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nvliyuanSameer Raheja
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Sameer Raheja
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[DOC] update cuda13 related jars in download page [skip ci] (#14476)
Fixes #14019. ### Description Since 25.10 we support CUDA 13, but the CUDA 13 jars were only added to the `release/25.12` branch (#14028) and not propagated to `main`. This PR adds the CUDA 13 download entries for the current v26.02.1 release. Changes: - Organized download table into separate "CUDA 12" and "CUDA 13" sections - Added 4 CUDA 13 jar entries (x86_64/arm64, Scala 2.12/2.13) with proper Maven coordinates - Added CUDA 13 build and testing information (built against CUDA 13.0, tested on H100 and GB100) Signed-off-by: liyuan <yuali@nvidia.com> ### Checklists - [x] This PR has added documentation for new or modified features or behaviors. - [ ] This PR has added new tests or modified existing tests to cover new code paths. - [ ] Performance testing has been performed and its results are added in the PR description. Or, an issue has been filed with a link in the PR description. --------- Signed-off-by: liyuan <yuali@nvidia.com> Signed-off-by: Sameer Raheja <sraheja@.nvidia.com> Co-authored-by: Sameer Raheja <sraheja@.nvidia.com>
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‎docs/archive.md‎

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Below are archived releases for RAPIDS Accelerator for Apache Spark.
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## Release v26.02.1
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### Hardware Requirements:
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The plugin is designed to work on NVIDIA Volta, Turing, Ampere, Ada Lovelace, Hopper and Blackwell generation datacenter GPUs. The plugin jar is tested on the following GPUs:
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GPU Models: NVIDIA V100, T4, A10, A100, L4, H100 and B100 GPUs
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### Software Requirements:
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OS: Spark RAPIDS is compatible with any Linux distribution with glibc >= 2.28 (Please check ldd --version output). glibc 2.28 was released August 1, 2018.
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Tested on Ubuntu 22.04, Ubuntu 24.04, Rocky Linux 8 and Rocky Linux 9
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NVIDIA Driver*: R525+
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Runtime:
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Scala 2.12, 2.13
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Python, Java Virtual Machine (JVM) compatible with your spark-version.
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* Check the Spark documentation for Python and Java version compatibility with your specific
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Spark version. For instance, visit `https://spark.apache.org/docs/3.4.1` for Spark 3.4.1.
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Supported Spark versions:
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Scala 2.12: Spark 3.3.x to Spark 3.5.x
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Scala 2.13: Spark 3.5.0+, 4.0.0, 4.0.1, 4.1.1
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Supported Databricks runtime versions for Azure and AWS:
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Databricks 12.2 ML LTS (GPU, Scala 2.12, Spark 3.3.2)
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Databricks 13.3 ML LTS (GPU, Scala 2.12, Spark 3.4.1)
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Databricks 14.3 ML LTS (GPU, Scala 2.12, Spark 3.5.0)
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Supported Dataproc versions (Debian/Ubuntu/Rocky):
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GCP Dataproc 2.1
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GCP Dataproc 2.2
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GCP Dataproc 2.3
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Supported Dataproc Serverless versions:
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Spark runtime 1.1 LTS
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Spark runtime 1.2
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Spark runtime 2.0
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Spark runtime 2.1
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Spark runtime 2.2
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*Some hardware may have a minimum driver version greater than R470. Check the GPU spec sheet
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for your hardware's minimum driver version.
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*For Cloudera and EMR support, please refer to the
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[Distributions](https://docs.nvidia.com/spark-rapids/user-guide/latest/faq.html#which-distributions-are-supported) section of the FAQ.
