1 files changed, 123 insertions, 0 deletions
diff --git a/BenchmarkFramework/app/src/main/java/art_benchmarks/benchmarksgame/spectralnorm.java b/BenchmarkFramework/app/src/main/java/art_benchmarks/benchmarksgame/spectralnorm.java
new file mode 100644
index 0000000..e00a4b6
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+++ b/BenchmarkFramework/app/src/main/java/art_benchmarks/benchmarksgame/spectralnorm.java
@@ -0,0 +1,123 @@
+/*
+ * This benchmark has been ported from "The Computer Language Benchmarks Game" suite and slightly
+ * modified to fit the benchmarking framework.
+ *
+ * The original file is `spectralnorm/spectralnorm.java` from the archive
+ * available at
+ * http://benchmarksgame.alioth.debian.org/download/benchmarksgame-sourcecode.zip.
+ * See LICENSE file in the same folder (BSD 3-clause)
+ *
+ * The Computer Language Benchmarks Game
+ * http://benchmarksgame.alioth.debian.org/
+ *
+ * contributed by Java novice Jarkko Miettinen
+ * modified ~3 lines of the original C#-version
+ * by Isaac Gouy
+ */
+
+ /*
+ * Description:     Eigenvalue using the power method.
+ * Main Focus:      TODO
+ *
+ */
+
+package art_benchmarks.benchmarksgame;
+
+import java.text.DecimalFormat;
+import java.text.NumberFormat; 
+
+// CHECKSTYLE.OFF: .*
+public class spectralnorm
+{
+   
+   private static final NumberFormat formatter = new DecimalFormat("#.000000000");
+   
+   private final double Approximate(int n) {
+      // create unit vector
+      double[] u = new double[n];
+      for (int i=0; i<n; i++) u[i] =  1;
+      
+      // 20 steps of the power method
+      double[] v = new double[n];
+      for (int i=0; i<n; i++) v[i] = 0;
+      
+      for (int i=0; i<10; i++) {
+         MultiplyAtAv(n,u,v);
+         MultiplyAtAv(n,v,u);
+      }
+      
+      // B=AtA         A multiplied by A transposed
+      // v.Bv /(v.v)   eigenvalue of v
+      double vBv = 0, vv = 0;
+      for (int i=0; i<n; i++) {
+         vBv += u[i]*v[i];
+         vv  += v[i]*v[i];
+      }
+      
+      return Math.sqrt(vBv/vv);
+   }
+   
+   
+   /* return element i,j of infinite matrix A */
+   private final double A(int i, int j){
+      return 1.0/((i+j)*(i+j+1)/2 +i+1);
+   }
+   
+   /* multiply vector v by matrix A */
+   private final void MultiplyAv(int n, double[] v, double[] Av){
+      for (int i=0; i<n; i++){
+         Av[i] = 0;
+         for (int j=0; j<n; j++) Av[i] += A(i,j)*v[j];
+      }
+   }
+   
+   /* multiply vector v by matrix A transposed */
+   private final void MultiplyAtv(int n, double[] v, double[] Atv){
+      for (int i=0;i<n;i++){
+         Atv[i] = 0;
+         for (int j=0; j<n; j++) Atv[i] += A(j,i)*v[j];
+      }
+   }
+   
+   /* multiply vector v by matrix A and then by matrix A transposed */
+   private final void MultiplyAtAv(int n, double[] v, double[] AtAv){
+      double[] u = new double[n];
+      MultiplyAv(n,v,u);
+      MultiplyAtv(n,u,AtAv);
+   }
+   // CHECKSTYLE.ON: .*
+
+  private static final int APPROXIMATE_N = 100;
+
+  public boolean verifySpectralNorm() {
+    double expected = 1.2742199912349306;
+    double found = Approximate(APPROXIMATE_N);
+
+    if (Math.abs(expected - found) > 0.000000001) {
+      System.out.println("ERROR: Expected " + expected + " but found " + found);
+      return false;
+    }
+    return true;
+  }
+
+  public void timeSpectralNorm(int iters) {
+    for (int j = 0; j < iters; j++) {
+      Approximate(APPROXIMATE_N);
+    }
+  }
+
+  public static void main(String[] args) {
+    int rc = 0;
+    spectralnorm obj = new spectralnorm();
+
+    final long before = System.currentTimeMillis();
+    obj.timeSpectralNorm(100);
+    final long after = System.currentTimeMillis();
+
+    if (!obj.verifySpectralNorm()) {
+      rc++;
+    }
+    System.out.println("art_benchmarks/benchmarksgame/spectralnorm: " + (after - before));
+    System.exit(rc);
+  }
+}