From ee177ab791fcfff0263fdd95d8211f2489a41a83 Mon Sep 17 00:00:00 2001 From: liyuan Date: Tue, 26 Oct 2021 08:58:46 +0800 Subject: [PATCH] capitalized all Nvidia and remove A2 from 21.06, add to 21.10 Signed-off-by: liyuan --- docs/FAQ.md | 2 +- docs/download.md | 30 +++++++++---------- docs/get-started/getting-started-aws-emr.md | 2 +- .../ExclusiveModeGpuDiscoveryPlugin.scala | 2 +- 4 files changed, 18 insertions(+), 18 deletions(-) diff --git a/docs/FAQ.md b/docs/FAQ.md index 918d81b40e1..97df8ad7794 100644 --- a/docs/FAQ.md +++ b/docs/FAQ.md @@ -35,7 +35,7 @@ release. ### What hardware is supported? -The plugin is tested and supported on V100, T4, A10, A30 and A100 datacenter GPUs. It is possible +The plugin is tested and supported on V100, T4, A2, A10, A30 and A100 datacenter GPUs. It is possible to run the plugin on GeForce desktop hardware with Volta or better architectures. GeForce hardware does not support [CUDA forward compatibility](https://docs.nvidia.com/deploy/cuda-compatibility/index.html#forward-compatibility-title), diff --git a/docs/download.md b/docs/download.md index 26248666a76..00f700d591f 100644 --- a/docs/download.md +++ b/docs/download.md @@ -23,13 +23,13 @@ Hardware Requirements: The plugin is tested on the following architectures: - GPU Architecture: NVIDIA V100, T4 and A10/A30/A100 GPUs + GPU Architecture: NVIDIA V100, T4 and A2/A10/A30/A100 GPUs Software Requirements: OS: Ubuntu 18.04, Ubuntu 20.04 or CentOS 7, CentOS 8 - CUDA & Nvidia Drivers*: 11.0-11.4 & v450.80.02+ + CUDA & NVIDIA Drivers*: 11.0-11.4 & v450.80.02+ Apache Spark 3.0.1, 3.0.2, 3.0.3, 3.1.1, 3.1.2, 3.2.0, Cloudera CDP 7.1.6, 7.1.7, Databricks 7.3 ML LTS or 8.2 ML Runtime, and GCP Dataproc 2.0 @@ -47,7 +47,7 @@ for your hardware's minimum driver version. This package is built against CUDA 11.2 and has [CUDA forward compatibility](https://docs.nvidia.com/deploy/cuda-compatibility/index.html) enabled. It is tested -on V100, T4, A30 and A100 GPUs with CUDA 11.0-11.4. For those using other types of GPUs which +on V100, T4, A2, A10, A30 and A100 GPUs with CUDA 11.0-11.4. For those using other types of GPUs which do not have CUDA forward compatibility (for example, GeForce), CUDA 11.2 is required. Users will need to ensure the minimum driver (450.80.02) and CUDA toolkit are installed on each Spark node. @@ -87,7 +87,7 @@ Software Requirements: OS: Ubuntu 18.04, Ubuntu 20.04 or CentOS 7, CentOS 8 - CUDA & Nvidia Drivers*: 11.0-11.4 & v450.80.02+ + CUDA & NVIDIA Drivers*: 11.0-11.4 & v450.80.02+ Apache Spark 3.0.1, 3.0.2, 3.0.3, 3.1.1, 3.1.2, Cloudera CDP 7.1.6, 7.1.7, Databricks 7.3 ML LTS or 8.2 ML Runtime, and GCP Dataproc 2.0 @@ -184,7 +184,7 @@ Software Requirements: OS: Ubuntu 18.04, Ubuntu 20.04 or CentOS 7, CentOS 8 - CUDA & Nvidia Drivers*: 11.0 or 11.2 & v450.80.02+ + CUDA & NVIDIA Drivers*: 11.0 or 11.2 & v450.80.02+ Apache Spark 3.0.1, 3.0.2, 3.1.1, 3.1.2, Cloudera CDP 7.1.7, and GCP Dataproc 2.0 @@ -224,7 +224,7 @@ Hardware Requirements: The plugin is tested on the following architectures: - GPU Architecture: NVIDIA V100, T4 and A2/A10/A30/A100 GPUs + GPU Architecture: NVIDIA V100, T4 and A10/A30/A100 GPUs Software Requirements: @@ -296,7 +296,7 @@ Software Requirements: OS: Ubuntu 18.04, Ubuntu 20.04 or CentOS 7, CentOS8 - CUDA & Nvidia Drivers: 10.1.2 & v418.87+, 10.2 & v440.33+ or 11.0 & v450.36+ + CUDA & NVIDIA Drivers: 10.1.2 & v418.87+, 10.2 & v440.33+ or 11.0 & v450.36+ Apache Spark 3.0.0, 3.0.1, 3.0.2, 3.1.1, Databricks 7.3 ML LTS Runtime, or GCP Dataproc 2.0 @@ -344,7 +344,7 @@ Software Requirements: OS: Ubuntu 16.04, Ubuntu 18.04 or CentOS 7 - CUDA & Nvidia Drivers: 10.1.2 & v418.87+, 10.2 & v440.33+ or 11.0 & v450.36+ + CUDA & NVIDIA Drivers: 10.1.2 & v418.87+, 10.2 & v440.33+ or 11.0 & v450.36+ Apache Spark 3.0, 3.0.1, 3.0.2, 3.1.1, Databricks 7.3 ML LTS Runtime, or GCP Dataproc 2.0 @@ -364,7 +364,7 @@ The list of all supported operations is provided [here](supported_ops.md). For a detailed list of changes, please refer to the [CHANGELOG](https://github.com/NVIDIA/spark-rapids/blob/main/CHANGELOG.md). -**_Note:_** Using Nvidia driver release 450.80.02, 450.102.04 or 460.32.03 in combination with the +**_Note:_** Using NVIDIA driver release 450.80.02, 450.102.04 or 460.32.03 in combination with the CUDA 10.1 or 10.2 toolkit may result in long read times when reading a file that is snappy compressed. In those cases we recommend either running with the CUDA 11.0 toolkit or using a newer driver. This issue is resolved in the 0.5.0 and higher releases. @@ -386,7 +386,7 @@ Software Requirements: OS: Ubuntu 16.04, Ubuntu 18.04 or CentOS 7 - CUDA & Nvidia Drivers: 10.1.2 & v418.87+, 10.2 & v440.33+ or 11.0 & v450.36+ + CUDA & NVIDIA Drivers: 10.1.2 & v418.87+, 10.2 & v440.33+ or 11.0 & v450.36+ Apache Spark 3.0, 3.0.1, 3.0.2, 3.1.1, Databricks 7.3 ML LTS Runtime, or GCP Dataproc 2.0 @@ -418,7 +418,7 @@ The list of all supported operations is provided [here](supported_ops.md). For a detailed list of changes, please refer to the [CHANGELOG](https://github.com/NVIDIA/spark-rapids/blob/main/CHANGELOG.md). -**_Note:_** Using Nvidia driver release 450.80.02, 450.102.04 or 460.32.03 in combination with the +**_Note:_** Using NVIDIA driver release 450.80.02, 450.102.04 or 460.32.03 in combination with the CUDA 10.1 or 10.2 toolkit may result in long read times when reading a file that is snappy compressed. In those cases we recommend either running with the CUDA 11.0 toolkit or using a newer driver. This issue is resolved in the 0.5.0 and higher releases. @@ -440,7 +440,7 @@ Software Requirements: OS: Ubuntu 16.04, Ubuntu 18.04 or CentOS 7 - CUDA & Nvidia Drivers: 10.1.2 & v418.87+, 10.2 & v440.33+ or 11.0 & v450.36+ + CUDA & NVIDIA Drivers: 10.1.2 & v418.87+, 10.2 & v440.33+ or 11.0 & v450.36+ Apache Spark 3.0, 3.0.1, Databricks 7.3 ML LTS Runtime, or GCP Dataproc 2.0 @@ -469,7 +469,7 @@ The list of all supported operations is provided [here](supported_ops.md). For a detailed list of changes, please refer to the [CHANGELOG](https://github.com/NVIDIA/spark-rapids/blob/main/CHANGELOG.md). -**_Note:_** Using