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### RAPIDS Accelerator's Support Policy for Apache Spark
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The RAPIDS Accelerator maintains support for Apache Spark versions available for download from [Apache Spark](https://spark.apache.org/downloads.html)
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### Download RAPIDS Accelerator for Apache Spark v26.02.1
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| Processor | Scala Version | Download Jar | Download Signature | Download From Maven |
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|-----------|---------------|--------------|--------------------|---------------------|
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| x86_64 | Scala 2.12 | [RAPIDS Accelerator v26.02.1](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.02.1/rapids-4-spark_2.12-26.02.1.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.02.1/rapids-4-spark_2.12-26.02.1.jar.asc) | <pre>&lt;dependency&gt;<br/> &lt;groupId&gt;com.nvidia&lt;/groupId&gt;<br/> &lt;artifactId&gt;rapids-4-spark_2.12&lt;/artifactId&gt;<br/> &lt;version&gt;26.02.1&lt;/version&gt;<br/>&lt;/dependency&gt;</pre> |
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| x86_64 | Scala 2.13 | [RAPIDS Accelerator v26.02.1](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/26.02.1/rapids-4-spark_2.13-26.02.1.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/26.02.1/rapids-4-spark_2.13-26.02.1.jar.asc) | <pre>&lt;dependency&gt;<br/> &lt;groupId&gt;com.nvidia&lt;/groupId&gt;<br/> &lt;artifactId&gt;rapids-4-spark_2.13&lt;/artifactId&gt;<br/> &lt;version&gt;26.02.1&lt;/version&gt;<br/>&lt;/dependency&gt;</pre> |
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| arm64 | Scala 2.12 | [RAPIDS Accelerator v26.02.1](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.02.1/rapids-4-spark_2.12-26.02.1-cuda12-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.02.1/rapids-4-spark_2.12-26.02.1-cuda12-arm64.jar.asc) | <pre>&lt;dependency&gt;<br/> &lt;groupId&gt;com.nvidia&lt;/groupId&gt;<br/> &lt;artifactId&gt;rapids-4-spark_2.12&lt;/artifactId&gt;<br/> &lt;version&gt;26.02.1&lt;/version&gt;<br/> &lt;classifier&gt;cuda12-arm64&lt;/classifier&gt;<br/>&lt;/dependency&gt;</pre> |
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| arm64 | Scala 2.13 | [RAPIDS Accelerator v26.02.1](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/26.02.1/rapids-4-spark_2.13-26.02.1-cuda12-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/26.02.1/rapids-4-spark_2.13-26.02.1-cuda12-arm64.jar.asc) | <pre>&lt;dependency&gt;<br/> &lt;groupId&gt;com.nvidia&lt;/groupId&gt;<br/> &lt;artifactId&gt;rapids-4-spark_2.13&lt;/artifactId&gt;<br/> &lt;version&gt;26.02.1&lt;/version&gt;<br/> &lt;classifier&gt;cuda12-arm64&lt;/classifier&gt;<br/>&lt;/dependency&gt;</pre> |
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This package is built against CUDA 12.9. It is tested on V100, T4, A10, A100, L4, H100 and GB100 GPUs with
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CUDA 12.9.
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### Verify signature
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* Download the [PUB_KEY](https://keys.openpgp.org/search?q=sw-spark@nvidia.com).
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* Import the public key: `gpg --import PUB_KEY`
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* Verify the signature for Scala 2.12 jar:
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`gpg --verify rapids-4-spark_2.12-26.02.1.jar.asc rapids-4-spark_2.12-26.02.1.jar`
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* Verify the signature for Scala 2.13 jar:
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`gpg --verify rapids-4-spark_2.13-26.02.1.jar.asc rapids-4-spark_2.13-26.02.1.jar`
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The output of signature verify:
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gpg: Good signature from "NVIDIA Spark (For the signature of spark-rapids release jars) <sw-spark@nvidia.com>"
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### Release Notes
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* Add support for Spark 4.1.1 ([#14120](https://github.com/NVIDIA/spark-rapids/pull/14120))
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* Iceberg enhancements: identity partitioning support ([#14183](https://github.com/NVIDIA/spark-rapids/pull/14183)), all types for bucket transform ([#14001](https://github.com/NVIDIA/spark-rapids/pull/14001)), and Iceberg 1.9.2 support ([#13986](https://github.com/NVIDIA/spark-rapids/pull/13986))
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* SHA-2 hash support ([#14038](https://github.com/NVIDIA/spark-rapids/pull/14038))
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* Rapids shuffle manager V2 phase 1 with pipelined write ([#13724](https://github.com/NVIDIA/spark-rapids/pull/13724))
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* Enable GPU kudo reads by default ([#14125](https://github.com/NVIDIA/spark-rapids/pull/14125))
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* Multiple deadlock and OOM fixes for improved stability ([#14202](https://github.com/NVIDIA/spark-rapids/pull/14202), [#14180](https://github.com/NVIDIA/spark-rapids/pull/14180), [#14175](https://github.com/NVIDIA/spark-rapids/pull/14175))
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For a detailed list of changes, please refer to the
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[CHANGELOG](https://github.com/NVIDIA/spark-rapids/blob/main/CHANGELOG.md).
