},
               "custom": {
                  "fillOpacity": 10,
                  "gradientMode": "hue",
                  "showPoints": "never"
               },
               "unit": "reqps"
            }
         },
         "gridPos": {
            "h": 5,
            "w": 6,
            "x": 0,
            "y": 1
         },
         "id": 2,
         "interval": "5s",

      + if std.length(desc) > 0 then
        stat.panelOptions.withDescription(desc)
      else {},

    statRps(title, targets, desc=''):
      self.stat(title, targets, desc)
      + timeSeries.standardOptions.withUnit('reqps'),

    statPercent(title, targets, desc=''):
      self.stat(title, targets, desc)
      + timeSeries.standardOptions.withUnit('percentunit'),

    allocations(title, targets, desc=''):

    }
  }

  @Benchmark
  int arraysSortNoComparator(int reps) {
    int tmp = 0;
    for (int i = 0; i < reps; i++) {
      Integer[] copy = inputArrays[i & 0xFF].clone();
      sort(copy);
      tmp += copy[0];
    }
    return tmp;
  }

  @Benchmark
  int arraysSortOrderingNatural(int reps) {
    int tmp = 0;
    for (int i = 0; i < reps; i++) {
      Integer[] copy = inputArrays[i & 0xFF].clone();

  @Benchmark
  int weakInterner(int reps) {
    Interner<String> interner = Interners.newWeakInterner();
    for (int i = 0; i < reps; i++) {
      String unused = interner.intern(Double.toHexString(Math.random()));
    }
    return reps;
  }

  @Benchmark
  int strongInterner(int reps) {
    Interner<String> interner = Interners.newStrongInterner();
    for (int i = 0; i < reps; i++) {

    return datasets[i & 0xFF].clone();
  }

  @Benchmark
  double median(int reps) {
    double dummy = 0.0;
    for (int i = 0; i < reps; i++) {
      dummy += algorithm.singleQuantile(1, 2, dataset(i));
    }
    return dummy;
  }

  @Benchmark
  double percentile90(int reps) {
    double dummy = 0.0;
    for (int i = 0; i < reps; i++) {
      dummy += algorithm.singleQuantile(90, 100, dataset(i));
    }

    return datasets[i & 0xFF].clone();
  }

  @Benchmark
  double median(int reps) {
    double dummy = 0.0;
    for (int i = 0; i < reps; i++) {
      dummy += algorithm.singleQuantile(1, 2, dataset(i));
    }
    return dummy;
  }

  @Benchmark
  double percentile90(int reps) {
    double dummy = 0.0;
    for (int i = 0; i < reps; i++) {
      dummy += algorithm.singleQuantile(90, 100, dataset(i));
    }

  }

  @Benchmark
  int slowFactorial(int reps) {
    int tmp = 0;
    for (int i = 0; i < reps; i++) {
      int j = i & ARRAY_MASK;
      tmp += oldSlowFactorial(slowFactorials[j]).intValue();
    }
    return tmp;
  }

  @Benchmark
  int factorial(int reps) {
    int tmp = 0;
    for (int i = 0; i < reps; i++) {
      int j = i & ARRAY_MASK;

  @Benchmark
  long stopwatch(int reps) {
    long total = 0;
    for (int i = 0; i < reps; i++) {
      Stopwatch s = Stopwatch.createStarted();
      // here is where you would do something
      total += s.elapsed(NANOSECONDS);
    }
    return total;
  }

  @Benchmark
  long manual(int reps) {
    long total = 0;
    for (int i = 0; i < reps; i++) {
      long start = System.nanoTime();

  }

  @Benchmark
  int collections(int reps) {
    int dummy = 0;
    // Yes, this could be done more elegantly
    if (mutable) {
      for (int i = 0; i < reps; i++) {
        List<Integer> copy = new ArrayList<>(input);
        sort(copy);
        dummy += copy.get(0);
      }
    } else {
      for (int i = 0; i < reps; i++) {
        List<Integer> copy = new ArrayList<>(input);

  // CRC32C

  @Benchmark
  byte crc32cHashFunction(int reps) {
    return runHashFunction(reps, Hashing.crc32c());
  }

  // Adler32

  @Benchmark
  byte adler32HashFunction(int reps) {
    return runHashFunction(reps, Hashing.adler32());
  }

  @Benchmark
  byte adler32Checksum(int reps) throws Exception {
    byte result = 0x01;
    for (int i = 0; i < reps; i++) {
      Adler32 checksum = new Adler32();