1 132 836 543 271 501 435 Converted to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 1 132 836 543 271 501 435(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
1 132 836 543 271 501 435(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;
  • 1 132 836 543 271 501 435 ÷ 2 = 566 418 271 635 750 717 + 1;
  • 566 418 271 635 750 717 ÷ 2 = 283 209 135 817 875 358 + 1;
  • 283 209 135 817 875 358 ÷ 2 = 141 604 567 908 937 679 + 0;
  • 141 604 567 908 937 679 ÷ 2 = 70 802 283 954 468 839 + 1;
  • 70 802 283 954 468 839 ÷ 2 = 35 401 141 977 234 419 + 1;
  • 35 401 141 977 234 419 ÷ 2 = 17 700 570 988 617 209 + 1;
  • 17 700 570 988 617 209 ÷ 2 = 8 850 285 494 308 604 + 1;
  • 8 850 285 494 308 604 ÷ 2 = 4 425 142 747 154 302 + 0;
  • 4 425 142 747 154 302 ÷ 2 = 2 212 571 373 577 151 + 0;
  • 2 212 571 373 577 151 ÷ 2 = 1 106 285 686 788 575 + 1;
  • 1 106 285 686 788 575 ÷ 2 = 553 142 843 394 287 + 1;
  • 553 142 843 394 287 ÷ 2 = 276 571 421 697 143 + 1;
  • 276 571 421 697 143 ÷ 2 = 138 285 710 848 571 + 1;
  • 138 285 710 848 571 ÷ 2 = 69 142 855 424 285 + 1;
  • 69 142 855 424 285 ÷ 2 = 34 571 427 712 142 + 1;
  • 34 571 427 712 142 ÷ 2 = 17 285 713 856 071 + 0;
  • 17 285 713 856 071 ÷ 2 = 8 642 856 928 035 + 1;
  • 8 642 856 928 035 ÷ 2 = 4 321 428 464 017 + 1;
  • 4 321 428 464 017 ÷ 2 = 2 160 714 232 008 + 1;
  • 2 160 714 232 008 ÷ 2 = 1 080 357 116 004 + 0;
  • 1 080 357 116 004 ÷ 2 = 540 178 558 002 + 0;
  • 540 178 558 002 ÷ 2 = 270 089 279 001 + 0;
  • 270 089 279 001 ÷ 2 = 135 044 639 500 + 1;
  • 135 044 639 500 ÷ 2 = 67 522 319 750 + 0;
  • 67 522 319 750 ÷ 2 = 33 761 159 875 + 0;
  • 33 761 159 875 ÷ 2 = 16 880 579 937 + 1;
  • 16 880 579 937 ÷ 2 = 8 440 289 968 + 1;
  • 8 440 289 968 ÷ 2 = 4 220 144 984 + 0;
  • 4 220 144 984 ÷ 2 = 2 110 072 492 + 0;
  • 2 110 072 492 ÷ 2 = 1 055 036 246 + 0;
  • 1 055 036 246 ÷ 2 = 527 518 123 + 0;
  • 527 518 123 ÷ 2 = 263 759 061 + 1;
  • 263 759 061 ÷ 2 = 131 879 530 + 1;
  • 131 879 530 ÷ 2 = 65 939 765 + 0;
  • 65 939 765 ÷ 2 = 32 969 882 + 1;
  • 32 969 882 ÷ 2 = 16 484 941 + 0;
  • 16 484 941 ÷ 2 = 8 242 470 + 1;
  • 8 242 470 ÷ 2 = 4 121 235 + 0;
  • 4 121 235 ÷ 2 = 2 060 617 + 1;
  • 2 060 617 ÷ 2 = 1 030 308 + 1;
  • 1 030 308 ÷ 2 = 515 154 + 0;
  • 515 154 ÷ 2 = 257 577 + 0;
  • 257 577 ÷ 2 = 128 788 + 1;
  • 128 788 ÷ 2 = 64 394 + 0;
  • 64 394 ÷ 2 = 32 197 + 0;
  • 32 197 ÷ 2 = 16 098 + 1;
  • 16 098 ÷ 2 = 8 049 + 0;
  • 8 049 ÷ 2 = 4 024 + 1;
  • 4 024 ÷ 2 = 2 012 + 0;
  • 2 012 ÷ 2 = 1 006 + 0;
  • 1 006 ÷ 2 = 503 + 0;
  • 503 ÷ 2 = 251 + 1;
  • 251 ÷ 2 = 125 + 1;
  • 125 ÷ 2 = 62 + 1;
  • 62 ÷ 2 = 31 + 0;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 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.

1 132 836 543 271 501 435(10) =


1111 1011 1000 1010 0100 1101 0101 1000 0110 0100 0111 0111 1110 0111 1011(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 59 positions to the left, so that only one non zero digit remains to the left of it:


1 132 836 543 271 501 435(10) =


1111 1011 1000 1010 0100 1101 0101 1000 0110 0100 0111 0111 1110 0111 1011(2) =


1111 1011 1000 1010 0100 1101 0101 1000 0110 0100 0111 0111 1110 0111 1011(2) × 20 =


1.1111 0111 0001 0100 1001 1010 1011 0000 1100 1000 1110 1111 1100 1111 011(2) × 259


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): 59


Mantissa (not normalized):
1.1111 0111 0001 0100 1001 1010 1011 0000 1100 1000 1110 1111 1100 1111 011


5. Adjust the exponent.

Use the 8 bit excess/bias notation:


Exponent (adjusted) =


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


59 + 2(8-1) - 1 =


(59 + 127)(10) =


186(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;
  • 186 ÷ 2 = 93 + 0;
  • 93 ÷ 2 = 46 + 1;
  • 46 ÷ 2 = 23 + 0;
  • 23 ÷ 2 = 11 + 1;
  • 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) =


186(10) =


1011 1010(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. 111 1011 1000 1010 0100 1101 0101 1000 0110 0100 0111 0111 1110 0111 1011 =


111 1011 1000 1010 0100 1101


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 1010


Mantissa (23 bits) =
111 1011 1000 1010 0100 1101


Decimal number 1 132 836 543 271 501 435 converted to 32 bit single precision IEEE 754 binary floating point representation:

0 - 1011 1010 - 111 1011 1000 1010 0100 1101


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