115 732 799 999 999 323 Converted to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 115 732 799 999 999 323(10) to 32 bit single precision IEEE 754 binary floating point representation standard (1 bit for sign, 8 bits for exponent, 23 bits for mantissa)

What are the steps to convert decimal number
115 732 799 999 999 323(10) to 32 bit single precision IEEE 754 binary floating point representation (1 bit for sign, 8 bits for exponent, 23 bits for mantissa)

1. Divide the number repeatedly by 2.

Keep track of each remainder.

We stop when we get a quotient that is equal to zero.


  • division = quotient + remainder;
  • 115 732 799 999 999 323 ÷ 2 = 57 866 399 999 999 661 + 1;
  • 57 866 399 999 999 661 ÷ 2 = 28 933 199 999 999 830 + 1;
  • 28 933 199 999 999 830 ÷ 2 = 14 466 599 999 999 915 + 0;
  • 14 466 599 999 999 915 ÷ 2 = 7 233 299 999 999 957 + 1;
  • 7 233 299 999 999 957 ÷ 2 = 3 616 649 999 999 978 + 1;
  • 3 616 649 999 999 978 ÷ 2 = 1 808 324 999 999 989 + 0;
  • 1 808 324 999 999 989 ÷ 2 = 904 162 499 999 994 + 1;
  • 904 162 499 999 994 ÷ 2 = 452 081 249 999 997 + 0;
  • 452 081 249 999 997 ÷ 2 = 226 040 624 999 998 + 1;
  • 226 040 624 999 998 ÷ 2 = 113 020 312 499 999 + 0;
  • 113 020 312 499 999 ÷ 2 = 56 510 156 249 999 + 1;
  • 56 510 156 249 999 ÷ 2 = 28 255 078 124 999 + 1;
  • 28 255 078 124 999 ÷ 2 = 14 127 539 062 499 + 1;
  • 14 127 539 062 499 ÷ 2 = 7 063 769 531 249 + 1;
  • 7 063 769 531 249 ÷ 2 = 3 531 884 765 624 + 1;
  • 3 531 884 765 624 ÷ 2 = 1 765 942 382 812 + 0;
  • 1 765 942 382 812 ÷ 2 = 882 971 191 406 + 0;
  • 882 971 191 406 ÷ 2 = 441 485 595 703 + 0;
  • 441 485 595 703 ÷ 2 = 220 742 797 851 + 1;
  • 220 742 797 851 ÷ 2 = 110 371 398 925 + 1;
  • 110 371 398 925 ÷ 2 = 55 185 699 462 + 1;
  • 55 185 699 462 ÷ 2 = 27 592 849 731 + 0;
  • 27 592 849 731 ÷ 2 = 13 796 424 865 + 1;
  • 13 796 424 865 ÷ 2 = 6 898 212 432 + 1;
  • 6 898 212 432 ÷ 2 = 3 449 106 216 + 0;
  • 3 449 106 216 ÷ 2 = 1 724 553 108 + 0;
  • 1 724 553 108 ÷ 2 = 862 276 554 + 0;
  • 862 276 554 ÷ 2 = 431 138 277 + 0;
  • 431 138 277 ÷ 2 = 215 569 138 + 1;
  • 215 569 138 ÷ 2 = 107 784 569 + 0;
  • 107 784 569 ÷ 2 = 53 892 284 + 1;
  • 53 892 284 ÷ 2 = 26 946 142 + 0;
  • 26 946 142 ÷ 2 = 13 473 071 + 0;
  • 13 473 071 ÷ 2 = 6 736 535 + 1;
  • 6 736 535 ÷ 2 = 3 368 267 + 1;
  • 3 368 267 ÷ 2 = 1 684 133 + 1;
  • 1 684 133 ÷ 2 = 842 066 + 1;
  • 842 066 ÷ 2 = 421 033 + 0;
  • 421 033 ÷ 2 = 210 516 + 1;
  • 210 516 ÷ 2 = 105 258 + 0;
  • 105 258 ÷ 2 = 52 629 + 0;
  • 52 629 ÷ 2 = 26 314 + 1;
  • 26 314 ÷ 2 = 13 157 + 0;
  • 13 157 ÷ 2 = 6 578 + 1;
  • 6 578 ÷ 2 = 3 289 + 0;
  • 3 289 ÷ 2 = 1 644 + 1;
  • 1 644 ÷ 2 = 822 + 0;
  • 822 ÷ 2 = 411 + 0;
  • 411 ÷ 2 = 205 + 1;
  • 205 ÷ 2 = 102 + 1;
  • 102 ÷ 2 = 51 + 0;
  • 51 ÷ 2 = 25 + 1;
  • 25 ÷ 2 = 12 + 1;
  • 12 ÷ 2 = 6 + 0;
  • 6 ÷ 2 = 3 + 0;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

2. Construct the base 2 representation of the positive number.

Take all the remainders starting from the bottom of the list constructed above.

