From 6c895b329d90730d41cfa131f504c431c351f204 Mon Sep 17 00:00:00 2001 From: Mary Camp Date: Tue, 17 Jul 2018 01:36:38 -0400 Subject: [PATCH] Update device-plugins.md to add Example link (#9531) Added link to Intel device plugins repo. Minor grammar/punctuation edits to make Example bullets parallel. --- .../extend-kubernetes/compute-storage-net/device-plugins.md | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/content/en/docs/concepts/extend-kubernetes/compute-storage-net/device-plugins.md b/content/en/docs/concepts/extend-kubernetes/compute-storage-net/device-plugins.md index 71e542b1ba..8186939e9a 100644 --- a/content/en/docs/concepts/extend-kubernetes/compute-storage-net/device-plugins.md +++ b/content/en/docs/concepts/extend-kubernetes/compute-storage-net/device-plugins.md @@ -141,12 +141,13 @@ ensure the continuous functioning of the device allocations during the upgrade. For examples of device plugin implementations, see: * The official [NVIDIA GPU device plugin](https://github.com/NVIDIA/k8s-device-plugin) - * it requires using [nvidia-docker 2.0](https://github.com/NVIDIA/nvidia-docker) which allows you to run GPU enabled docker containers -* The [NVIDIA GPU device plugin for COS base OS](https://github.com/GoogleCloudPlatform/container-engine-accelerators/tree/master/cmd/nvidia_gpu). + * Requires [nvidia-docker 2.0](https://github.com/NVIDIA/nvidia-docker) which allows you to run GPU enabled docker containers. +* The [NVIDIA GPU device plugin for COS base OS](https://github.com/GoogleCloudPlatform/container-engine-accelerators/tree/master/cmd/nvidia_gpu) * The [RDMA device plugin](https://github.com/hustcat/k8s-rdma-device-plugin) * The [Solarflare device plugin](https://github.com/vikaschoudhary16/sfc-device-plugin) * The [AMD GPU device plugin](https://github.com/RadeonOpenCompute/k8s-device-plugin) * The [SRIOV Network device plugin](https://github.com/intel/sriov-network-device-plugin) +* The [Intel device plugins](https://github.com/intel/intel-device-plugins-for-kubernetes) for GPU and FPGA devices {{% /capture %}}