if (this.text === level) {
                                this.click();
                            }
                        });

                        var divider = \$("<hr>");
                        divider.css({ margin: "5px" });
                        var tip = \$("<small>").text("Use the 'bin.cmp.report.severity.filter' property to set the default severity filter");

  // to the given dividend, so that we don't have half of our divisions being
  // trivial because the divisor is bigger than the dividend.
  // Using remainder here does not give us a uniform distribution but it should
  // not have a big impact on the measurement.
  private static long randomDivisor(long dividend) {
    long r = RANDOM_SOURCE.nextLong();
    if (dividend == -1) {
      return r;
    } else {

  // to the given dividend, so that we don't have half of our divisions being
  // trivial because the divisor is bigger than the dividend.
  // Using remainder here does not give us a uniform distribution but it should
  // not have a big impact on the measurement.
  private static long randomDivisor(long dividend) {
    long r = RANDOM_SOURCE.nextLong();
    if (dividend == -1) {
      return r;
    } else {

    return Tables.transformValues(table, DIVIDE_BY_2);
  }

  @Override
  protected Map<String, Integer> makePopulatedMap() {
    Table<String, Character, Integer> table = HashBasedTable.create();
    table.put("one", 'a', 1);
    table.put("two", 'a', 2);
    table.put("three", 'a', 3);
    table.put("four", 'b', 4);
    return Tables.transformValues(table, DIVIDE_BY_2).column('a');
  }

        } else if (size.divide(ONE_GB_BI).compareTo(BigInteger.ZERO) > 0) {
            displaySize = new BigDecimal(size.divide(ONE_MB_BI)).divide(BigDecimal.valueOf(1000)) + "GB";
        } else if (size.divide(ONE_MB_BI).compareTo(BigInteger.ZERO) > 0) {
            displaySize = new BigDecimal(size.divide(ONE_KB_BI)).divide(BigDecimal.valueOf(1000)) + "MB";

      int j = i & ARRAY_MASK;
      tmp += IntMath.sqrt(positive[j], mode);
    }
    return tmp;
  }

  @Benchmark
  int divide(int reps) {
    int tmp = 0;
    for (int i = 0; i < reps; i++) {
      int j = i & ARRAY_MASK;
      tmp += IntMath.divide(ints[j], nonzero[j], mode);
    }
    return tmp;
  }

## How are drives used for Erasure Code?

MinIO divides the drives you provide into erasure-coding sets of *2 to 16* drives.  Therefore, the number of drives you present must be a multiple of one of these numbers.  Each object is written to a single erasure-coding set.

      int j = i & ARRAY_MASK;
      tmp += LongMath.sqrt(positive[j], mode);
    }
    return tmp;
  }

  @Benchmark
  int divide(int reps) {
    int tmp = 0;
    for (int i = 0; i < reps; i++) {
      int j = i & ARRAY_MASK;
      tmp += LongMath.divide(longs[j], nonzero[j], mode);
    }
    return tmp;
  }

      int j = i & ARRAY_MASK;
      tmp += BigIntegerMath.sqrt(positive[j], mode).intValue();
    }
    return tmp;
  }

  @Benchmark
  int divide(int reps) {
    int tmp = 0;
    for (int i = 0; i < reps; i++) {
      int j = i & ARRAY_MASK;
      tmp += BigIntegerMath.divide(nonzero1[j], nonzero2[j], mode).intValue();
    }
    return tmp;
  }

  @Benchmark
  long roundToDouble(int reps) {
    long tmp = 0;

    return Tables.transformValues(table, DIVIDE_BY_2);
  }

  @Override
  protected Map<String, Integer> makePopulatedMap() {
    Table<String, Character, Integer> table = HashBasedTable.create();
    table.put("one", 'a', 1);
    table.put("two", 'a', 2);
    table.put("three", 'a', 3);
    table.put("four", 'b', 4);
    return Tables.transformValues(table, DIVIDE_BY_2).column('a');
  }