RAPIDS Docs - Notices

Changes to RAPIDS branching strategy in 25.08

Mon, 05 May 2025 00:00:00 +0000

Overview

RAPIDS will be migrating to a new branching strategy for the 25.08 release. The new strategy will use a single long-lived branch called main, which all pull requests should target. In preparation for a release, a release branch will be created from main and any remaining pull requests for that release should be merged into the release branch.

Releases and hot fixes will be tagged from the release branch.

This new strategy will be piloted on several RAPIDS libraries (rapidsai/rmm, rapidsai/kvikio, and rapidsai/cugraph-gnn) during the 25.08 development cycle. Migrations will begin shortly after the 25.06 release. After the 25.08 release, the new strategy will be implemented across all RAPIDS libraries.

Impact

Below is a table comparing the current and new branching strategies. Here, the current release is YY.MM (e.g. 25.06) and we denote the next release as <YY.MM-next> (e.g. 25.08).

Aspect	Current (25.06)	New Branching Strategy (25.08+)
Default Branch	Switched per release (e.g. `branch-YY.MM`, then `branch-<YY.MM-next>`)	Always `main` (latest and greatest)
Feature PRs	Target current default branch; retarget manually if moving to a different release	Always target `main`. During release preparation, pull requests may need to be re-targeted to the release branch.
Release Branching	No specific branch, `branch-YY.MM` is the release branch	Create `release/YY.MM` for releases, used during burndown & code freeze
Burndown Process	`branch-<YY.MM-next>` is created	Bump `main` to `<YY.MM-next>.00`, tag `v<YY.MM-next>.00a`, create branch `release/YY.MM`, enable forward merges from `release/YY.MM` → `main`
Code Freeze	Only admin-merges to `branch-YY.MM`	Only admin-merges to `release/YY.MM`
Release	Merge `branch/YY.MM` → `main`; tag `vYY.MM.00` on `main`	Merge `release/YY.MM` → `main`; disable forward-merges from `release/YY.MM` → `main`; tag `vYY.MM.00` on `release/YY.MM`
Hotfixes	Cherry-pick directly onto `branch-YY.MM`, follow release process	Create branch `hotfix/YY.MM` from pre-tag commit on `release/YY.MM`, open PRs to `release/YY.MM` and `main`, follow release process
Tooling	Ops-bot for forward-mergers, release scripts	Minimal custom tooling; leverage standard GitHub workflows

External repositories that depend on RAPIDS shared-workflows should be updated to use the main branch or new tags for each release. The RAPIDS team will work with external repositories to ensure a smooth transition.

Dropping of Publishing cuGraph-DGL Packages in RAPIDS Release v25.08

Fri, 25 Apr 2025 00:00:00 +0000

Overview

RAPIDS will stop publishing cuGraph-DGL packages in RAPIDS Release v25.08. The RAPIDS 25.06 release will be the last release to include cuGraph-DGL. As part of release 25.08, all remaining code for the cuGraph-DGL library will be removed from the cuGraph and cuGraph-GNN GitHub repositories.

Impact

Development of cuGraph-DGL will be terminated and no new packages will be published.

Dropping of Publishing cuSpatial Packages in RAPIDS Release v25.06

Wed, 09 Apr 2025 00:00:00 +0000

Overview

RAPIDS will stop publishing cuSpatial packages in RAPIDS Release v25.06, scheduled for June 05, 2025. Development for the cuSpatial repository will be paused and no new packages will be published.

Impact

Development for the cuSpatial repository will be paused and no new packages will be published. cuSpatial will be dropped from the rapids conda metapackage and RAPIDS Docker containers.

Moving older RAPIDS conda packages to a `legacy` label

Wed, 09 Apr 2025 00:00:00 +0000

Overview

RAPIDS will move certain older conda packages in the rapidsai conda channel under a new label: legacy. These packages will still be available by adding -c rapidsai/label/legacy to installation and search commands.

By moving these packages out of the main portion of the channel, newer RAPIDS conda environments will be solvable with channel_priority: strict, speeding up environment solve times and providing stronger correctness guarantees.

All RAPIDS conda install commands for RAPIDS versions v23.04+ will continue to work without any user intervention.

This change will occur concurrently with the release of RAPIDS v25.04.

Impact

RAPIDS environments installed using conda or mamba, for environments older than RAPIDS v23.04 will fail to install unless -c rapidsai/label/legacy is added to the installation command.

e.g. if you are creating an environment like:

mamba create -n rapids-23.02 -c rapidsai -c conda-forge -c nvidia rapids=23.02 python=3.10 'cuda-version>=11.4,<=11.8'

you will need to instead run

mamba create -n rapids-23.02 -c rapidsai -c rapidsai/label/legacy -c conda-forge -c nvidia rapids=23.02 python=3.10 'cuda-version>=11.4,<=11.8'

Deprecation of cuml-cpu in favor of cuml.accel

Mon, 31 Mar 2025 00:00:00 +0000

Overview

The cuml-cpu package is being deprecated in favor of cuml.accel, cuML’s new Zero Code Change Acceleration layer. The final release of cuml-cpu will be version 25.04. This change is part of RAPIDS’ ongoing effort to provide more efficient and maintainable solutions for CPU acceleration.

Impact

The cuml-cpu package will be deprecated starting with RAPIDS 25.04
The final release of cuml-cpu will be version 25.04
Users are encouraged to migrate to cuml.accel for CPU acceleration
No immediate action is required for users of cuml-cpu, but migration planning should begin

Users are encouraged to explore cuml.accel as their new solution for CPU acceleration. Find more information at: rapids.ai/cuml-accel

RAPIDS 25.02 replaces CUDA 12.5 with CUDA 12.8 in our Docker Images

Mon, 03 Feb 2025 00:00:00 +0000

Overview

RAPIDS is removing support for CUDA 12.5 Docker containers in Release v25.02, and will cease publishing CUDA 12.5 Docker containers before the v25.02 release. The CUDA 12.5 containers will be replaced by CUDA 12.8 containers. We are continuing support for CUDA 11.8 and 12.0 containers.

Impact

Effective RAPIDS v25.02 release, RAPIDS will cease distribution of CUDA 12.5 Docker containers. RAPIDS will support CUDA 11.8, 12.0, and 12.8 Docker containers. Users who still wish to use CUDA 12.5 (or other versions in the CUDA 11.x or 12.x series) may continue to use RAPIDS via conda or pip.

Removing cugraph-ops from RAPIDS

Fri, 10 Jan 2025 00:00:00 +0000

Overview

RAPIDS will stop releasing cugraph-ops in 25.02, including the libcugraphops and pylibcugraphops packages. The graph sampling code previously used by cuGraph has been directly integrated into cuGraph. The equivariant neural network primitives have been migrated to BioNeMo, with the front-end package now available as cuEquivariance. The GNN aggregation primitives will be relocated to a new destination soon.

