diff --git a/src/main/java/edu/thi/phga/aparapi_test/App.java b/src/main/java/edu/thi/phga/aparapi_test/App.java
index 45d861e..47f83d7 100644
--- a/src/main/java/edu/thi/phga/aparapi_test/App.java
+++ b/src/main/java/edu/thi/phga/aparapi_test/App.java
@@ -143,6 +143,9 @@ public class App {
       case 90:
         System.out.println("Matrix Gauss");
         MatrixGauss.start();
+      case 100:
+        System.out.println("Matrix Reduzieren (WS2019)");
+        MatrixReduce.start();
     }
   }
 }
diff --git a/src/main/java/edu/thi/phga/aparapi_test/MatrixReduce.java b/src/main/java/edu/thi/phga/aparapi_test/MatrixReduce.java
new file mode 100644
index 0000000..fddc47c
--- /dev/null
+++ b/src/main/java/edu/thi/phga/aparapi_test/MatrixReduce.java
@@ -0,0 +1,53 @@
+package edu.thi.phga.aparapi_test;
+
+import java.util.Random;
+
+import com.aparapi.Kernel;
+
+public class MatrixReduce {
+  static final int N = 6;
+  static final int F = 2;
+  public static void start() {
+    var in = new Random().ints(N * N, 1, 10).toArray();
+    var out = new float[N / F * N / F];
+
+    System.out.println("IN:");
+
+    for (int i = 0; i < N; i++) {
+      for (int j = 0; j < N; j++) {
+        System.out.printf("%2d ", in[i * N + j]);
+      }
+      System.out.println();
+    }
+
+    reduziere(in, out);
+
+    System.out.println("OUT:");
+
+    for (int i = 0; i < N / F; i++) {
+      for (int j = 0; j < N / F; j++) {
+        System.out.printf("%.1f ", out[i * N / F + j]);
+      }
+      System.out.println();
+    }
+  }
+
+  public static void reduziere(int[] in, float[] out) {
+    class MyKernel extends Kernel {
+      @Override public void run() {
+        int i = getGlobalId(0);
+        float sum = 0;
+
+        for (int k = 0; k < F; k++) {
+          for (int x = 0; x < F; x++) {
+            sum += in[(i % F) * F + k * N + ((int) i / F) * N + x];
+          }
+        }
+        out[i] = sum / (F * F);
+      }
+    }
+
+    MyKernel k = new MyKernel();
+    k.execute(out.length);
+  }
+}