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How to carry out NVIDIA and k8s-device-plugin source code analysis, in view of this problem, this article introduces the corresponding analysis and answers in detail, hoping to help more partners who want to solve this problem to find a more simple and easy way.

K8s-device-plugin internal implementation schematic diagram

In how Kubernetes uses NVIDIA GPU through Device Plugins, this paper makes an in-depth analysis of the working principle of NVIDIA/k8s-device-plugin, in order to facilitate us to post its internal implementation schematic diagram again:

PreStartContainer and GetDevicePluginOptions interfaces, which can be ignored in NVIDIA/k8s-device-plugin, can be considered empty implementations. We focus on the implementation of ListAndWatch and Allocate.

Start

It all starts with the main function! The core code is as follows:

Func main () {log.Println ("Loading NVML") if err: = nvml.Init (); err! = nil {select {}}. Log.Println ("Fetching devices.") If len (getDevices ()) = 0 {select {}} log.Println ("Starting FS watcher.") Watcher, err: = newFSWatcher (pluginapi.DevicePluginPath) if err! = nil {os.Exit (1)}. Log.Println ("Starting OS watcher.") Sigs: = newOSWatcher (syscall.SIGHUP, syscall.SIGINT, syscall.SIGTERM Syscall.SIGQUIT) restart: = true var devicePlugin * NvidiaDevicePluginL: for {if restart {if devicePlugin! = nil {devicePlugin.Stop ()} devicePlugin = NewNvidiaDevicePlugin () if err: = devicePlugin.Serve () Err! = nil {...} else {restart = false}} select {case event: =

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