Impact

The GNN convolutional layers in the cugraph_dgl.nn and cugraph_pyg.nn modules will be temporarily removed. They will be reintroduced at a later time.

Dropping Support for Python v3.9 and adding Python 3.12 Support in v24.10

Thu, 17 Oct 2024 00:00:00 +0000

Overview

RAPIDS is dropping support for Python 3.9 in the upcoming release of v24.10, scheduled for October 10, 2024. Python 3.12 support will be added at the same time, so that v24.10 will support Python 3.10, Python 3.11, and Python 3.12.

Impact

Users should plan to move to a supported Python version 3.10, 3.11, or 3.12 as soon as possible.

Deprecation Announcement Dropping CUDA 12.2 support in our Docker Images in Release v24.08

Thu, 17 Oct 2024 00:00:00 +0000

Overview

RAPIDS is planning to deprecate support of CUDA 12.2 Docker containers in Release v24.08, and to cease publishing CUDA 12.2 Docker containers before the v24.10 release. The CUDA 12.2 containers will be replaced by CUDA 12.5 containers. We are continuing support for CUDA 11.8 and 12.0 containers.

Impact

Effective RAPIDS v24.08 release, RAPIDS will cease distribution of CUDA 12.2 Docker containers. RAPIDS will continue to support CUDA 11.8, 12.0 and 12.5 containers. Users who still wish to use CUDA 12.2 (or other versions in the CUDA 11.x or 12.x series) may continue to use RAPIDS via conda or pip.

Moving libcumlprims, libcugraphops, pylibcugraphops to the rapidsai channel

Thu, 17 Oct 2024 00:00:00 +0000

Overview

Currently, most RAPIDS conda packages are published to the rapidsai channel except for libcumlprims, libcugraphops, and pylibcugraphops, which are published to the nvidia channel. These packages will be moved to the rapidsai channel, to simplify the user experience and ensure that all RAPIDS packages are available from the same channel.

For the 24.06 release, libcumlprims, libcugraphops, and pylibcugraphops will be added to the rapidsai channel. These packages will be available on both the rapidsai and nvidia channels for 24.06 and 24.08. Starting in 24.10, the packages will only be available on the rapidsai channel.

RAPIDS users should continue to use the conda channel priority -c rapidsai -c conda-forge -c nvidia to ensure that packages are installed from the correct channel (this is unchanged).

Impact

New installations of RAPIDS will be unaffected, as the rapidsai channel is already required for most RAPIDS packages. Users updating libcumlprims, libcugraphops, and pylibcugraphops should be aware that the channel will change.

Deprecation of `CentOS 7` in v24.04

Thu, 17 Oct 2024 00:00:00 +0000

Overview

RAPIDS is deprecating CentOS 7 in release v24.04, and it will be removed in release v24.06. This is due to CentOS 7 becoming end of life in June 2024, which means RAPIDS will no longer publish any images built on CentOS 7 following the RAPIDS v24.04 release.

Impact

Users should consider switching to any of the following supported operating systems for any rapidsai/rapidsai image:

Ubuntu 22.04
Ubuntu 20.04
Rocky 8

Support for Pandas 2 in Release v24.04

Thu, 17 Oct 2024 00:00:00 +0000

Overview

Pandas 1.x series support will be deprecated in the upcoming release of v24.02 scheduled for February 8, 2024, and removed in v24.04, scheduled for April 11, 2024. Effective v24.04, the minimum version of Pandas supported will be Pandas 2.0.0.

Impact

Users should plan to move to Pandas 2 for RAPIDS 24.04 and later.

Deprecation Announcement Dropping CUDA 11.2 support in our Docker Images in Release v23.12

Tue, 13 Feb 2024 00:00:00 +0000

Overview

RAPIDS is planning to deprecate support for its CUDA 11.2 Docker containers in Release v23.12, and to cease publishing CUDA 11.2 Docker containers in the v24.02 release. v23.12 will be the last version of RAPIDS to distribute CUDA 11.2 Docker containers.

Impact

Effective RAPIDS v24.02 release, RAPIDS will cease distribution of CUDA 11.2 Docker containers. RAPIDS will continue to distribute CUDA 12.0 and 11.8 containers. Users who still wish to use CUDA 11.2 (or other versions in the CUDA 11.x or 12.x series) may continue to use RAPIDS via conda installation.

Deprecation announcement for Pascal GPU support in Release v23.12

Tue, 13 Feb 2024 00:00:00 +0000

Overview

RAPIDS team is planning to deprecate support for Pascal GPUs in its v23.12 release and to remove support in its v24.02 release. v23.12 will be the last version of RAPIDS to support Pascal GPUs.

Impact

Effective RAPIDS v24.02 release, RAPIDS will no longer support Pascal GPUs. GPUs with Compute Capability 7.0 or higher will be required. The last release with support for Pascal GPUs is RAPIDS v23.12.

RAPIDS v23.10 Hotfix for cuDF

Mon, 20 Nov 2023 00:00:00 +0000

Overview

cudf 23.10.01 introduced a bug that could cause incorrect output in cudf and dask-cudf when merging dataframes in which one of the indexes is not unique. cudf is being hotfixed to 23.10.02 to resolve this issue.

Rationale

Impact

All cudf and dask-cudf users are encouraged to upgrade to the new 23.10.02 patch release.

Deprecation announcement for CLX RAPIDS Repository

Tue, 05 Sep 2023 00:00:00 +0000

Overview

RAPIDS CLX repository will be deprecated in our upcoming release of v23.04 scheduled for April 13 2023. After the v23.04 release, this repository will be archived during v23.06 release. v23.04 will be the final release of RAPIDS CLX.

Impact

Users may wish to migrate to Morpheus, which includes much of the CLX functionality: https://github.com/nv-morpheus/Morpheus

Support for 22.10 cuml/cugraph Users

Tue, 05 Sep 2023 00:00:00 +0000

Overview

RAPIDS 22.10 cuML and cuGraph users will need to add libcusparse<12 libcusolver<=11.4.1.48 to conda install commands for installing cuML or cuGraph.

Example

conda create -n rapids-22.10 -c rapidsai -c conda-forge -c nvidia  cugraph=22.10 python=3.8 cudatoolkit=11.5 libcusparse<12 libcusolver<=11.4.1.48

Impact

Impact is limited to RAPIDS 22.10 cuml and cugraph users.

Background

Since the release of RAPIDS 22.10, some packages that cuML and cuGraph depend on have upgraded and introduced incompatibilities. Conda will install these newer dependencies by default when installing 22.10 cuML or cuGraph, which will result in runtime errors such as:

error while loading shared libraries: libnvJitLink.so.12: cannot open shared object file: No such file or directory

In order to restrict conda to installing only compatible versions of these dependencies, the workaround above should be applied. This workaround is not needed for RAPIDS releases 22.12 and beyond.