Nvidia driver release 450.80.02, 450.102.04 or 460.32.03 in combination with the +**_Note:_** Using NVIDIA driver release 450.80.02, 450.102.04 or 460.32.03 in combination with the CUDA 10.1 or 10.2 toolkit may result in long read times when reading a file that is snappy compressed. In those cases we recommend either running with the CUDA 11.0 toolkit or using a newer driver. This issue is resolved in the 0.5.0 and higher releases. @@ -491,7 +491,7 @@ Software Requirements: OS: Ubuntu 16.04, Ubuntu 18.04 or CentOS 7 - CUDA & Nvidia Drivers: 10.1.2 & v418.87+, 10.2 & v440.33+ or 11.0 & v450.36+ + CUDA & NVIDIA Drivers: 10.1.2 & v418.87+, 10.2 & v440.33+ or 11.0 & v450.36+ Apache Spark 3.0, 3.0.1 @@ -523,7 +523,7 @@ The list of all supported operations is provided For a detailed list of changes, please refer to the [CHANGELOG](https://github.com/NVIDIA/spark-rapids/blob/main/CHANGELOG.md). -**_Note:_** Using Nvidia driver release 450.80.02, 450.102.04 or 460.32.03 in combination with the +**_Note:_** Using NVIDIA driver release 450.80.02, 450.102.04 or 460.32.03 in combination with the CUDA 10.1 or 10.2 toolkit may result in long read times when reading a file that is snappy compressed. In those cases we recommend either running with the CUDA 11.0 toolkit or using a newer driver. This issue is resolved in the 0.5.0 and higher releases. diff --git a/docs/get-started/getting-started-aws-emr.md b/docs/get-started/getting-started-aws-emr.md index b8f356296d6..4b1140531ad 100644 --- a/docs/get-started/getting-started-aws-emr.md +++ b/docs/get-started/getting-started-aws-emr.md @@ -26,7 +26,7 @@ documentation](https://docs.aws.amazon.com/emr/latest/ManagementGuide/emr-what-i ## Configure and Launch AWS EMR with GPU Nodes -The following steps are based on the AWS EMR document ["Using the Nvidia Spark-RAPIDS Accelerator +The following steps are based on the AWS EMR document ["Using the NVIDIA Spark-RAPIDS Accelerator for Spark"](https://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-spark-rapids.html) ### Launch an EMR Cluster using AWS CLI diff --git a/sql-plugin/src/main/scala/com/nvidia/spark/ExclusiveModeGpuDiscoveryPlugin.scala b/sql-plugin/src/main/scala/com/nvidia/spark/ExclusiveModeGpuDiscoveryPlugin.scala index 646ee984702..3e77021d451 100644 --- a/sql-plugin/src/main/scala/com/nvidia/spark/ExclusiveModeGpuDiscoveryPlugin.scala +++ b/sql-plugin/src/main/scala/com/nvidia/spark/ExclusiveModeGpuDiscoveryPlugin.scala @@ -25,7 +25,7 @@ import org.apache.spark.api.resource.ResourceDiscoveryPlugin import org.apache.spark.resource.{ResourceInformation, ResourceRequest} /** - * A Spark Resource Discovery Plugin that relies on the Nvidia GPUs being in PROCESS_EXCLUSIVE + * A Spark Resource Discovery Plugin that relies on the NVIDIA GPUs being in PROCESS_EXCLUSIVE * mode so that it can discover free GPUs. * This plugin iterates through all the GPUs on the node and tries to initialize a CUDA context * on each one. When the GPUs are in process exclusive mode this