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* linkedin#606 Integrated TonY GPU metrics to Dr. Elephant; linkedin#605
fixed NPE in TonYUtils * removed unused imports * Added number GPU requested metric; Updated nvidia-smi doc link * Addressed reviewer's comment (cherry picked from commit be6d03a)
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app/com/linkedin/drelephant/tony/heuristics/TaskGPUHeuristic.java
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,122 @@ | ||
| /* | ||
| * Copyright 2019 LinkedIn Corp. | ||
| * | ||
| * Licensed 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 com.linkedin.drelephant.tony.heuristics; | ||
|
|
||
| import com.linkedin.drelephant.analysis.Heuristic; | ||
| import com.linkedin.drelephant.analysis.HeuristicResult; | ||
| import com.linkedin.drelephant.analysis.HeuristicResultDetails; | ||
| import com.linkedin.drelephant.analysis.Severity; | ||
| import com.linkedin.drelephant.configurations.heuristic.HeuristicConfigurationData; | ||
| import com.linkedin.drelephant.tony.data.TonyApplicationData; | ||
| import com.linkedin.drelephant.tony.data.TonyTaskData; | ||
| import com.linkedin.drelephant.tony.util.TonyUtils; | ||
| import com.linkedin.drelephant.util.Utils; | ||
| import com.linkedin.tony.Constants; | ||
| import com.linkedin.tony.TonyConfigurationKeys; | ||
| import java.util.ArrayList; | ||
| import java.util.List; | ||
| import java.util.Map; | ||
| import java.util.Set; | ||
| import org.apache.commons.io.FileUtils; | ||
| import org.apache.hadoop.conf.Configuration; | ||
| import org.apache.log4j.Logger; | ||
|
|
||
|
|
||
| /** | ||
| * For each type of task (e.g.: worker, ps), this heuristic checks the GPU utilization across all tasks of that type | ||
| * and compares against some thresholds. The final severity is the highest severity across all task types. | ||
| */ | ||
| public class TaskGPUHeuristic implements Heuristic<TonyApplicationData> { | ||
| private static final Logger _LOGGER = Logger.getLogger(TaskGPUHeuristic.class); | ||
| private static final String[] MAX_METRICS_TO_APPLY = { | ||
| Constants.MAX_GPU_UTILIZATION, | ||
| Constants.MAX_GPU_FB_MEMORY_USAGE, | ||
| Constants.MAX_GPU_MAIN_MEMORY_USAGE}; | ||
| private static final String[] AVG_METRICS_TO_APPLY = { | ||
| Constants.AVG_GPU_UTILIZATION, | ||
| Constants.AVG_GPU_FB_MEMORY_USAGE, | ||
| Constants.AVG_GPU_MAIN_MEMORY_USAGE | ||
| }; | ||
|
|
||
| private HeuristicConfigurationData _heuristicConfData; | ||
|
|
||
| /** | ||
| * Constructor for {@link TaskGPUHeuristic}. | ||
| * @param heuristicConfData the configuration for this heuristic | ||
| */ | ||
| public TaskGPUHeuristic(HeuristicConfigurationData heuristicConfData) { | ||
| this._heuristicConfData = heuristicConfData; | ||
| } | ||
|
|
||
| @Override | ||
| public HeuristicResult apply(TonyApplicationData data) { | ||
| _LOGGER.debug("Applying TaskGPUHeuristic"); | ||
| Map<String, Map<Integer, TonyTaskData>> taskMap = data.getTaskMap(); | ||
| Configuration conf = data.getConfiguration(); | ||
|
|
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| Set<String> taskTypes = com.linkedin.tony.util.Utils.getAllJobTypes(conf); | ||
| Severity finalSeverity = Severity.NONE; | ||
| List<HeuristicResultDetails> details = new ArrayList<>(); | ||
|
|
||
| for (String taskType : taskTypes) { | ||
| details.add(new HeuristicResultDetails("Number of " + taskType + " tasks", | ||
| Integer.toString(taskMap.get(taskType).size()))); | ||
|
|
||
