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RAPIDS AI

RAPIDS is a suite of software libraries for executing end-to-end data science & analytics pipelines entirely on GPUs.

  • RAPIDS Releases
  • DataFrames
  • Machine Learning
  • Data Visualization
  • Graph Analytics
  • NLP
  • Learn More
  • cuSpatial 23.04

    cuSpatial 23.04

    GeoSeries, Intersection, Spatial Predicates, and more!
    Go to the profile of Alex Ravenel
    Alex Ravenel
    May 23
    Intro to Graph Neural Networks with cuGraph-PyG

    Intro to Graph Neural Networks with cuGraph-PyG

    Accelerate GNN training with the power of cuGraph and PyG
    Go to the profile of Alex Barghi
    Alex Barghi
    May 11
    RAPIDS Release 23.04

    RAPIDS Release 23.04

    RAPIDS 23.04 is out! We are excited about this release, which includes major updates to cuSpatial, continued improvements to graph neural…
    Go to the profile of Alex Ravenel
    Alex Ravenel
    May 9
    RAPIDS Release 23.02

    RAPIDS Release 23.02

    First Release of the Year
    Go to the profile of Paul Mahler
    Paul Mahler
    Mar 9
    Faster Resampling with Imbalanced-learn and cuML

    Faster Resampling with Imbalanced-learn and cuML

    Authors (alphabetical): Nick Becker (NVIDIA), Dante Gama Dessavre (NVIDIA), and Corey Nolet (NVIDIA)
    Go to the profile of Nick Becker
    Nick Becker
    Feb 22
    Easy CPU/GPU Arrays and DataFrames — Run your Dask code where you’d like

    Easy CPU/GPU Arrays and DataFrames — Run your Dask code where you’d like

    Authors: Rick Zamora and Ben Zaitlen
    Go to the profile of Rick Zamora
    Rick Zamora
    Feb 1
    Faster Topic Modeling with BERTopic and RAPIDS cuML

    Faster Topic Modeling with BERTopic and RAPIDS cuML

    Authors (alphabetical): Nick Becker (NVIDIA), Dante Gama Dessavre (NVIDIA), Maarten Grootendorst (BERTopic), and Corey Nolet (NVIDIA)
    Go to the profile of Maarten Grootendorst
    Maarten Grootendorst
    Jan 19
    PyTorch + Rapids RMM: Maximize the Memory Efficiency of your Workflows

    PyTorch + Rapids RMM: Maximize the Memory Efficiency of your Workflows

    GPU-accelerated machine learning is producing fascinating results across a wide range of fields on a seemingly daily basis. While neural…
    Go to the profile of Ashwin Srinath
    Ashwin Srinath
    Jan 12
    Query cuSpatial about your (Spatial) Relationship

    Query cuSpatial about your (Spatial) Relationship

    Authors: Thomson Comer, Michael Wang and Mark Harris
    Go to the profile of Michael Wang
    Michael Wang
    Dec 16, 2022
    RAPIDS 22.12 Release

    RAPIDS 22.12 Release

    Making sure your holiday season is full of presents.
    Go to the profile of Nick Becker
    Nick Becker
    Dec 14, 2022
    RAPIDS Memory Manager Pool: Speed up your memory allocations

    RAPIDS Memory Manager Pool: Speed up your memory allocations

    By: Vibhu Jawa and Randy Gelhausen
    Go to the profile of Vibhu Jawa
    Vibhu Jawa
    Dec 12, 2022
    cuSpatial Makes Progress Toward a Full-Featured Spatial Analytics Library

    cuSpatial Makes Progress Toward a Full-Featured Spatial Analytics Library

    by Michael Wang, Thomson Comer, Mark Harris, Ben Jarmak
    Go to the profile of Michael Wang
    Michael Wang
    Dec 1, 2022
    Fast Data Pipelining with String UDFs

    Fast Data Pipelining with String UDFs

    Ever wish you could apply your own custom functions to string data columns in cuDF? Well, now you can! Recently cuDF introduced support for…
    Go to the profile of Brandon B. Miller
    Brandon B. Miller
    Nov 28, 2022
    Announcing RAPIDS 22.10

    Announcing RAPIDS 22.10

    Serving cake, pip, and Windows at our fourth birthday party!
    Go to the profile of Sophie Watson
    Sophie Watson
    Oct 26, 2022
    Extending Numba’s CUDA target with the high-level API

    Extending Numba’s CUDA target with the high-level API

    Numba is the Just-In-Time compiler used in RAPIDS cuDF to implement high-performance User-Defined Functions (UDFs) by turning user-supplied…
    Go to the profile of Graham Markall
    Graham Markall
    Oct 26, 2022
    Announcing the General Availability of Dask-SQL on GPUs

    Announcing the General Availability of Dask-SQL on GPUs

    We’re excited to announce General Availability of Dask-SQL on GPUs! This matters to you because it means more interoperability between data…
    Go to the profile of Randy Gelhausen
    Randy Gelhausen
    Oct 6, 2022
    Announcing RAPIDS on WSL for Windows

    Announcing RAPIDS on WSL for Windows

    We are announcing General Availability for RAPIDS on Windows 11 via WSL, the Windows Subsystem for Linux. Usability is now part of our…
    Go to the profile of Paul Mahler
    Paul Mahler
    Sep 21, 2022
    RAPIDS release blog 22.08

    RAPIDS release blog 22.08

    Improved performance, new features, extended functionality and greater stability
    Go to the profile of Sophie Watson
    Sophie Watson
    Sep 8, 2022
    RAPIDS release blog 22.06

    RAPIDS release blog 22.06

    RAPIDS 22.06 brings new support for massive graphs, and expands the support for Multi-Node Multi-GPU algorithms.
    Go to the profile of Sophie Watson
    Sophie Watson
    Jun 30, 2022
    RAPIDS Release 22.04

    RAPIDS Release 22.04

    Scaling and simplifying developer experience
    Go to the profile of Sophie Watson
    Sophie Watson
    Apr 14, 2022
    Accelerating Topic modeling with RAPIDS and BERT models

    Accelerating Topic modeling with RAPIDS and BERT models

    Topic modeling for text processing, Deep Learning based embedding creation, reduction, and clustering on GPUs.
    Go to the profile of Vibhu Jawa
    Vibhu Jawa
    Mar 15, 2022
    RAPIDS Release 22.02

    RAPIDS Release 22.02

    Bringing more integration points, expanding functionality, and improving performance.
    Go to the profile of Sophie Watson
    Sophie Watson
    Feb 9, 2022
    RAPIDS Release 21.12

    RAPIDS Release 21.12

    RAPIDS 21.12 strengthens the GPU analytics foundation, improves ecosystem compatibility, and brings new functionality and integrations.
    Go to the profile of Nick Becker
    Nick Becker
    Dec 16, 2021
    Time Moves Forward — RAPIDS Hits Its Three Year Milestone

    Time Moves Forward — RAPIDS Hits Its Three Year Milestone

    Release 21.10 continues to work toward the vision of making GPU speed available to everyone
    Go to the profile of Paul Mahler
    Paul Mahler
    Oct 11, 2021
    Accelerating TF-IDF for Natural Language Processing with Dask and RAPIDS

    Accelerating TF-IDF for Natural Language Processing with Dask and RAPIDS

    Learn how to use RAPIDS and Dask to make NLP pipelines for indexing, summation, and text clustering much faster.
    Go to the profile of Vibhu Jawa
    Vibhu Jawa
    Sep 16, 2021
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