115 732 799 999 999 323(10) =


1 1001 1011 0010 1010 0101 1110 0101 0000 1101 1100 0111 1101 0101 1011(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 56 positions to the left, so that only one non zero digit remains to the left of it:


115 732 799 999 999 323(10) =


1 1001 1011 0010 1010 0101 1110 0101 0000 1101 1100 0111 1101 0101 1011(2) =


1 1001 1011 0010 1010 0101 1110 0101 0000 1101 1100 0111 1101 0101 1011(2) × 20 =


1.1001 1011 0010 1010 0101 1110 0101 0000 1101 1100 0111 1101 0101 1011(2) × 256


4. Up to this moment, there are the following elements that would feed into the 32 bit single precision IEEE 754 binary floating point representation:

Sign 0 (a positive number)


Exponent (unadjusted): 56


Mantissa (not normalized):
1.1001 1011 0010 1010 0101 1110 0101 0000 1101 1100 0111 1101 0101 1011


5. Adjust the exponent.

Use the 8 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(8-1) - 1 =


56 + 2(8-1) - 1 =


(56 + 127)(10) =


183(10)


6. Convert the adjusted exponent from the decimal (base 10) to 8 bit binary.

Use the same technique of repeatedly dividing by 2:


  • division = quotient + remainder;
  • 183 ÷ 2 = 91 + 1;
  • 91 ÷ 2 = 45 + 1;
  • 45 ÷ 2 = 22 + 1;
  • 22 ÷ 2 = 11 + 0;
  • 11 ÷ 2 = 5 + 1;
  • 5 ÷ 2 = 2 + 1;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

7. Construct the base 2 representation of the adjusted exponent.

Take all the remainders starting from the bottom of the list constructed above.


Exponent (adjusted) =


183(10) =


1011 0111(2)


8. Normalize the mantissa.

a) Remove the leading (the leftmost) bit, since it's allways 1, and the decimal point, if the case.


b) Adjust its length to 23 bits, by removing the excess bits, from the right (if any of the excess bits is set on 1, we are losing precision...).


Mantissa (normalized) =


1. 100 1101 1001 0101 0010 1111 0 0101 0000 1101 1100 0111 1101 0101 1011 =


100 1101 1001 0101 0010 1111


9. The three elements that make up the number's 32 bit single precision IEEE 754 binary floating point representation:

Sign (1 bit) =
0 (a positive number)


Exponent (8 bits) =
1011 0111


Mantissa (23 bits) =
100 1101 1001 0101 0010 1111


Decimal number 115 732 799 999 999 323 converted to 32 bit single precision IEEE 754 binary floating point representation:

0 - 1011 0111 - 100 1101 1001 0101 0010 1111


How to convert decimal numbers from base ten to 32 bit single precision IEEE 754 binary floating point standard

Follow the steps below to convert a base 10 decimal number to 32 bit single precision IEEE 754 binary floating point:

  • 1. If the number to be converted is negative, start with its the positive version.
  • 2. First convert the integer part. Divide repeatedly by 2 the base ten positive representation of the integer number that is to be converted to binary, until we get a quotient that is equal to zero, keeping track of each remainder.
  • 3. Construct the base 2 representation of the positive integer part of the number, by taking all the remainders of the previous dividing operations, starting from the bottom of the list constructed above. Thus, the last remainder of the divisions becomes the first symbol (the leftmost) of the base two number, while the first remainder becomes the last symbol (the rightmost).
  • 4. Then convert the fractional part. Multiply the number repeatedly by 2, until we get a fractional part that is equal to zero, keeping track of each integer part of the results.
  • 5. Construct the base 2 representation of the fractional part of the number by taking all the integer parts of the previous multiplying operations, starting from the top of the constructed list above (they should appear in the binary representation, from left to right, in the order they have been calculated).
  • 6. Normalize the binary representation of the number, by shifting the decimal point (or if you prefer, the decimal mark) "n" positions either to the left or to the right, so that only one non zero digit remains to the left of the decimal point.
  • 7. Adjust the exponent in 8 bit excess/bias notation and then convert it from decimal (base 10) to 8 bit binary, by using the same technique of repeatedly dividing by 2, as shown above:
    Exponent (adjusted) = Exponent (unadjusted) + 2(8-1) - 1
  • 8. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal sign if the case) and adjust its length to 23 bits, either by removing the excess bits from the right (losing precision...) or by adding extra '0' bits to the right.
  • 9. Sign (it takes 1 bit) is either 1 for a negative or 0 for a positive number.