Support for Ubuntu 22.04 in v23.02

Tue, 05 Sep 2023 00:00:00 +0000

Overview

RAPIDS is planning GA support for Ubuntu 22.04 in its v23.02 release. Ubuntu 22.04 will replace the Ubuntu 18.04 OS distributions for future RAPIDS releases. Experimental support will begin in v23.02 nightlies.

Impact

Ubuntu 18.04 users are encouraged to migrate to a supported version of Ubuntu as soon as possible.

Deprecation announcement for Ubuntu 18.04 in v22.12

Tue, 05 Sep 2023 00:00:00 +0000

Overview

Ubuntu 18.04 will be deprecated in our upcoming release of v22.12 scheduled for December 2022. After the v22.12 release, users should expect that support for Ubuntu 18.04 may be dropped at any point.

Impact

Users should consider switching to any of the following supported operating systems for any rapidsai/rapidsai image:

Ubuntu 20.04
Ubuntu 22.04 (support targeted for RAPIDS 23.02 – see RSN 25)
CentOS 7
Rocky Linux 8

Support for Python 3.10 in v23.02

Tue, 05 Sep 2023 00:00:00 +0000

Overview

With the deprecation of Python 3.9 announced in RSN 22, development effort has been redirected to support Python 3.10 in v23.02 nightly releases.

Impact

Users are encouraged to test nightly conda and docker builds and report any issues in their respective repos.

Deprecation announcement for Python v3.9 in v22.12

Tue, 05 Sep 2023 00:00:00 +0000

Overview

Python 3.9 will be deprecated in our upcoming release of v22.12 scheduled for December 2022. After the v22.12 release, users should expect that support for Python 3.9 may be dropped at any point.

Impact

Users should plan to move to a supported Python version as soon as possible. Support for Python 3.8 is being maintained, and support for Python 3.10 is being targeted for RAPIDS 23.02 (see RSN 23).

EOL for CUDA 11.0 in v22.10

Tue, 05 Sep 2023 00:00:00 +0000

Overview

CUDA 11.0 is now end of life (EOL) in RAPIDS v22.10 and will not be supported in the v22.10 stable release nor the upcoming release of v22.12. This includes v22.10 nightly support which ended on 2022-10-13.

Impact

Users should migrate to CUDA 11.2, 11.4 or 11.5 for RAPIDS.

Please Pin cuda-python to 11.7.0

Tue, 05 Sep 2023 00:00:00 +0000

Overview

We have recently become aware that cuda-python 11.7.1 has incorporated changes that makes it incompatible with current and legacy versions of RAPIDS when you try to install RAPIDS. You will need to pin cuda-python to 11.7.0 in conda during installation, and potentially after. An affected installation with the 11.7.1 issue results in this error being thrown:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/opt/conda/lib/python3.9/site-packages/cudf/__init__.py", line 5, in <module>
    validate_setup()
  File "/opt/conda/lib/python3.9/site-packages/cudf/utils/gpu_utils.py", line 20, in validate_setup
    from rmm._cuda.gpu import (
  File "/opt/conda/lib/python3.9/site-packages/rmm/__init__.py", line 16, in <module>
    from rmm import mr
  File "/opt/conda/lib/python3.9/site-packages/rmm/mr.py", line 14, in <module>
    from rmm._lib.memory_resource import (
  File "/opt/conda/lib/python3.9/site-packages/rmm/_lib/__init__.py", line 15, in <module>
    from .device_buffer import DeviceBuffer
  File "device_buffer.pyx", line 1, in init rmm._lib.device_buffer
TypeError: C function cuda.ccudart.cudaStreamSynchronize has wrong signature (expected __pyx_t_4cuda_7ccudart_cudaError_t (__pyx_t_4cuda_7ccudart_cudaStream_t), got cudaError_t (cudaStream_t)

Status

Currently, we have these two resolution paths to offer:

Resolution Path 1: You can upgrade your RAPIDS version to `v22.06.01`.
- We've made it easy to upgrade: simply use our Release selector and install `v22.06` or rerun you `v22.06` installation script. It will automatically grab `v22.06.01` via Conda or Docker.

Resolution Path 2: If you can NOT upgrade, pin `cuda-python` to `11.7.0` in RAPIDS `v22.02`, `v22.04`, and `v22.06`,
- You can pin `cuda-python` to `11.7.0` by using `cuda-python=11.7.0` when doing an install.
- Example command: `conda install -c nvidia cuda-python=11.7.0`.

Older versions of RAPIDS may also be affected and users should attempt to upgrade or pin.

Impact

This issue impacts users installing conda packages of RAPIDS 22.02 through 22.06, which depend on cuda-python. This issue also affects existing conda installations of RAPIDS versions 22.02 - 22.06 if the user installs additional packages depending on cuda-python that result in an update to cuda-python>11.7.0.

Stop supporting `CentOS 8` in v22.08

Tue, 05 Sep 2023 00:00:00 +0000

Overview

CentOS 8 is now at end-of-life, which means RAPIDS will no longer publish any images built on CentOS 8 following the RAPIDS v22.06 release.

Additionally, gpuCI CPU builds will be converted over to use Rocky 8.6 instead of CentOS 8.

Status

Support for CentOS 8 has ended. RAPIDS v22.06 is the last version to support CentOS 8.

Impact

Users should consider switching to any of the following container OSes:

Ubuntu 18.04
Ubuntu 20.04
Rocky 8.6
CentOS 7

Support for Rocky 8.6 in v22.08

Tue, 05 Sep 2023 00:00:00 +0000

Overview

Development effort will begin supporting Rocky 8.6 in v22.08. Rocky 8.6 will replace the CentOS 8 OS distributions for future RAPIDS releases. Experimental support will begin in v22.08 nightlies. GA support for Rocky 8.6 is expected for v22.10 stable.

Impact

CentOS 8 users are encouraged to migrate to Rocky 8.6 if possible and provide feedback to the RAPIDS libraries as we develop v22.08.

Support for ARM SBSA in v22.04

Tue, 05 Sep 2023 00:00:00 +0000

Overview

Announcing support of ARM SBSA in v22.04. ARM users will be able to install RAPIDS via our conda and docker channels. This support does not yet extend to NVIDIA Jetson products.

See our release blog for installation detailss.

Status

ARM SBSA stable and nightly support started on 08-Apr-2022 for both conda and docker

Impact

Users are encouraged to test nightly conda and docker builds and report any issues in their respective repos.

Support for Python 3.9 in v22.02

Tue, 05 Sep 2023 00:00:00 +0000

Overview

With the EOL of Python 3.7 announced in RSN 14, development effort has been redirected to support Python 3.9 in v22.02 stable and v22.04 nightly releases.

Status

Python 3.9 nightly support started on 04-Feb-2022 for both conda and docker

Impact

Users are encouraged to test nightly conda and docker builds and report any issues in their respective repos.

