123 456 789 012 346 183 Converted to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 123 456 789 012 346 183(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
123 456 789 012 346 183(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;
  • 123 456 789 012 346 183 ÷ 2 = 61 728 394 506 173 091 + 1;
  • 61 728 394 506 173 091 ÷ 2 = 30 864 197 253 086 545 + 1;
  • 30 864 197 253 086 545 ÷ 2 = 15 432 098 626 543 272 + 1;
  • 15 432 098 626 543 272 ÷ 2 = 7 716 049 313 271 636 + 0;
  • 7 716 049 313 271 636 ÷ 2 = 3 858 024 656 635 818 + 0;
  • 3 858 024 656 635 818 ÷ 2 = 1 929 012 328 317 909 + 0;
  • 1 929 012 328 317 909 ÷ 2 = 964 506 164 158 954 + 1;
  • 964 506 164 158 954 ÷ 2 = 482 253 082 079 477 + 0;
  • 482 253 082 079 477 ÷ 2 = 241 126 541 039 738 + 1;
  • 241 126 541 039 738 ÷ 2 = 120 563 270 519 869 + 0;
  • 120 563 270 519 869 ÷ 2 = 60 281 635 259 934 + 1;
  • 60 281 635 259 934 ÷ 2 = 30 140 817 629 967 + 0;
  • 30 140 817 629 967 ÷ 2 = 15 070 408 814 983 + 1;
  • 15 070 408 814 983 ÷ 2 = 7 535 204 407 491 + 1;
  • 7 535 204 407 491 ÷ 2 = 3 767 602 203 745 + 1;
  • 3 767 602 203 745 ÷ 2 = 1 883 801 101 872 + 1;
  • 1 883 801 101 872 ÷ 2 = 941 900 550 936 + 0;
  • 941 900 550 936 ÷ 2 = 470 950 275 468 + 0;
  • 470 950 275 468 ÷ 2 = 235 475 137 734 + 0;
  • 235 475 137 734 ÷ 2 = 117 737 568 867 + 0;
  • 117 737 568 867 ÷ 2 = 58 868 784 433 + 1;
  • 58 868 784 433 ÷ 2 = 29 434 392 216 + 1;
  • 29 434 392 216 ÷ 2 = 14 717 196 108 + 0;
  • 14 717 196 108 ÷ 2 = 7 358 598 054 + 0;
  • 7 358 598 054 ÷ 2 = 3 679 299 027 + 0;
  • 3 679 299 027 ÷ 2 = 1 839 649 513 + 1;
  • 1 839 649 513 ÷ 2 = 919 824 756 + 1;
  • 919 824 756 ÷ 2 = 459 912 378 + 0;
  • 459 912 378 ÷ 2 = 229 956 189 + 0;
  • 229 956 189 ÷ 2 = 114 978 094 + 1;
  • 114 978 094 ÷ 2 = 57 489 047 + 0;
  • 57 489 047 ÷ 2 = 28 744 523 + 1;
  • 28 744 523 ÷ 2 = 14 372 261 + 1;
  • 14 372 261 ÷ 2 = 7 186 130 + 1;
  • 7 186 130 ÷ 2 = 3 593 065 + 0;
  • 3 593 065 ÷ 2 = 1 796 532 + 1;
  • 1 796 532 ÷ 2 = 898 266 + 0;
  • 898 266 ÷ 2 = 449 133 + 0;
  • 449 133 ÷ 2 = 224 566 + 1;
  • 224 566 ÷ 2 = 112 283 + 0;
  • 112 283 ÷ 2 = 56 141 + 1;
  • 56 141 ÷ 2 = 28 070 + 1;
  • 28 070 ÷ 2 = 14 035 + 0;
  • 14 035 ÷ 2 = 7 017 + 1;
  • 7 017 ÷ 2 = 3 508 + 1;
  • 3 508 ÷ 2 = 1 754 + 0;
  • 1 754 ÷ 2 = 877 + 0;
  • 877 ÷ 2 = 438 + 1;
  • 438 ÷ 2 = 219 + 0;
  • 219 ÷ 2 = 109 + 1;
  • 109 ÷ 2 = 54 + 1;
  • 54 ÷ 2 = 27 + 0;
  • 27 ÷ 2 = 13 + 1;
  • 13 ÷ 2 = 6 + 1;
  • 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.

123 456 789 012 346 183(10) =


1 1011 0110 1001 1011 0100 1011 1010 0110 0011 0000 1111 0101 0100 0111(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:


123 456 789 012 346 183(10) =


1 1011 0110 1001 1011 0100 1011 1010 0110 0011 0000 1111 0101 0100 0111(2) =


1 1011 0110 1001 1011 0100 1011 1010 0110 0011 0000 1111 0101 0100 0111(2) × 20 =


1.1011 0110 1001 1011 0100 1011 1010 0110 0011 0000 1111 0101 0100 0111(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):
1.1011 0110 1001 1011 0100 1011 1010 0110 0011 0000 1111 0101 0100 0111


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. 101 1011 0100 1101 1010 0101 1 1010 0110 0011 0000 1111 0101 0100 0111 =


101 1011 0100 1101 1010 0101


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) =
101 1011 0100 1101 1010 0101


Decimal number 123 456 789 012 346 183 converted to 32 bit single precision IEEE 754 binary floating point representation:

0 - 1011 0111 - 101 1011 0100 1101 1010 0101


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