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cudf | cuDF GPU DataFrame Library | GPU library

 by   rapidsai C++ Version: v22.02.00 License: Apache-2.0

 by   rapidsai C++ Version: v22.02.00 License: Apache-2.0

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kandi X-RAY | cudf Summary

cudf is a C++ library typically used in Hardware, GPU, Numpy, Pandas, Spark applications. cudf has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.
Built based on the Apache Arrow columnar memory format, cuDF is a GPU DataFrame library for loading, joining, aggregating, filtering, and otherwise manipulating data. cuDF provides a pandas-like API that will be familiar to data engineers & data scientists, so they can use it to easily accelerate their workflows without going into the details of CUDA programming.
Support
Support
Quality
Quality
Security
Security
License
License
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kandi-support Support

  • cudf has a medium active ecosystem.
  • It has 4484 star(s) with 586 fork(s). There are 142 watchers for this library.
  • There were 2 major release(s) in the last 6 months.
  • There are 638 open issues and 3684 have been closed. On average issues are closed in 110 days. There are 69 open pull requests and 0 closed requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of cudf is v22.02.00
cudf Support
Best in #GPU
Average in #GPU
cudf Support
Best in #GPU
Average in #GPU

quality kandi Quality

  • cudf has 0 bugs and 0 code smells.
cudf Quality
Best in #GPU
Average in #GPU
cudf Quality
Best in #GPU
Average in #GPU

securitySecurity

  • cudf has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • cudf code analysis shows 0 unresolved vulnerabilities.
  • There are 0 security hotspots that need review.
cudf Security
Best in #GPU
Average in #GPU
cudf Security
Best in #GPU
Average in #GPU

license License

  • cudf is licensed under the Apache-2.0 License. This license is Permissive.
  • Permissive licenses have the least restrictions, and you can use them in most projects.
cudf License
Best in #GPU
Average in #GPU
cudf License
Best in #GPU
Average in #GPU

buildReuse

  • cudf releases are available to install and integrate.
  • Installation instructions, examples and code snippets are available.
  • It has 130902 lines of code, 8588 functions and 428 files.
  • It has high code complexity. Code complexity directly impacts maintainability of the code.
cudf Reuse
Best in #GPU
Average in #GPU
cudf Reuse
Best in #GPU
Average in #GPU
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cudf Key Features

cuDF - GPU DataFrame Library

cudf Examples and Code Snippets

  • Overview
  • Conda
  • what is the most efficient way to do `diff` for a `cudf`
  • how to use tqdm progress bar in dask_cudf and cudf
  • cuPy error : Implicit conversion to a host NumPy array via __array__ is not allowed,
  • searching index with cudf dataframe doesn't work with numpy
  • How to create unique ID column in DASK_CUDF
  • AttributeError: 'cupy.core.core.ndarray' object has no attribute 'iloc'
  • RAPIDS: How to use one dataframe in a UDF called with apply_rows of another dataframe?
  • from numba import cuda, numpy_support and ImportError: cannot import name 'numpy_support' from 'numba'
  • How do I install dask_cudf?
  • Python modified groupby ngroup in cuDF with list comprehension

Overview

import cudf, io, requests
from io import StringIO

url = "https://github.com/plotly/datasets/raw/master/tips.csv"
content = requests.get(url).content.decode('utf-8')

tips_df = cudf.read_csv(StringIO(content))
tips_df['tip_percentage'] = tips_df['tip'] / tips_df['total_bill'] * 100

# display average tip by dining party size
print(tips_df.groupby('size').tip_percentage.mean())

Community Discussions

Trending Discussions on cudf
  • How to install cuDF on google colab with GPU Tesla K80?
  • Is there a way of using the entire memory of my GPU for CUML calculations?
  • Why do I get a CUDA memory error when using RAPIDS in WSL?
  • what is the most efficient way to do `diff` for a `cudf`
  • how to use tqdm progress bar in dask_cudf and cudf
  • cuPy error : Implicit conversion to a host NumPy array via __array__ is not allowed,
  • searching index with cudf dataframe doesn't work with numpy
  • cuDF: an alternative of Pandas Groupby + Shift?
  • How to create unique ID column in DASK_CUDF
  • CUML fit functions throwing cp.full TypeError
Trending Discussions on cudf

QUESTION

How to install cuDF on google colab with GPU Tesla K80?

Asked 2022-Mar-10 at 22:05

I am trying to install cuDF on Google Colab for hours. One of the requirements I should install cuDF with GPU Tesla T4. While google colab gives me every time GPU Tesla K80 and I cannot install cuDF. I tried this snippet of code to check what type of GPU I have every time:

import pynvml

pynvml.nvmlInit()
handle = pynvml.nvmlDeviceGetHandleByIndex(0)
device_name = pynvml.nvmlDeviceGetName(handle)

if device_name != b'Tesla T4':
  raise Exception("""
    Unfortunately this instance does not have a T4 GPU.
    
    Please make sure you've configured Colab to request a GPU instance type.
    
    Sometimes Colab allocates a Tesla K80 instead of a T4. Resetting the instance.

    If you get a K80 GPU, try Runtime -> Reset all runtimes...
  """)
else:
  print('Woo! You got the right kind of GPU!') 

It is too frustrating to get specific type of GPU by google colab because it is kind of a luck. I am asking here to see if someone experienced the same issue, and how was it solved?

ANSWER

Answered 2022-Mar-10 at 22:05

The K80 use Kepler GPU architecture, which is not supported by RAPIDS. Colab itself no longer can run the latest versions of RAPIDS. You can try SageMaker Studio Lab for your Try it Now experience. https://github.com/rapidsai-community/rapids-smsl.

Source https://stackoverflow.com/questions/71294926

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install cudf

Please see the Demo Docker Repository, choosing a tag based on the NVIDIA CUDA version you’re running. This provides a ready to run Docker container with example notebooks and data, showcasing how you can utilize cuDF.

Support

Please see our guide for contributing to cuDF.

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