EOL Python 3.7 in v22.02

Tue, 05 Sep 2023 00:00:00 +0000

Overview

Python 3.7 has reached end of life (EOL) in RAPIDS v22.02 and will not be supported in the v22.02 stable release nor the upcoming release of v22.04. This includes v22.02 nightly support which ended on 2022-02-03.

Status

Release support - `v22.02`

Final release of conda packages or docker images supporting Python 3.7
Nightly support - v22.04
No further conda packages or docker images supported for Python 3.7
Documentation
Updates to Docker Hub and NGC repos will be reflected with the v22.02 release
Updated rapids.ai release selector to reflect EOL changes and available install options
Impact

Users should migrate to Python 3.8 or Python 3.9 for RAPIDS.

Support for CUDA 11.4 in v21.08

Tue, 05 Sep 2023 00:00:00 +0000

Overview

Development effort has begun on supporting CUDA 11.4 in v21.08. Support is currently experimental for v21.08. GA for CUDA 11.4 is expected in v21.10

Impact

Users are encouraged to use CUDA 11.4 if possible and provide feedback to the RAPIDS libraries as we develop v21.08.

Stop supporting Ubuntu 16.04 in v21.08

Tue, 05 Sep 2023 00:00:00 +0000

Overview

Ubuntu 16.04 is now at end-of-life, which means RAPIDS will no longer publish any images built on Ubuntu 16.04.

Additionally, gpuCI CPU builds will be converted over to use CentOS 7 instead of Ubuntu 16.04.

Status

Dropping full support for Ubuntu 16.04 is an ongoing effort.

Impact

Users should consider switching to any of the following supported operating systems for any rapidsai/rapidsai image:

Ubuntu 18.04
Ubuntu 20.04
CentOS 7
CentOS 8

RAPIDS v22.10.01 Hotfix Release

Tue, 05 Sep 2023 00:00:00 +0000

Overview

RAPIDS v22.10 was hotfixed to version v22.10.01 to update cuda-python and cupy dependencies.

Rationale

cuda-python version requirement was updated to >=11.7.1 to resolve errors on CPU-only machines or machines without CUDA installed. Additionally, the cupy dependency for pip packages was changed to cupy-cuda11x to resolve installation issues for some users.

Impact

All users are recommended to use the latest 22.10.01 version of rmm, cuDF, cuML, cuGraph, and cuGraph-ops.

RAPIDS Docker Run Command Changes in v22.04

Tue, 05 Sep 2023 00:00:00 +0000

Overview

As we expand out further across platforms and GPU architectures, we have recently identified and updated the RAPIDS docker run with additional parameters to provide a more stable way to run Multi Node/Multi GPU (MNMG). The new parameters are --shm-size=1g --ulimit memlock=-1. This change is currently in the RAPIDS Release Selector and will soon be updated in all docker instructions. We advise everyone to adopt these additional parameters for when running RAPIDS on Docker, especially if you’re running RAPIDS on ARM SBSA with MNMG.

Status

2022-06-08 - This change is currently in the RAPIDS Release Selector

Impact

Refer to the examples below for a comparison of old & new docker run commands:

Example Old Docker Run Command

    docker run --gpus all --rm -it \
    -p 8888:8888 -p 8787:8787 -p 8786:8786 \
    rapidsai/rapidsai-core-arm64:22.06-cuda11.5-runtime-ubuntu20.04-py3.9

Example New Docker Run Command

    docker run --gpus all --rm -it \
    --shm-size=1g --ulimit memlock=-1 \
    -p 8888:8888 -p 8787:8787 -p 8786:8786 \
    rapidsai/rapidsai-core-arm64:22.06-cuda11.5-runtime-ubuntu20.04-py3.9

v22.06 Release Update

Tue, 05 Sep 2023 00:00:00 +0000

Overview

22.06 devel containers will be released on Wednesday 6/15/22. Conda packages and base container release dates will remain unchanged.

Rationale

22.06 release artifacts will be bifurcated–conda packages and base containers (i.e. those other than devel) will be released on Wednesday 6/8/22. devel containers will be released on Wednesday 6/15/22.

Impact

N/A

rmm v22.04.01 Hotfix Release

Tue, 05 Sep 2023 00:00:00 +0000

Overview

rmm was hotfixed to version v22.04.01.

Rationale

rmm was hotfixed to v22.04.01 in order to fix a packaging issue as noted in #1024.

Impact

All v22.04 users are encouraged to update the rmm library to v22.04.01 as soon as possible.

Updated WSL2 Installation Method

Tue, 05 Sep 2023 00:00:00 +0000

Overview

The installation method for a RAPIDS compatible WSL2 instance has changed with the release of NVIDIA’s WSL2 capable Windows 11 Production Drivers. If you already have RAPIDS running on WSL2, Please update your Windows drivers accordingly for continued EA support with RAPIDS v22.02. If you are installing RAPIDS inside WSL2 for the first time, please follow the updated instructions below:

1. Please follow the steps in this MS Blog to install WSL2: https://docs.microsoft.com/en-us/windows/wsl/install
2. Install the latest Windows 11 production drivers on the host machine, which are WSL2 capable: https://www.nvidia.com/Download/index.aspx?lang=en-us
3. Inside WSL2:
	a. Install conda or docker environments
	b. Install RAPIDS as normal with your environment options of choice.

This makes a complete RAPIDS installation far easier in WSL2. Please do not install any additional NVIDIA drivers, neither GPU nor CUDA, inside your WSL2 instance as it is no longer necessary. CUDA Toolkit (CTK) will be installed when you install RAPIDS in your desired environment.

Status

12-Feb-2022 - EA support continues.

Impact

Users intending to run RAPIDS v22.02+ in WSL2 should update their systems in accordance with this updated installation guide.

New 'Try RAPIDS Now' Capability via SageMaker Studio Labs in Beta

Tue, 05 Sep 2023 00:00:00 +0000

Overview

SageMaker Studio Labs has been added as a new “Try it Now” capability for all Stable (v22.02), Nightly (v22.04), and Legacy (v21.12) RAPIDS installations. Open in SageMaker Studio Lab buttons and links can be found in the Getting Started sections of our Website. A new, quick-start repository can be found in RAPIDS community with further installation instructions. You can only try RAPIDS in SageMaker Studio Lab after you have successfully created a SageMaker Studio Lab account. Please share any issues you face in the rapids-smsl repo and feedback in the RAPIDS GoAI Slack!

Status

12-Feb-2022 - Appropriate links to SageMaker Studio Lab have been added. Quick Start Repository has been made.

Impact

Users continue to have Try RAPIDS Now options for Stable (v22.02), Nightly (v22.04), and Legacy (v21.12) RAPIDS versions.

CUDA Enhanced Compatibility

Tue, 05 Sep 2023 00:00:00 +0000

Overview

RAPIDS 21.12 packages will be built using the latest 11.5 version of nvcc and the CUDA runtime and distributed for use with any CUDA driver >=450.80.02 via the use of CUDA Enhanced Compatibility. We strongly recommend using the CUDA 11.5 runtime. Any runtime >=11.0 and <11.5 is supported on a best-effort basis.

