Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Fix small typo in readme #344

Merged
merged 1 commit into from
Jul 11, 2020
Merged

Fix small typo in readme #344

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 2 additions & 2 deletions README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
# RAPIDS Accelerator For Apache Spark
NOTE: For the latest stable [README.md](https://github.com/nvidia/spark-rapids/blob/main/README.md) ensure you are on the main branch. The RAPIDS Accelerator for Apache Spark provides a set of plugins for Apache Spark that leverage GPUs to accelerate processing via the RAPIDS libraries and UCX. Documentation on the current release can be found at [here](https://nvidia.github.io/spark-rapids/)
NOTE: For the latest stable [README.md](https://github.com/nvidia/spark-rapids/blob/main/README.md) ensure you are on the main branch. The RAPIDS Accelerator for Apache Spark provides a set of plugins for Apache Spark that leverage GPUs to accelerate processing via the RAPIDS libraries and UCX. Documentation on the current release can be found [here](https://nvidia.github.io/spark-rapids/).

The RAPIDS Accelerator for Apache Spark provides a set of plugins for
[Apache Spark](https://spark.apache.org) that leverage GPUs to accelerate processing
Expand Down Expand Up @@ -64,4 +64,4 @@ Currently, we are working with XGBoost to try to provide this integration out of

You may need to disable RMM caching when exporting data to an ML library as that library
will likely want to use all of the GPU's memory and if it is not aware of RMM it will not have
access to any of the memory that RMM is holding.
access to any of the memory that RMM is holding.