Example: convert the negative number -25.347 from decimal system (base ten) to 32 bit single precision IEEE 754 binary floating point:

  • 1. Start with the positive version of the number:

    |-25.347| = 25.347

  • 2. First convert the integer part, 25. Divide it repeatedly by 2, keeping track of each remainder, until we get a quotient that is equal to zero:
    • division = quotient + remainder;
    • 25 ÷ 2 = 12 + 1;
    • 12 ÷ 2 = 6 + 0;
    • 6 ÷ 2 = 3 + 0;
    • 3 ÷ 2 = 1 + 1;
    • 1 ÷ 2 = 0 + 1;
    • We have encountered a quotient that is ZERO => FULL STOP
  • 3. Construct the base 2 representation of the integer part of the number by taking all the remainders of the previous dividing operations, starting from the bottom of the list constructed above:

    25(10) = 1 1001(2)

  • 4. Then convert the fractional part, 0.347. Multiply repeatedly by 2, keeping track of each integer part of the results, until we get a fractional part that is equal to zero:
    • #) multiplying = integer + fractional part;
    • 1) 0.347 × 2 = 0 + 0.694;
    • 2) 0.694 × 2 = 1 + 0.388;
    • 3) 0.388 × 2 = 0 + 0.776;
    • 4) 0.776 × 2 = 1 + 0.552;
    • 5) 0.552 × 2 = 1 + 0.104;
    • 6) 0.104 × 2 = 0 + 0.208;
    • 7) 0.208 × 2 = 0 + 0.416;
    • 8) 0.416 × 2 = 0 + 0.832;
    • 9) 0.832 × 2 = 1 + 0.664;
    • 10) 0.664 × 2 = 1 + 0.328;
    • 11) 0.328 × 2 = 0 + 0.656;
    • 12) 0.656 × 2 = 1 + 0.312;
    • 13) 0.312 × 2 = 0 + 0.624;
    • 14) 0.624 × 2 = 1 + 0.248;
    • 15) 0.248 × 2 = 0 + 0.496;
    • 16) 0.496 × 2 = 0 + 0.992;
    • 17) 0.992 × 2 = 1 + 0.984;
    • 18) 0.984 × 2 = 1 + 0.968;
    • 19) 0.968 × 2 = 1 + 0.936;
    • 20) 0.936 × 2 = 1 + 0.872;
    • 21) 0.872 × 2 = 1 + 0.744;
    • 22) 0.744 × 2 = 1 + 0.488;
    • 23) 0.488 × 2 = 0 + 0.976;
    • 24) 0.976 × 2 = 1 + 0.952;
    • We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit = 23) and at least one integer part that was different from zero => FULL STOP (losing precision...).
  • 5. Construct the base 2 representation of the fractional part of the number, by taking all the integer parts of the previous multiplying operations, starting from the top of the constructed list above:

    0.347(10) = 0.0101 1000 1101 0100 1111 1101(2)

  • 6. Summarizing - the positive number before normalization:

    25.347(10) = 1 1001.0101 1000 1101 0100 1111 1101(2)

  • 7. Normalize the binary representation of the number, shifting the decimal point 4 positions to the left so that only one non-zero digit stays to the left of the decimal point:

    25.347(10) =
    1 1001.0101 1000 1101 0100 1111 1101(2) =
    1 1001.0101 1000 1101 0100 1111 1101(2) × 20 =
    1.1001 0101 1000 1101 0100 1111 1101(2) × 24

  • 8. Up to this moment, there are the following elements that would feed into the 32 bit single precision IEEE 754 binary floating point:

    Sign: 1 (a negative number)

    Exponent (unadjusted): 4

    Mantissa (not-normalized): 1.1001 0101 1000 1101 0100 1111 1101

  • 9. Adjust the exponent in 8 bit excess/bias notation and then convert it from decimal (base 10) to 8 bit binary (base 2), by using the same technique of repeatedly dividing it by 2, as already demonstrated above:

    Exponent (adjusted) = Exponent (unadjusted) + 2(8-1) - 1 = (4 + 127)(10) = 131(10) =
    1000 0011(2)

  • 10. Normalize the mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal point) and adjust its length to 23 bits, by removing the excess bits from the right (losing precision...):

    Mantissa (not-normalized): 1.1001 0101 1000 1101 0100 1111 1101

    Mantissa (normalized): 100 1010 1100 0110 1010 0111

  • Conclusion:

    Sign (1 bit) = 1 (a negative number)

    Exponent (8 bits) = 1000 0011

    Mantissa (23 bits) = 100 1010 1100 0110 1010 0111

  • Number -25.347, converted from the decimal system (base 10) to 32 bit single precision IEEE 754 binary floating point =
    1 - 1000 0011 - 100 1010 1100 0110 1010 0111