Impact

One limitation this poses for users running older minor versions of the CUDA runtime is that the use of debug=True with the numba @cuda.jit decorator will result in a runtime error. Users running 11.5 will still be able to use debug=True.

Devel Container Release Change

Tue, 05 Sep 2023 00:00:00 +0000

Overview

Effective with the 21.12 release, RAPIDS devel packages will only be distributed for CUDA 11.5.

Dropping Support for Ubuntu 20.04 arm64 containers in Release v23.06

Thu, 17 Aug 2023 00:00:00 +0000

Overview

Due to a bug in glibc 2.31 (https://bugzilla.redhat.com/show_bug.cgi?id=1722181) with no current workaround, we are unable to publish arm64 ubuntu20.04 containers effective RAPIDS release 23.04. x86_64 containers are not affected. More details may be found in the tracking issue: https://github.com/rapidsai/docker/pull/551

Impact

arm64 users should migrate to ubuntu22.04 as soon as possible.

Deprecation announcement for cuSignal

Thu, 17 Aug 2023 00:00:00 +0000

Overview

The RAPIDS cuSignal repository is integrating into the CuPy repository and will be deprecated in 3 to 4 months. We are tentatively targeting the v23.08 release scheduled for August 10, 2023 as the final release of RAPIDS cuSignal. After the v23.08 release, this repository will be archived during the v23.10 development cycle.

Impact

Users should prepare to migrate to CuPy, which will include cuSignal functionality: https://github.com/cupy/cupy

CUDA 12 pip Wheels Release in v23.06

Thu, 17 Aug 2023 00:00:00 +0000

Overview

RAPIDS packages that build pip wheels (rmm, cudf, raft, cuml, cugraph, cuopt, ucx-py) are now building pip wheels with CUDA 12 support. We plan to release these packages in release v23.06.

CUDA 12 wheels are named with a -cu12 suffix to distinguish them from CUDA 11 wheels which have a -cu11 suffix.

Impact

Users should be aware we now are building pip wheels with CUDA 12 support as noted above.

Docker Image Changes in Release v23.08

Thu, 17 Aug 2023 00:00:00 +0000

Overview

The RAPIDS 23.08 release has made changes to end-user Docker images to improve functionality, performance, and maintainability.

While many of these changes should be seamless to users, some of them are breaking. Users should review the full list of changes in the associated issue: https://github.com/rapidsai/docker/issues/539

Impact

Users should be particularly aware of the breaking changes as noted above.

Dropping Python v3.8 in v23.06

Thu, 17 Aug 2023 00:00:00 +0000

Overview

Python 3.8 support will be dropped in the upcoming release of v23.06, scheduled for June 2023. Python 3.9 support will be added at the same time, so that v23.06 will support Python 3.9 and 3.10.

Impact

Users should plan to move to a supported Python version 3.9 and/or 3.10 as soon as possible.

Deprecation announcement for CUDA 11.4 and 11.5 containers

Thu, 17 Aug 2023 00:00:00 +0000

Overview

RAPIDS is deprecating CUDA 11.4 and CUDA 11.5 containers effective its v23.04 release. RAPIDS will plan to EOL these containers in a future release (currently targeting v23.06), at which point CUDA 11.4 and CUDA 11.5 containers will no longer be published.

Impact

Once these containers reach EOL (currently targeting v23.06 release), RAPIDS will no longer publish these containers. Note that conda packages will still support CUDA 11.4 and CUDA 11.5 due to CUDA Enhanced Compatibility.

22.06 Hotfix for `cuda-python` Package

Thu, 07 Jul 2022 00:00:00 +0000

Overview

RAPIDS v22.06 was hotfixed to pin the cuda-python package dependency to a maximum version of 11.7.0 for several RAPIDS libraries.

Rationale

cuda-python version 11.7.1 was recently released, which switched its dependency on the cudatoolkit package to the cuda-toolkit package. This dependency change had unintended consequences for several RAPIDS libraries, including blocking installation for some users.

Impact

All users are recommended to use the latest 22.06.01 version of all RAPIDS libraries.

Deprecation announcement for CUDA 11.0 in v22.06

Wed, 08 Jun 2022 00:00:00 +0000

Overview

CUDA 11.0 will be deprecated in our upcoming release of v22.06 scheduled for June 2022. After the v22.06 release, users should expect that support for CUDA 11.0 may be dropped at any point.

Impact

Users should plan to move to CUDA 11.2+ as soon as possible or update their driver to r450.80.02 or higher to take advantage of the CUDA Enhanced Compatibility capability. Future support of additional CUDA 11.X versions are being worked on for upcoming releases. Further details will be shared in RSN notices as they become available.

SQL migration in v21.12

Thu, 17 Feb 2022 00:00:00 +0000

Overview

RAPIDS will preview its migration path from BlazingSQL to dask-based SQL in 21.12

Impact

21.12 will contain a preview of a migration path for users to use RAPIDS with dask-based SQL

Google Colab RAPIDS support limited to RAPIDS v21.12

Thu, 17 Feb 2022 00:00:00 +0000

Overview

RAPIDS v22.02 requires Python 3.8+; Google Colab is currently limited to Python 3.7. Google Colab will only support up to RAPIDS v21.12 until Colab support for Python 3.8+ is complete. Users may make use of SageMaker Studio Labs as an alternative “Try it Now” for Stable (v22.02), Nightly (v22.04), and Legacy (v21.12) RAPIDS trials.

NOTE: Refer to RSN 14 for more information about EOL support of Python 3.7.

Status

12-Feb-2022 - Warnings have been added to links to Colab on RAPIDS website; links to SageMaker Studio Lab have been added.

Impact

Google Colab support for RAPIDS is currently limited to RAPIDS version v21.12. Users can use SageMaker Studio Lab for all Stable (v22.02), Nightly (v22.04), and Legacy (v21.12) RAPIDS versions.

Deprecation announcement for Python v3.7 in v21.12

Thu, 03 Feb 2022 00:00:00 +0000

Overview

Python 3.7 will be deprecated in our upcoming release of v21.12 scheduled for December 2021. After the v21.12 release, users should expect that support for Python 3.7 may be dropped at any point.

Impact

Users should plan to move to Python 3.8 as soon as possible. Future support of additional Python 3.9 version is being worked on for upcoming releases. Further details will be shared in RSN notices as they become available.

cuDF v21.12.02 Hotfix Release

Thu, 16 Dec 2021 00:00:00 +0000

Overview

cuDF was hotfixed to version v21.12.02.

Rationale

cuDF was hotfixed to v21.12.02 in order to fix a performance regression as noted in #9898.

Impact

All v21.12 users are encouraged to update the cuDF library to v21.12.02 as soon as possible.

cuDF v21.12.01 Hotfix Release

Thu, 09 Dec 2021 00:00:00 +0000

Overview

cuDF was hotfixed to version v21.12.01.