| // get number of GPU resource requested, if any | ||
| int numGPUsRequested = conf.getInt(TonyConfigurationKeys.getResourceKey(taskType, Constants.GPUS), 0); | ||
| if (numGPUsRequested > 0) { | ||
| details.add(new HeuristicResultDetails("Number of GPUs requested per " + taskType + " tasks", | ||
| Integer.toString(numGPUsRequested))); | ||
| } | ||
|
|
||
| // get global max gpu utilization metrics | ||
| for (String maxMetricToApply : MAX_METRICS_TO_APPLY) { | ||
| double maxMetric = TonyUtils.getMaxMetricForTaskTypeAndMetricName(taskMap, taskType, maxMetricToApply); | ||
|
|
||
| if (maxMetric <= 0 || Double.isNaN(maxMetric)) { | ||
| details.add(new HeuristicResultDetails(maxMetricToApply + " in any " + taskType + " task", "Unknown")); | ||
| continue; | ||
| } | ||
| details.add(new HeuristicResultDetails(maxMetricToApply + " in any " + taskType + " task", | ||
| String.format("%.2f", maxMetric) + "%")); | ||
| } | ||
|
|
||
| // get global average gpu utilization metrics | ||
| for (String avgMetricToApply : AVG_METRICS_TO_APPLY) { | ||
| double avgMetric = TonyUtils.getAvgMetricForTaskTypeAndMetricName(taskMap, taskType, avgMetricToApply); | ||
|
|
||
| if (avgMetric <= 0 || Double.isNaN(avgMetric)) { | ||
| details.add(new HeuristicResultDetails(avgMetricToApply + " in any " + taskType + " task", "Unknown")); | ||
| continue; | ||
| } | ||
| details.add(new HeuristicResultDetails(avgMetricToApply + " in any " + taskType + " task", | ||
| String.format("%.2f", avgMetric) + "%")); | ||
| } | ||
|
|
||
| // compare to threshold and update severity | ||
| // TODO: pass all metrics collected as not severe for now, update heuristic when collected enough data to | ||
| // determine the appropriate threshold. | ||
| } | ||
|
|
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| return new HeuristicResult(_heuristicConfData.getClassName(), _heuristicConfData.getHeuristicName(), finalSeverity, | ||
| 0, details); | ||
| } | ||
|
|
||
| @Override | ||
| public HeuristicConfigurationData getHeuristicConfData() { | ||
| return _heuristicConfData; | ||
| } | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,37 @@ | ||
| @* | ||
| * Copyright 2019 LinkedIn Corp. | ||
| * | ||
| * Licensed 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. | ||
| *@ | ||
| <p> | ||
| This heuristic shows GPU utilization and GPU memory utilization for each task type. | ||
| Try to optimize your GPU utilization! | ||
| </p> | ||
| <p> | ||
| GPU_UTILIZATION shows the percent of time over the past sample period during which one or more kernels was executing | ||
| on the GPU. | ||
| </p> | ||
| <p> | ||
| GPU_FB_MEMORY_USAGE shows the on-board frame buffer memory usage in percentage. Note, reported total memory is | ||
| affected by ECC (error-correcting code) state. If ECC is enabled the total available memory is decreased by several | ||
| percent, due to the requisite parity bits. The driver may also reserve a small amount of memory for internal use, even | ||
| without active work on the GPU. | ||
| </p> | ||
| <p> | ||
| GPU_MAIN_MEMORY_USAGE aka BAR1 memory usage shows the percentage of memory used to map the FB (device memory) so that | ||
| it can be directly accessed by CPU. | ||
| </p> | ||
| <p> | ||
| Above metrics are collected via nvidia-smi tools installed on the host, for more detailed information please visit | ||
| <a href="https://developer.nvidia.com/nvidia-system-management-interface">nvidia-smi manual</a>. | ||
| </p> |
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