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## Release v26.02.0
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### Hardware Requirements:
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The plugin is designed to work on NVIDIA Volta, Turing, Ampere, Ada Lovelace, Hopper and Blackwell generation datacenter GPUs. The plugin jar is tested on the following GPUs:
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GPU Models: NVIDIA V100, T4, A10, A100, L4, H100 and B100 GPUs
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### Software Requirements:
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OS: Spark RAPIDS is compatible with any Linux distribution with glibc >= 2.28 (Please check ldd --version output). glibc 2.28 was released August 1, 2018.
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Tested on Ubuntu 22.04, Ubuntu 24.04, Rocky Linux 8 and Rocky Linux 9
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NVIDIA Driver*: R525+
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Runtime:
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Scala 2.12, 2.13
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Python, Java Virtual Machine (JVM) compatible with your spark-version.
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* Check the Spark documentation for Python and Java version compatibility with your specific
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Spark version. For instance, visit `https://spark.apache.org/docs/3.4.1` for Spark 3.4.1.
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Supported Spark versions:
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Scala 2.12: Spark 3.3.x to Spark 3.5.x
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Scala 2.13: Spark 3.5.0+, 4.0.0, 4.0.1, 4.1.1
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Supported Databricks runtime versions for Azure and AWS:
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Databricks 12.2 ML LTS (GPU, Scala 2.12, Spark 3.3.2)
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Databricks 13.3 ML LTS (GPU, Scala 2.12, Spark 3.4.1)
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Databricks 14.3 ML LTS (GPU, Scala 2.12, Spark 3.5.0)
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Supported Dataproc versions (Debian/Ubuntu/Rocky):
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GCP Dataproc 2.1
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GCP Dataproc 2.2
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GCP Dataproc 2.3
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Supported Dataproc Serverless versions:
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Spark runtime 1.1 LTS
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Spark runtime 1.2
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Spark runtime 2.0
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Spark runtime 2.1
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Spark runtime 2.2
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*Some hardware may have a minimum driver version greater than R470. Check the GPU spec sheet
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for your hardware's minimum driver version.
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*For Cloudera and EMR support, please refer to the
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[Distributions](https://docs.nvidia.com/spark-rapids/user-guide/latest/faq.html#which-distributions-are-supported) section of the FAQ.