Rationale

cuDF was hotfixed to v21.12.01 in order to fix the bug, #9868.

Impact

All v21.12 users are encouraged to update the cuDF library to v21.12.01 as soon as possible.

Minimum driver requirement for CUDA 11.0 in v21.12

Tue, 12 Oct 2021 00:00:00 +0000

Overview

We are increasing the minimum driver version for RAPIDS CUDA 11.0 to 450.80.02+ in order to support CUDA Enhanced Compatibility

Impact

Users should upgrade their driver to 450.80.02 or newer to continue using RAPIDS in the future

Hotfix 21.10 release for RMM and cuDF

Mon, 11 Oct 2021 00:00:00 +0000

Overview

rmm and cuDF libraries were hotfixed to version 21.10.01.

Rationale

rmm and cuDF were hotfixed to resolve conda packaging issue observed with third-party files

Impact

The fix moves the third-party cmake files from lib64 to lib subdirectory

Hotfix 21.08 release for five libraries

Mon, 09 Aug 2021 00:00:00 +0000

Overview

Four RAPIDS libraries were hotfixed to version 21.08.01 and cuDF was hotfixed to version 21.08.02.

Rationale

rmm, cuml, cugraph, and cuspatial were hotfixed to 21.08.01. cudf was hotfixed to 21.08.02. These five libraries were hotfixed in order to fix the conda package location of the CMake configuration files, #56.

Impact

All v21.08 users are encouraged to update rmm, cuml, cugraph, and cuspatial libraries to 21.08.01 and cuDF to 21.08.02 as soon as possible.

cuCIM and cuDF 21.08.01 Hotfix Release

Mon, 09 Aug 2021 00:00:00 +0000

Overview

cuCIM and cuDF were hotfixed to version 21.08.01.

Rationale

cucim was hotfixed to 21.08.01 in order to ensure the compiler stack aligned with the rest of RAPIDS, #84.

cudf was hotfixed to 21.08.01 in order to fix the bug, #8984 and performance degradation in concatenate for string columns, #8968.

Impact

All v21.08 users are encouraged to update cuCIM and cuDF libraries to 21.08.01 as soon as possible.

cuDF v21.06.01 Hotfix Release

Tue, 22 Jun 2021 00:00:00 +0000

Overview

cuDF was hotfixed to version 21.06.01.

Rationale

cuDF was hotfixed to fix an offset error which could lead to data corruption when writing ORC files with multiple large string columns, #8538.

Impact

All v21.06 users are encouraged to update cuDF libraries to 21.06.01 as soon as possible.

cuML v21.06.02 Hotfix Release

Tue, 22 Jun 2021 00:00:00 +0000

Overview

cuML was hotfixed to version 21.06.02.

Rationale

cuML was hotfixed (21.06.01) to fix a bug with batch sizes larger than 32 bits, #3971.

cuML was hotfixed (21.06.02) to fix a bug with missing OpenMP support, #3988.

Impact

All v21.06 users are encouraged to update cuML libraries to 21.06.02 as soon as possible.

RAPIDS switching to CalVer in v0.20 (now v21.06)

Mon, 17 May 2021 00:00:00 +0000

Overview

All RAPIDS projects are switching their versioning scheme to Calendar Versioning.

This versioning will apply to both the overall RAPIDS release and each core library, so we will release cuDF 21.06.00, cuML 21.06.00, etc. as part of the overall RAPIDS 21.06.00 release.

Impact

Instead of a 0.20.0 release in June 2021, we will release 21.06.00

New version format for release: YY.MM.PP, for example 21.06.00

New version format for nightlies: YY.MM.PPaYYMMDD, for example 21.06.00a210505

Where PP is the two digit patch number not day.

ABI & API compatibility will be maintained within each YY.MM.xx release.

Change minimum support gcc/g++ version to 9.x

Wed, 05 May 2021 00:00:00 +0000

Overview

All RAPIDS projects will require gcc/g++ 9.0+ in order to take advantage of new C++ features, notably including moving to C++17.

This also aligns RAPIDS with the current conda-forge build stack.

Status

All conda builds and docker images use gcc/g++ 9.3 starting with v0.20 (now v21.06).

Impact

Users building from source should use gcc/g++ 9.0 or higher to build RAPIDS.

cuDF v0.19.2 Hotfix Release

Wed, 28 Apr 2021 00:00:00 +0000

Overview

cuDF was hotfixed to version 0.19.2.

Rationale

cuDF was hotfixed to fix a deadlock that could occur in decompression in cuIO, #8073.

Impact

All v0.19 users are encouraged to update cudf libraries to 0.19.2 as soon as possible.

cuDF & cuXfilter v0.19.1 Hotfix Release

Thu, 22 Apr 2021 00:00:00 +0000

Overview

Both cuDF and cuXfilter were hotfixed to version 0.19.1.

Rationale

cuDF was hotfixed for two bugs: #8023 #8031.

cuXfilter was hotfixed to resolve a dependency conflict.

Impact

All v0.19 users are encouraged to update cudf & cuxfilter libraries to 0.19.1 as soon as possible.

cuDF v0.18.2 Hotfix Release

Thu, 22 Apr 2021 00:00:00 +0000

Overview

cuDF was hotfixed to version 0.18.2.

Rationale

cuDF was hotfixed for a bug in the parquet file reader.

Impact

All v0.18 users are encouraged to update cudf libraries to 0.18.2 as soon as possible.

Support for CUDA 11.2 in v0.19

Wed, 21 Apr 2021 00:00:00 +0000

Overview

With the EOL of CUDA 10.X announced in RSN 6, development effort has been redirected to support CUDA 11.2 in v0.19 and v0.20.

Impact

Users are encouraged to use CUDA 11.2 if possible and provide feedback to the RAPIDS libraries as we develop v0.20.

EOL CUDA 10.1 & 10.2 in v0.19

Wed, 21 Apr 2021 00:00:00 +0000

Overview

CUDA 10.1 & 10.2 have reached end of life (EOL) in RAPIDS v0.19 and will not be supported in the upcoming release of v0.20. This includes v0.20 nightly support which ended on 2021-04-05.

Status

Release support - `v0.19`

Final release of conda packages or docker images supporting CUDA 10.X

Nightly support - `v0.20`

No further conda packages or docker images supporting for CUDA 10.X

Documentation

Updates to Docker Hub and NGC repos will be reflected with the v0.19 release
Updated rapids.ai release selector to reflect EOL changes and available install options

Impact

Users should migrate to CUDA 11.0 or 11.2 for RAPIDS.

v0.19 Release Extension

Wed, 14 Apr 2021 00:00:00 +0000

Overview

The RAPIDS v0.19 release date has been extended for 1 week to 21-Apr-2021.

Rationale

The release is being extended in order to fix a bug in the parquet file reader.

