hadoop GpuResourcePlugin 源码

haddop GpuResourcePlugin 代码

文件路径：/hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-nodemanager/src/main/java/org/apache/hadoop/yarn/server/nodemanager/containermanager/resourceplugin/gpu/GpuResourcePlugin.java

/**
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.apache.hadoop.yarn.server.nodemanager.containermanager.resourceplugin.gpu;

import java.util.List;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.yarn.conf.YarnConfiguration;
import org.apache.hadoop.yarn.exceptions.YarnException;
import org.apache.hadoop.yarn.server.nodemanager.ContainerExecutor;
import org.apache.hadoop.yarn.server.nodemanager.Context;
import org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor;
import org.apache.hadoop.yarn.server.nodemanager.containermanager.linux.privileged.PrivilegedOperationExecutor;
import org.apache.hadoop.yarn.server.nodemanager.containermanager.linux.resources.CGroupsHandler;
import org.apache.hadoop.yarn.server.nodemanager.containermanager.linux.resources.ResourceHandler;
import org.apache.hadoop.yarn.server.nodemanager.containermanager.linux.resources.gpu.GpuResourceAllocator;
import org.apache.hadoop.yarn.server.nodemanager.containermanager.linux.resources.gpu.GpuResourceHandlerImpl;
import org.apache.hadoop.yarn.server.nodemanager.containermanager.resourceplugin.DockerCommandPlugin;
import org.apache.hadoop.yarn.server.nodemanager.containermanager.resourceplugin.NodeResourceUpdaterPlugin;
import org.apache.hadoop.yarn.server.nodemanager.containermanager.resourceplugin.ResourcePlugin;
import org.apache.hadoop.yarn.server.nodemanager.webapp.dao.NMResourceInfo;
import org.apache.hadoop.yarn.server.nodemanager.webapp.dao.gpu.GpuDeviceInformation;
import org.apache.hadoop.yarn.server.nodemanager.webapp.dao.gpu.NMGpuResourceInfo;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

public class GpuResourcePlugin implements ResourcePlugin {

  private static final Logger LOG =
      LoggerFactory.getLogger(GpuResourcePlugin.class);

  private final GpuNodeResourceUpdateHandler resourceDiscoverHandler;
  private final GpuDiscoverer gpuDiscoverer;
  public static final int MAX_REPEATED_ERROR_ALLOWED = 10;

  private int numOfErrorExecutionSinceLastSucceed = 0;

  private GpuResourceHandlerImpl gpuResourceHandler = null;
  private DockerCommandPlugin dockerCommandPlugin = null;

  public GpuResourcePlugin(GpuNodeResourceUpdateHandler resourceDiscoverHandler,
      GpuDiscoverer gpuDiscoverer) {
    this.resourceDiscoverHandler = resourceDiscoverHandler;
    this.gpuDiscoverer = gpuDiscoverer;
  }

  @Override
  public void initialize(Context context) throws YarnException {
    validateExecutorConfig(context.getConf());
    this.gpuDiscoverer.initialize(context.getConf(),
        new NvidiaBinaryHelper());
    this.dockerCommandPlugin =
        GpuDockerCommandPluginFactory.createGpuDockerCommandPlugin(
            context.getConf());
  }

  private void validateExecutorConfig(Configuration conf) {
    Class<? extends ContainerExecutor> executorClass = conf.getClass(
        YarnConfiguration.NM_CONTAINER_EXECUTOR, DefaultContainerExecutor.class,
        ContainerExecutor.class);

    if (executorClass.equals(DefaultContainerExecutor.class)) {
      LOG.warn("Using GPU plugin with disabled LinuxContainerExecutor" +
          " is considered to be unsafe.");
    }
  }

  @Override
  public ResourceHandler createResourceHandler(
      Context context, CGroupsHandler cGroupsHandler,
      PrivilegedOperationExecutor privilegedOperationExecutor) {
    if (gpuResourceHandler == null) {
      gpuResourceHandler = new GpuResourceHandlerImpl(context, cGroupsHandler,
          privilegedOperationExecutor, gpuDiscoverer);
    }

    return gpuResourceHandler;
  }

  @Override
  public NodeResourceUpdaterPlugin getNodeResourceHandlerInstance() {
    return resourceDiscoverHandler;
  }

  @Override
  public void cleanup() throws YarnException {
    // Do nothing.
  }

  public DockerCommandPlugin getDockerCommandPluginInstance() {
    return dockerCommandPlugin;
  }

  @Override
  public synchronized NMResourceInfo getNMResourceInfo() throws YarnException {
    final GpuDeviceInformation gpuDeviceInformation;

    if (gpuDiscoverer.isAutoDiscoveryEnabled()) {
      //At this point the gpu plugin is already enabled
      checkGpuResourceHandler();

      checkErrorCount();
      try{
        gpuDeviceInformation = gpuDiscoverer.getGpuDeviceInformation();
        numOfErrorExecutionSinceLastSucceed = 0;
      } catch (YarnException e) {
        LOG.error(e.getMessage(), e);
        numOfErrorExecutionSinceLastSucceed++;
        throw e;
      }
    } else {
      gpuDeviceInformation = null;
    }
    GpuResourceAllocator gpuResourceAllocator =
        gpuResourceHandler.getGpuAllocator();
    List<GpuDevice> totalGpus = gpuResourceAllocator.getAllowedGpus();
    List<AssignedGpuDevice> assignedGpuDevices =
        gpuResourceAllocator.getAssignedGpus();
    return new NMGpuResourceInfo(gpuDeviceInformation, totalGpus,
        assignedGpuDevices);
  }

  private void checkGpuResourceHandler() throws YarnException {
    if(gpuResourceHandler == null) {
      String errorMsg =
          "Linux Container Executor is not configured for the NodeManager. "
              + "To fully enable GPU feature on the node also set "
              + YarnConfiguration.NM_CONTAINER_EXECUTOR + " properly.";
      LOG.warn(errorMsg);
      throw new YarnException(errorMsg);
    }
  }

  private void checkErrorCount() throws YarnException {
    if (numOfErrorExecutionSinceLastSucceed == MAX_REPEATED_ERROR_ALLOWED) {
      String msg =
          "Failed to execute GPU device information detection script for "
              + MAX_REPEATED_ERROR_ALLOWED
              + " times, skip following executions.";
      LOG.error(msg);
      throw new YarnException(msg);
    }
  }

  @Override
  public String toString() {
    return GpuResourcePlugin.class.getName();
  }
}

相关信息

hadoop 源码目录

相关文章

hadoop AssignedGpuDevice 源码

hadoop GpuDevice 源码

hadoop GpuDeviceSpecificationException 源码

hadoop GpuDiscoverer 源码

hadoop GpuDockerCommandPluginFactory 源码

hadoop GpuNodeResourceUpdateHandler 源码

hadoop NvidiaBinaryHelper 源码

hadoop NvidiaDockerV1CommandPlugin 源码

hadoop NvidiaDockerV2CommandPlugin 源码

hadoop package-info 源码