RAPIDS Accelerator for Apache Spark
The RAPIDS Accelerator for Apache Spark leverages GPUs to accelerate processing by combining the power of the RAPIDS cuDF library and the scale of the Spark distributed computing framework. You can run your existing Apache Spark applications on GPUs with no code change by launching Spark with the RAPIDS Accelerator for Apache Spark plugin jar and enabling a single configuration setting.
Apache Spark 3.0+ lets users provide a plugin that can replace the backend for SQL and DataFrame operations. This requires no API changes from the user. The plugin will replace SQL operations it supports with GPU accelerated versions. If an operation is not supported it will fall back to using the Spark CPU version. Note that the plugin cannot accelerate operations that manipulate RDDs directly.
Previous Releases
User Guides
The current release of RAPIDS Accelerator for Apache Spark User Guide.
Earlier release of RAPIDS Accelerator for Apache Spark User Guide.
Earlier release of RAPIDS Accelerator for Apache Spark User Guide.
Earlier release of RAPIDS Accelerator for Apache Spark User Guide.
Earlier release of RAPIDS Accelerator for Apache Spark User Guide.
Earlier release of RAPIDS Accelerator for Apache Spark User Guide.
Earlier release of RAPIDS Accelerator for Apache Spark User Guide.
Earlier release of RAPIDS Accelerator for Apache Spark User Guide.
Earlier release of RAPIDS Accelerator for Apache Spark User Guide.