Impact

See our updated release schedule for v0.19

Deprecation announcement for CUDA 10.1 & 10.2 in v0.19

Thu, 25 Feb 2021 00:00:00 +0000

Overview

CUDA 10.1 & 10.2 will be deprecated in our upcoming release of v0.19 scheduled for April 2021. After the v0.19 release, users should expect that support for CUDA 10.X may be dropped at any point.

Impact

Users should plan to move to CUDA 11.0+ as soon as possible. Future support of additional CUDA 11.X versions are being worked on for upcoming releases. Further details will be shared in RSN notices as they become available.

v0.18 Release Extension

Thu, 11 Feb 2021 00:00:00 +0000

Overview

The RAPIDS v0.18 release date has been extended to 2021-02-24 due to issues encountered in RDN 2

Impact

See our updated release schedule for v0.18
Refer to RDN 2 for more details on gcc 7.5.0 from-source build changes needed in v0.18+

Updates to from-source builds with conda for gcc '7.5.0'

Thu, 11 Feb 2021 00:00:00 +0000

Overview

Recently conda-forge has switched to publish conda packages using the gcc/g++ 9.3.0 build stack. RAPIDS v0.18 has also switched to this build stack for our conda dependencies resulting in the following changes for developers.

Impact

All from-source builds with conda dependencies for CUDA 10.1/10.2/11.0 using gcc 7.5.0 are affected and need changes to successfully build RAPIDS v0.18+

NOTE: CUDA 11.0 RAPIDS from-source builds with conda dependencies using gcc 9.3.0 are not impacted (CUDA 10.1/10.2 do not support gcc 9.3.0 for builds)

Ubuntu 16.04/18.04/20.04

For all Ubuntu versions, we use this PPA to install gcc 7.5.0 and update the alternatives to set it as the default compiler:

sudo apt-get update
sudo apt-get install -y software-properties-common
sudo add-apt-repository -y ppa:ubuntu-toolchain-r/test
sudo apt-get update
sudo apt-get install -y gcc-7 g++-7 libstdc++6
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-7 7
sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-7 7
sudo update-alternatives --set gcc /usr/bin/gcc-7
sudo update-alternatives --set g++ /usr/bin/g++-7

NOTE: The docker equivalent for this code can be found here

With the install of gcc 7.5.0 and an updated libstdc++6 pkg, you should be able to build RAPIDS from-source with conda dependencies. If you encounter any GLIBC errors during the build process, be sure the check the version of the libstdc++6 package outlined below.

Check libstdc++6 package version

In order to build with conda dependencies from conda-forge the installed libstdc++6 package must be >= 9.3.0. You can verify the current installed version and available version through the following commands:

sudo apt-get update
sudo apt-cache policy `libstdc++6`

If the version is not >= 9.3.0 install the package again to update it:

sudo apt-get install libstdc++6

CentOS 7/8 or RHEL 7/8

For CentOS and RHEL we build gcc 7.5.0 from source for our docker images and make it available as a tarball. Our public tarball is now patched to include a version of libstdc++ from a gcc 9.3.0 build that allows from-source builds of RAPIDS with conda dependencies to work.

Installing our patched gcc 7.5.0

Download and extract the tarball to the target machine or docker image. The tarball is meant to be extracted from the root and extracts into the following path: /usr/local/gcc7

sudo wget --quiet https://gpuci.s3.us-east-2.amazonaws.com/builds/gcc7.tgz -O /gcc7.tgz
sudo tar xzf /gcc7.tgz
sudo rm -f /gcc7.tgz

NOTE: The docker equivalent for this code can be found here

Once extracted, setup the environment variables to enable the use of the installed gcc 7.5.0:

export GCC7_DIR=/usr/local/gcc7
export CC=${GCC7_DIR}/bin/gcc
export CXX=${GCC7_DIR}/bin/g++
export CUDAHOSTCXX=${GCC7_DIR}/bin/g++
export CUDA_HOME=/usr/local/cuda
export LD_LIBRARY_PATH=${GCC7_DIR}/lib64:$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/local/lib
export PATH=${GCC7_DIR}/bin:$PATH

NOTE: The docker equivalent for this code can be found here

From here all ./build.sh scripts in RAPIDS repos should build without error.

RAPIDS docker image changes in v0.17

Thu, 10 Dec 2020 00:00:00 +0000

Overview

The RAPIDS v0.17 docker images have been updated to include BlazingSQL by default using existing images and tags. New images with the root name of rapidsai-core have been created that only contain RAPIDS libraries.

Status

10-Dec-2020 - Changes have been pushed with the v0.17 release

Impact

Refer to the tables below for a comparison of v0.16 & v0.17 behavior and options

Stable (Release) Images

Docker Repo	Image Type	Previous Behavior	v0.17+ Behavior	Options
`rapidsai/rapidsai`	`base` & `runtime` conda-based images	*ONLY* RAPIDS	RAPIDS *AND* BlazingSQL	Switch to `rapidsai/rapidsai-core` for RAPIDS *ONLY* images
`rapidsai/rapidsai-dev`	`devel` from-source images	*ONLY* RAPIDS	RAPIDS *AND* BlazingSQL	Switch to `rapidsai/rapidsai-core-dev` for RAPIDS *ONLY* images

Nightly Images

Docker Repo	Image Type	Previous Behavior	v0.17+ Behavior	Options
`rapidsai/rapidsai-nightly`	`base` & `runtime` conda-based images	*ONLY* RAPIDS	RAPIDS *AND* BlazingSQL	Switch to `rapidsai/rapidsai-core-nightly` for RAPIDS *ONLY* images
`rapidsai/rapidsai-dev-nightly`	`devel` from-source images	*ONLY* RAPIDS	RAPIDS *AND* BlazingSQL	Switch to `rapidsai/rapidsai-core-dev-nightly` for RAPIDS *ONLY* images

v0.16 Release Extension

Wed, 07 Oct 2020 00:00:00 +0000

Overview

The RAPIDS v0.16 release date has been extended for 1 week to 2020-10-21

Impact

See our updated release schedule for v0.16

Google Colab RAPIDS support limited to RAPIDS 0.14

Tue, 15 Sep 2020 00:00:00 +0000

Overview

RAPIDS 0.15 requires Python 3.7+; Google Colab is currently limited to Python 3.6. Google Colab will only support up to RAPIDS 0.14 until Colab support for Python 3.7+ is complete. Users may make use of BlazingSQL Notebooks at http://app.blazingsql.com for RAPIDS 0.15 support.

NOTE: Refer to RSN 2 for more information about EOL support of Python 3.6 & CUDA 10.0

Status

11-Sep-2020 - Warnings have been added to links to Colab on RAPIDS website; links to BlazingSQL Notebooks have been added.