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### RAPIDS Accelerator's Support Policy for Apache Spark
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The RAPIDS Accelerator maintains support for Apache Spark versions available for download from [Apache Spark](https://spark.apache.org/downloads.html)
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### Download RAPIDS Accelerator for Apache Spark v26.02.0
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| Processor | Scala Version | Download Jar | Download Signature | Download From Maven |
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|-----------|---------------|--------------|--------------------|---------------------|
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| x86_64 | Scala 2.12 | [RAPIDS Accelerator v26.02.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.02.0/rapids-4-spark_2.12-26.02.0.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.02.0/rapids-4-spark_2.12-26.02.0.jar.asc) | <pre>&lt;dependency&gt;<br/> &lt;groupId&gt;com.nvidia&lt;/groupId&gt;<br/> &lt;artifactId&gt;rapids-4-spark_2.12&lt;/artifactId&gt;<br/> &lt;version&gt;26.02.0&lt;/version&gt;<br/>&lt;/dependency&gt;</pre> |
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| x86_64 | Scala 2.13 | [RAPIDS Accelerator v26.02.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/26.02.0/rapids-4-spark_2.13-26.02.0.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/26.02.0/rapids-4-spark_2.13-26.02.0.jar.asc) | <pre>&lt;dependency&gt;<br/> &lt;groupId&gt;com.nvidia&lt;/groupId&gt;<br/> &lt;artifactId&gt;rapids-4-spark_2.13&lt;/artifactId&gt;<br/> &lt;version&gt;26.02.0&lt;/version&gt;<br/>&lt;/dependency&gt;</pre> |
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| arm64 | Scala 2.12 | [RAPIDS Accelerator v26.02.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.02.0/rapids-4-spark_2.12-26.02.0-cuda12-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.02.0/rapids-4-spark_2.12-26.02.0-cuda12-arm64.jar.asc) | <pre>&lt;dependency&gt;<br/> &lt;groupId&gt;com.nvidia&lt;/groupId&gt;<br/> &lt;artifactId&gt;rapids-4-spark_2.12&lt;/artifactId&gt;<br/> &lt;version&gt;26.02.0&lt;/version&gt;<br/> &lt;classifier&gt;cuda12-arm64&lt;/classifier&gt;<br/>&lt;/dependency&gt;</pre> |
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| arm64 | Scala 2.13 | [RAPIDS Accelerator v26.02.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/26.02.0/rapids-4-spark_2.13-26.02.0-cuda12-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/26.02.0/rapids-4-spark_2.13-26.02.0-cuda12-arm64.jar.asc) | <pre>&lt;dependency&gt;<br/> &lt;groupId&gt;com.nvidia&lt;/groupId&gt;<br/> &lt;artifactId&gt;rapids-4-spark_2.13&lt;/artifactId&gt;<br/> &lt;version&gt;26.02.0&lt;/version&gt;<br/> &lt;classifier&gt;cuda12-arm64&lt;/classifier&gt;<br/>&lt;/dependency&gt;</pre> |
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This package is built against CUDA 12.9. It is tested on V100, T4, A10, A100, L4, H100 and GB100 GPUs with
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CUDA 12.9.
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### Verify signature
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* Download the [PUB_KEY](https://keys.openpgp.org/search?q=sw-spark@nvidia.com).
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* Import the public key: `gpg --import PUB_KEY`
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* Verify the signature for Scala 2.12 jar:
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`gpg --verify rapids-4-spark_2.12-26.02.0.jar.asc rapids-4-spark_2.12-26.02.0.jar`
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* Verify the signature for Scala 2.13 jar:
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`gpg --verify rapids-4-spark_2.13-26.02.0.jar.asc rapids-4-spark_2.13-26.02.0.jar`
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The output of signature verify:
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gpg: Good signature from "NVIDIA Spark (For the signature of spark-rapids release jars) <sw-spark@nvidia.com>"
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### Release Notes
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* Add support for Spark 4.1.1 ([#14120](https://github.com/NVIDIA/spark-rapids/pull/14120))
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* Iceberg enhancements: identity partitioning support ([#14183](https://github.com/NVIDIA/spark-rapids/pull/14183)), all types for bucket transform ([#14001](https://github.com/NVIDIA/spark-rapids/pull/14001)), and Iceberg 1.9.2 support ([#13986](https://github.com/NVIDIA/spark-rapids/pull/13986))
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* SHA-2 hash support ([#14038](https://github.com/NVIDIA/spark-rapids/pull/14038))
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* Rapids shuffle manager V2 phase 1 with pipelined write ([#13724](https://github.com/NVIDIA/spark-rapids/pull/13724))
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* Enable GPU kudo reads by default ([#14125](https://github.com/NVIDIA/spark-rapids/pull/14125))
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* Multiple deadlock and OOM fixes for improved stability ([#14202](https://github.com/NVIDIA/spark-rapids/pull/14202), [#14180](https://github.com/NVIDIA/spark-rapids/pull/14180), [#14175](https://github.com/NVIDIA/spark-rapids/pull/14175))
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For a detailed list of changes, please refer to the
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[CHANGELOG](https://github.com/NVIDIA/spark-rapids/blob/main/CHANGELOG.md).
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## Release v25.12.0
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### Hardware Requirements:
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