to execute faster if it is possible? Those that do work in big data domain do use threads and vectorized instructions without user having to type in any directive; just import different library. Example, numpy or numpy with cuda backend, or similar GPU accelerated libraries like cudf.
-
[D] Can we use Ray for distributed training on vertex ai ? Can someone provide me examples for the same ? Also which dataframe libraries you guys used for training machine learning models on huge datasets (100 gb+) (because pandas can't handle huge data).
Not the answer about Ray: you could use rapids.ai. I'm using it for for dataframe manipulation on GPU
-
Story of my life
To put Data Analytics on GPU Steroids, Try RAPIDS cudf https://rapids.ai/
-
Artificial Intelligence in Python
You can scope out https://rapids.ai/. Nvidia's AI toolkits. They have some handy notebooks to poke at to get you started.
-
A note from our sponsor - SaaSHub
www.saashub.com | 18 Feb 2025
Stats
rapidsai/cudf is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of cudf is C++.