Impact

Google Colab support for RAPIDS is currently limited to RAPIDS version 0.14. Users can use BlazingSQL Notebooks for RAPIDS 0.15.

v0.15 Release Delay for 'cuxfilter'

Tue, 08 Sep 2020 00:00:00 +0000

Overview

cuxfilter depends on Numba v0.51. Currently there is only v0.51.0 there are known issues with this release for other RAPIDS libraries and we need to wait for v0.51.1 to release cuxfilter.

Status

26-Aug-2020 - Released RAPIDS v0.15 without cuxfilter
08-Sept-2020 - Re-released RAPIDS v0.15 with cuxfilter

Impact

Users are encouraged to use the previous version of cuxfilter from v0.15 until this is resolved.

Stable/Release Branch Renaming to 'main' in v0.15

Fri, 28 Aug 2020 00:00:00 +0000

Overview

RAPIDS has decided to follow other Open Source projects in renaming their “default” git branch to main. Starting with the v0.15 release, the existing RAPIDS stable/release branch will be removed and all references should use the main branch going forward.

NOTE: RAPIDS uses branch-X.Y as our GitHub default branch for development; however, our stable/release branch is typically the “default” branch for others and new git projects.

For more information read the GitHub docs detailing their plan for renaming branches.

Status

Updates

10-Jul-2020 - main branches were added to all repos with an existing stable/release branch
15-Jul-2020 - Documentation with outdated references were updated with PRs to main
Completed - PRs to update scripts and other mentions will be merged into branch-0.15 and then into main
26-Aug-2020 - Release v0.15 occurred and using the main branch
28-Aug-2020 - Renaming complete, old branches removed

Impact

Any other projects or developers referring to our current stable/release branch will no longer work or may redirect incorrectly. This includes search and web links that link to GitHub.

From the GitHub docs on renaming, there will be some redirects in place; however, they will redirect to the GitHub “default” branch which in our case means links to stable/release will redirect to our development branch. This may cause some confusion, but we will do our best to ensure the links are updated.

Users that find outdated links should open an issue in the repo they have been found. For updates on this docs site or rapids.ai, file an issue here.

Support for CUDA 11.0 in v0.15

Wed, 26 Aug 2020 00:00:00 +0000

Overview

With the EOL of CUDA 10.0 announced in RSN 2, development effort has been redirected to support CUDA 11.0 in v0.15.

CuPy has released v7.8.0 with CUDA 11.0 support. We have temporarily built a version of the cupy package in rapidsai channel that has CUDA 11.0 support. In addition we have temporarily built faiss, faiss-gpu, libfaiss to support CUDA 11.0 in the rapidsai channel. These packages are a stop-gap until conda-forge provides support for CUDA 11.0. Once packages are up on conda-forge we will remove our packages.

NOTE: v0.16 nightlies will continue to use our v7.8.0 package for CUDA 11.0 until an update is made on conda-forge

Status

Updates

21-Jul-2020 - Working on getting core conda dependencies for CUDA 11.0 built to enable testing and bring up
12-Aug-2020 - CUDA 11 packages released in rapidsai-nightly channel
26-Aug-2020 - CUDA 11 condatoolkit published in anaconda and defaults channels (also available on nvidia channel)
26-Aug-2020 - Released v0.15 with CUDA 11 support

v0.15 No CUDA 11 Release for 'clx'

Wed, 26 Aug 2020 00:00:00 +0000

Overview

clx depends on PyTorch v1.6 which does not have CUDA 11.0 support currently. The v0.15 release of clx will only support CUDA 10.1 & CUDA 10.2.

Status

26-Aug-2020 - Released CUDA 10.1 and CUDA 10.2 support for clx

Impact

Users are encouraged to use nightly conda packages in v0.16 when CUDA 11 support is available.

'dask-xgboost' is deprecated in v0.15 & removed v0.16

Wed, 26 Aug 2020 00:00:00 +0000

Overview

rapidsai/dask-xgboost is deprecated in v0.15 and will be removed in v0.16. As of release 1.0, XGBoost provides a native Dask API.

The native XGBoost API has all of the functionality of dask-xgboost, combined with an updated, clean API and much more extensive testing. All users are encouraged to switch to the native API. See also this blog post for an overview.

Status

Added a deprecation warning to the RAPIDS rapidsai/dask-xgboost repo

Impact

Any other projects or developers using our version of rapidsai/dask-xgboost should switch to the upstream repo dask/dask-xgboost

v0.15 Release Extension

Wed, 05 Aug 2020 00:00:00 +0000

Overview

The RAPIDS v0.15 release date has been extended for 1 week to 26-Aug-2020 to better support CUDA 11.

Rationale

Core RAPIDS dependencies like CuPy and Numba are planning to release stable or release candidate versions that support CUDA 11 on or around 19-Aug-2020. Given their release dates are scheduled on the original release date for RAPIDS v0.15, we are extending the release so we can ship with more stable dependencies instead.

Impact

See our updated release schedule for v0.15

Support for Python 3.8 in v0.15

Fri, 17 Jul 2020 00:00:00 +0000

Overview

With the EOL of Python 3.6 announced in RSN 2, development effort has been redirected to support Python 3.8 in v0.15.

Status

Python 3.8 nightly support started on 16-Jul-2020 for both conda and docker

Impact

Users are encouraged to test nightly conda and docker builds and report any issues in their respective repos.

Change minimum support gcc/g++ version to 7.5

Fri, 17 Jul 2020 00:00:00 +0000

Overview

Changes in the conda-forge ecosystem forced RAPIDS to change from gcc/g++ 7.3 support to gcc/g++ 7.5 support for v0.14 and future releases.

Status

All conda and docker images use gcc/g++ 7.5 to ensure compatibility with conda-forge

Impact

Users building from source should use gcc/g++ 7.5 or higher to build RAPIDS.

EOL Python 3.6 & CUDA 10.0 in v0.14

Mon, 13 Jul 2020 00:00:00 +0000

Overview

Python 3.6 and CUDA 10.0 have reached end of life (EOL) in RAPIDS v0.14 and will not be supported in the upcoming release of v0.15. This includes v0.15 nightly support which ended on 13-Jul-2020.

Status

Nightly support

Has ended as of 13-Jul-2020
- No further conda packages or docker images will be released for these versions

Documentation

Updates to Docker Hub and NGC repos will be reflected with the v0.15 release
Updated rapids.ai release selector to reflect EOL

Rationale

Python 3.6 EOL

Due to NEP 29 support for Python 3.6 in a large number of our dependent libraries was removed in late June 2020. Some libraries are continuing to publish Python 3.6 packages; however, others are working towards discontinuing them in the near future.

Given the push of the community to focus on Python 3.7 & 3.8 we opted to spend our resources on Python 3.8 bring up for v0.15. See RSN 3 for updates.

CUDA 10.0 EOL

Given community input and the release of CUDA 11.0, the team has opted to EOL CUDA 10.0 in favor of bring up for beta support of CUDA 11.0 in v0.15. See RSN 4 for updates.

Impact

Users should migrate to Python 3.7 & CUDA 10.1 our new defaults for RAPIDS.