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https://github.com/intel/intel-device-plugins-for-kubernetes.git
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FPGA demo: add screencast for preprogrammed mode
This screencast demonstrates deployment scenario for FPGA preprogrammed mode. It uses Docker as a runtime to show that CRI-O is not required in this mode.
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Ed Bartosh
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@ -53,23 +53,29 @@ Only one worker node has a GPU. The time difference in transcoding speed is capt
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## Intel® FPGA Device Plugin demo videos
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The screencasts demonstrate the deployment of the Intel® FPGA Device Plugin for
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Kubernetes. Demo 1 executes a native loopback 3 (NLB3) workload, and demo 2 runs an [OpenCL workload](https://www.intel.com/content/www/us/en/programmable/support/support-resources/design-examples/design-software/opencl/matrix-multiplication.html) to do English letters recognition, and compares time used with and without FPGA to show the acceleration. The demos begin
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with a fully [configured Kubernetes cluster](https://kubernetes.io/docs/setup/independent/create-cluster-kubeadm/)
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with the [Go runtime](https://golang.org/doc/install).
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Kubernetes.
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### Demo 1 (NLB3) platform configuration
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- Demo 1 executes a native loopback 3 (NLB3) workload in preprogrammed mode
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- Demo 2 executes NLB3 workload in orchestrated mode
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- Demo 3 runs an [OpenCL workload](https://www.intel.com/content/www/us/en/programmable/support/support-resources/design-examples/design-software/opencl/matrix-multiplication.html) to do English letters recognition, and compares time used with and without FPGA to show the acceleration.
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The demos begin with a fully [configured Kubernetes cluster](https://kubernetes.io/docs/setup/independent/create-cluster-kubeadm/).
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### Demo 1 and 2 (NLB3) platform configuration
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- Hardware
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- 1-node, 2x Intel@ Xeon@ Gold 6140M CPU @ 2.30GHz
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- Total memory 377 GB
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- Intel® Arria® 10 GX FPGA
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- 1-node, Intel(R) Xeon(R) CPU E5-2650 0 @ 2.00GHz
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- Total memory 62 GB
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- 2 x Intel® Arria® 10 GX FPGA Programmable Acceleration Card(PAC)
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- Software
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- Ubuntu 18.04.2 LTS (Kernel: 4.15.0-60-generic)
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- Kubernetes* 1.13
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- CRI-O 1.13.1
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- openSUSE Leap 15.1 (Kernel: 5.4.5-1.g47eef04-default)
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- Kubernetes* 1.17
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- CRI-O 1.13.1 (for orchestrated mode)
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- Docker 19.03.1 (for preprogrammed mode)
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- runc 1.0.0-rc8
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- Intel® FPGA Device Plugin built from master branch
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### Demo 2 (OpenCL) platform configuration
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### Demo 3 (OpenCL) platform configuration
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- Hardware
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- Multi-node, FPGA host has 24 cores Intel(R) Xeon(R) Gold 6252N CPU @ 2.30GHz
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@ -86,17 +92,21 @@ with the [Go runtime](https://golang.org/doc/install).
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1. Validate the status of the [Kubernetes cluster](https://kubernetes.io/docs/setup/independent/create-cluster-kubeadm/).
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2. Clone the [Intel Device Plugins for Kubernetes source](https://github.com/intel/intel-device-plugins-for-kubernetes).
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3. Provision the [admission controller webhook](https://github.com/intel/intel-device-plugins-for-kubernetes/blob/master/cmd/fpga_admissionwebhook/README.md).
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4. Provision the [Intel® FPGA Device Plugin](https://github.com/intel/intel-device-plugins-for-kubernetes/blob/master/cmd/fpga_plugin/README.md).
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5. Build the opae-nlb-demo or fpga-opencl-centos image
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4. Create bitstream storage (for orchestrated mode only)
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5. Provision the [Intel® FPGA Device Plugin](https://github.com/intel/intel-device-plugins-for-kubernetes/blob/master/cmd/fpga_plugin/README.md).
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6. Run the NLB3 or OpenCL workload.
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### Screencasts
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Intel® FPGA Device Plugin deployment with orchestrated/region mode and NLB workload:
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- Intel® FPGA Device Plugin deployment in preprogrammed mode
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[<img src="https://asciinema.org/a/78iLCNz4W344vm4oSrDuJ6g6i.svg" width="700">](https://asciinema.org/a/78iLCNz4W344vm4oSrDuJ6g6i)
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- Intel® FPGA Device Plugin deployment with orchestrated/region mode and NLB workload:
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[<img src="https://asciinema.org/a/JuYzNxx9n0eQ1vQBzy86GYBki.svg" width="700">](https://asciinema.org/a/JuYzNxx9n0eQ1vQBzy86GYBki)
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Intel® FPGA Device Plugin deployment with orchestrated/region mode and OpenCL workload:
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- Intel® FPGA Device Plugin deployment with orchestrated/region mode and OpenCL workload:
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[<img src="https://asciinema.org/a/344184.svg" width="700">](https://asciinema.org/a/344184)
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149
demo/screencast-fpga-preprogrammed.sh
Executable file
149
demo/screencast-fpga-preprogrammed.sh
Executable file
@ -0,0 +1,149 @@
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#!/bin/bash -e
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PV='pv -qL'
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# check if FPGA devices exist
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if [ -d /sys/class/fpga ] ; then
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DRIVER=OPAE
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DEVICE_PREFIX=/dev/intel-fpga-port
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elif [ -d /sys/class/fpga_region ] ; then
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DRIVER=DFL
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DEVICE_PREFIX=/dev/dfl-port
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else
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>&2 echo 'ERROR: FPGA devices not found or kernel drivers not loaded'
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exit 1
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fi
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command()
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{
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speed=$2
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[ -z "$speed" ] && speed=10
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echo "> $1" | $PV $speed
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sh -c "$1"
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echo | $PV $speed
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}
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out()
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{
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speed=$2
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[ -z "$speed" ] && speed=10
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echo "$1" | $PV $speed
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echo | $PV $speed
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}
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cleanup()
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{
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clear
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out 'Cleanup demo artifacts' 200
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command 'kubectl delete pod test-fpga-preprogrammed || true' 200
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command 'kubectl delete -f plugins/deployments/fpga_admissionwebhook/mappings-collection.yaml || true' 200
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command 'kubectl delete -k plugins/deployments/fpga_admissionwebhook/default || true' 200
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command './plugins/scripts/deploy-fpgaplugin.sh cleanup' 200
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command 'kubectl annotate node --all fpga.intel.com/device-plugin-mode-' 200
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command 'rm -rf plugins' 200
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}
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record()
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{
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clear
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out 'Record this screencast'
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command "asciinema rec -t 'Intel FPGA Device Plugin for Kubernetes in preprogrammed mode with $DRIVER kernel driver.' Intel-FPGA-Device-Plugin-for-Kubernetes-preprogrammed-$DRIVER-Demo.cast -c 'sh ./screencast-fpga-preprogrammed.sh play'" 300
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}
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screen1()
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{
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clear
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out "This screencast demonstrates deployment of the Intel FPGA Plugin for Kubernetes in preprogrammed mode with $DRIVER kernel driver"
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out "Let's get started!"
