tillrohrmann commented on a change in pull request #12398:
URL: https://github.com/apache/flink/pull/12398#discussion_r438073416



##########
File path: 
flink-examples/flink-examples-streaming/src/main/java/org/apache/flink/streaming/examples/gpu/MatrixVectorMul.java
##########
@@ -0,0 +1,258 @@
+/*
+ * 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.flink.streaming.examples.gpu;
+
+import org.apache.flink.api.common.externalresource.ExternalResourceInfo;
+import org.apache.flink.api.common.functions.RichMapFunction;
+import org.apache.flink.api.common.serialization.SimpleStringEncoder;
+import org.apache.flink.api.java.utils.ParameterTool;
+import org.apache.flink.configuration.Configuration;
+import org.apache.flink.core.fs.Path;
+import org.apache.flink.streaming.api.datastream.DataStream;
+import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
+import 
org.apache.flink.streaming.api.functions.sink.filesystem.StreamingFileSink;
+import org.apache.flink.streaming.api.functions.source.RichSourceFunction;
+import org.apache.flink.util.Preconditions;
+
+import jcuda.Pointer;
+import jcuda.Sizeof;
+import jcuda.jcublas.JCublas;
+import jcuda.runtime.JCuda;
+
+import java.util.ArrayList;
+import java.util.List;
+import java.util.Optional;
+import java.util.Set;
+import java.util.UUID;
+
+/**
+ * Implement the matrix-vector multiplication program that show how to 
leverage GPU resources in Flink.
+ *
+ * <p>The input is a vector stream from a {@link RandomVectorSource}, which 
will generate random vectors with specified
+ * dimension. The data size of the vector stream could be specified by user. 
Each vector will be multiplied with a random
+ * dimension * dimension matrix in {@link Multiplier} and the result would be 
emitted to output.
+ *
+ * <p>Usage: MatrixVectorMul [--output &lt;path&gt;] [--dimension 
&lt;dimension&gt; --data-size &lt;data_size&gt;]
+ *
+ * <p>If no parameters are provided, the program is run with default vector 
dimension 10 and data size 100.
+ *
+ * <p>This example shows how to:
+ * <ul>
+ * <li>leverage external resource in operators,
+ * <li>accelerate complex calculation with GPU resources.
+ * </ul>
+ *
+ * <p>Notice that you need to add jcuda natives libraries by executing 
example/streaming/add-jcuda-dependency.sh in your Flink distribution.
+ */
+public class MatrixVectorMul {
+
+       private static final int DEFAULT_DIM = 10;
+       private static final int DEFAULT_DATA_SIZE = 100;
+       private static final String DEFAULT_RESOURCE_NAME = "gpu";
+
+       public static void main(String[] args) throws Exception {
+
+               // Checking input parameters
+               final ParameterTool params = ParameterTool.fromArgs(args);
+               System.out.println("Usage: MatrixVectorMul [--output <path>] 
[--dimension <dimension> --data-size <data_size>] [--resource-name 
<resource_name>]");
+
+               // Set up the execution environment
+               final StreamExecutionEnvironment env = 
StreamExecutionEnvironment.getExecutionEnvironment();
+
+               // Make parameters available in the web interface
+               env.getConfig().setGlobalJobParameters(params);
+
+               int dimension;
+               if (params.has("dimension")) {
+                       dimension = params.getInt("dimension");
+               } else {
+                       System.out.println(String.format("Executing 
MatrixVectorMul example with default vector dimension %d.\nUse --dimension to 
specify dimension of input vector.", DEFAULT_DIM));
+                       dimension = DEFAULT_DIM;
+               }
+
+               int dataSize;
+               if (params.has("data-size")) {
+                       dataSize = params.getInt("data-size");
+               } else {
+                       System.out.println(String.format("Executing 
MatrixVectorMul example with default data size %d.\nUse --data-size to specify 
size of the vector stream.", DEFAULT_DATA_SIZE));
+                       dataSize = DEFAULT_DATA_SIZE;
+               }
+
+               String resourceName;
+               if (params.has("resource-name")) {
+                       resourceName = params.get("resource-name");
+               } else {
+                       System.out.println(String.format("Executing 
MatrixVectorMul example with default resource name %s.\nUse --resource-name to 
specify resource name of GPU.", DEFAULT_RESOURCE_NAME));
+                       resourceName = DEFAULT_RESOURCE_NAME;
+               }
+
+               DataStream<List<Float>> result = env.addSource(new 
RandomVectorSource(dimension, dataSize))
+                                               .map(new Multiplier(dimension, 
resourceName));
+
+               // Emit result
+               if (params.has("output")) {
+                       result.addSink(StreamingFileSink.forRowFormat(new 
Path(params.get("output")),
+                                       new 
SimpleStringEncoder<List<Float>>()).build());
+               } else {
+                       System.out.println("Printing result to stdout. Use 
--output to specify output path.");
+                       result.print();
+               }
+               // Execute program
+               env.execute("Matrix-Vector Multiplication");
+       }
+
+       // 
*************************************************************************
+       // USER FUNCTIONS
+       // 
*************************************************************************
+
+       /**
+        * Random vector source which generates random vectors with specified 
dimension and total data size.
+        */
+       private static final class RandomVectorSource extends 
RichSourceFunction<List<Float>> {
+
+               private transient volatile boolean running;
+               private final int dimension;
+               private final int dataSize;
+
+               RandomVectorSource(int dimension, int dataSize) {
+                       this.dimension = dimension;
+                       this.dataSize = dataSize;
+               }
+
+               @Override
+               public void open(Configuration parameters) {
+                       running = true;
+               }
+
+               @Override
+               public void run(SourceContext<List<Float>> ctx) {
+                       int count = 0;
+                       while (running && count < dataSize) {
+                               List<Float> randomRecord = new ArrayList<>();
+                               for (int i = 0; i < dimension; ++i) {
+                                       randomRecord.add((float) Math.random());
+                               }
+                               ctx.collect(randomRecord);
+                               count += 1;
+                       }
+               }
+
+               @Override
+               public void cancel() {
+                       running = false;
+               }
+       }
+
+       /**
+        * Matrix-Vector multiplier using CUBLAS library.
+        */
+       private static final class Multiplier extends 
RichMapFunction<List<Float>, List<Float>> {
+               private final int dimension;
+               private final String resourceName;
+               private Pointer matrixPointer;
+
+               Multiplier(int dimension, String resourceName) {
+                       this.dimension = dimension;
+                       this.resourceName = resourceName;
+               }
+
+               @Override
+               public void open(Configuration parameters) {
+                       // When multiple instances of this class and JCuda 
exist in different class loaders, then we will get UnsatisfiedLinkError.
+                       // To avoid that, we need to temporarily override the 
java.io.tmpdir, where the JCuda store its native library, with a random path.

Review comment:
       Makes sense. Thanks for verifying it @KarmaGYZ.




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