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out '1. Check if Kubernetes node is in good shape:'
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command 'kubectl get nodes'
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command 'kubectl get pods -n kube-system'
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sleep 2
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out 'Check if cert-manager is running:'
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command 'kubectl get pods -n cert-manager'
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sleep 2
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out 'Check if docker is running k8s pods:'
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command 'docker ps --format "table {{.Names}}"'
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sleep 2
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}
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screen2()
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{
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clear
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rm -rf plugins
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out '2. Clone Intel Device Plugins for Kubernetes repository'
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command "git clone https://github.com/intel/intel-device-plugins-for-kubernetes plugins" 15
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}
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screen3()
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{
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clear
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out '3. Deploy admission controller webhook'
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command 'kubectl apply -k plugins/deployments/fpga_admissionwebhook/default'
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sleep 3
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out 'Deploy example mappings:'
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command 'kubectl apply -f plugins/deployments/fpga_admissionwebhook/mappings-collection.yaml'
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sleep 3
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out 'Check if webhook pod is running:'
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command 'kubectl get pods -n intelfpgawebhook-system'
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sleep 2
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out 'Check its logs:'
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command "kubectl logs $(kubectl get pods -n intelfpgawebhook-system| grep intelfpgawebhook-controller-manager | awk '{print $1}') -n intelfpgawebhook-system"
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sleep 2
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}
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screen4()
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{
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clear
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out '5. Deploy FPGA plugin'
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command './plugins/scripts/deploy-fpgaplugin.sh'
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sleep 4
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out 'Check if its pod is runnning:'
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command 'kubectl get pod | grep intel-fpga-plugin'
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sleep 2
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out 'Check if resource fpga.intel.com/af-<af id> is allocatable:'
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command 'kubectl describe node |grep -A4 Allocatable'
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sleep 2
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}
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screen5()
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{
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clear
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out '6. Run OPAE workload that uses NLB3 bitstream'
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out 'Check if devices are programmed with NLB3:'
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command 'cat /sys/class/*/*/*/afu_id'
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out 'Run workload:'
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command 'cat plugins/demo/test-fpga-preprogrammed.yaml'
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command 'kubectl create -f plugins/demo/test-fpga-preprogrammed.yaml'
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sleep 5
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out 'Look at the test output'
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command 'kubectl logs test-fpga-preprogrammed'
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}
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screen6()
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{
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clear
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out 'Summary:' 15
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out "This screencast demonstrated 'Preprogrammed' use case for FPGA:" 15
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out ' - FPGA device was already programmed with NLB3 bitstream' 15
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out ' - desired bitstream resource was specified in the pod spec as fpga.intel.com/arria10.dcp1.2-nlb3-preprogrammed' 15
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out ' - the machinery mapped fpga.intel.com/arria10.dcp1.2-nlb3-preprogrammed into the pair of region id/AFU id using admission controller webhook' 15
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out
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out 'More detailed information about Intel Device Plugins can be found at https://github.com/intel/intel-device-plugins-for-kubernetes' 15
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}
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if [ "$1" == 'play' ] ; then
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if [ -n "$2" ] ; then
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screen$2
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else
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for n in $(seq 6) ; do screen$n ; sleep 3; done
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fi
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elif [ "$1" == 'cleanup' ] ; then
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cleanup
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elif [ "$1" == 'record' ] ; then
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record
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else
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echo 'Usage: screencast-fpga-preprogrammed.sh [--help|help|-h] | [play [<screen number>]] | [cleanup] | [record]'
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fi
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20
demo/test-fpga-preprogrammed.yaml
Normal file
20
demo/test-fpga-preprogrammed.yaml
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apiVersion: v1
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kind: Pod
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metadata:
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name: test-fpga-preprogrammed
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spec:
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containers:
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- name: test-container
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image: intel/opae-nlb-demo:devel
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imagePullPolicy: IfNotPresent
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securityContext:
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capabilities:
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add:
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[IPC_LOCK]
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resources:
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limits:
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fpga.intel.com/arria10.dcp1.2-nlb3-preprogrammed: 1
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cpu: 1
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hugepages-2Mi: 20Mi
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restartPolicy: Never
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