10 000.555 555 555 555 572 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 10 000.555 555 555 555 572(10) to 64 bit double precision IEEE 754 binary floating point representation standard (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

What are the steps to convert decimal number
10 000.555 555 555 555 572(10) to 64 bit double precision IEEE 754 binary floating point representation (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

1. First, convert to binary (in base 2) the integer part: 10 000.
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;
  • 10 000 ÷ 2 = 5 000 + 0;
  • 5 000 ÷ 2 = 2 500 + 0;
  • 2 500 ÷ 2 = 1 250 + 0;
  • 1 250 ÷ 2 = 625 + 0;
  • 625 ÷ 2 = 312 + 1;
  • 312 ÷ 2 = 156 + 0;
  • 156 ÷ 2 = 78 + 0;
  • 78 ÷ 2 = 39 + 0;
  • 39 ÷ 2 = 19 + 1;
  • 19 ÷ 2 = 9 + 1;
  • 9 ÷ 2 = 4 + 1;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

2. Construct the base 2 representation of the integer part of the number.

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

10 000(10) =


10 0111 0001 0000(2)


3. Convert to binary (base 2) the fractional part: 0.555 555 555 555 572.

Multiply it repeatedly by 2.


Keep track of each integer part of the results.


Stop when we get a fractional part that is equal to zero.


  • #) multiplying = integer + fractional part;
  • 1) 0.555 555 555 555 572 × 2 = 1 + 0.111 111 111 111 144;
  • 2) 0.111 111 111 111 144 × 2 = 0 + 0.222 222 222 222 288;
  • 3) 0.222 222 222 222 288 × 2 = 0 + 0.444 444 444 444 576;
  • 4) 0.444 444 444 444 576 × 2 = 0 + 0.888 888 888 889 152;
  • 5) 0.888 888 888 889 152 × 2 = 1 + 0.777 777 777 778 304;
  • 6) 0.777 777 777 778 304 × 2 = 1 + 0.555 555 555 556 608;
  • 7) 0.555 555 555 556 608 × 2 = 1 + 0.111 111 111 113 216;
  • 8) 0.111 111 111 113 216 × 2 = 0 + 0.222 222 222 226 432;
  • 9) 0.222 222 222 226 432 × 2 = 0 + 0.444 444 444 452 864;
  • 10) 0.444 444 444 452 864 × 2 = 0 + 0.888 888 888 905 728;
  • 11) 0.888 888 888 905 728 × 2 = 1 + 0.777 777 777 811 456;
  • 12) 0.777 777 777 811 456 × 2 = 1 + 0.555 555 555 622 912;
  • 13) 0.555 555 555 622 912 × 2 = 1 + 0.111 111 111 245 824;
  • 14) 0.111 111 111 245 824 × 2 = 0 + 0.222 222 222 491 648;
  • 15) 0.222 222 222 491 648 × 2 = 0 + 0.444 444 444 983 296;
  • 16) 0.444 444 444 983 296 × 2 = 0 + 0.888 888 889 966 592;
  • 17) 0.888 888 889 966 592 × 2 = 1 + 0.777 777 779 933 184;
  • 18) 0.777 777 779 933 184 × 2 = 1 + 0.555 555 559 866 368;
  • 19) 0.555 555 559 866 368 × 2 = 1 + 0.111 111 119 732 736;
  • 20) 0.111 111 119 732 736 × 2 = 0 + 0.222 222 239 465 472;
  • 21) 0.222 222 239 465 472 × 2 = 0 + 0.444 444 478 930 944;
  • 22) 0.444 444 478 930 944 × 2 = 0 + 0.888 888 957 861 888;
  • 23) 0.888 888 957 861 888 × 2 = 1 + 0.777 777 915 723 776;
  • 24) 0.777 777 915 723 776 × 2 = 1 + 0.555 555 831 447 552;
  • 25) 0.555 555 831 447 552 × 2 = 1 + 0.111 111 662 895 104;
  • 26) 0.111 111 662 895 104 × 2 = 0 + 0.222 223 325 790 208;
  • 27) 0.222 223 325 790 208 × 2 = 0 + 0.444 446 651 580 416;
  • 28) 0.444 446 651 580 416 × 2 = 0 + 0.888 893 303 160 832;
  • 29) 0.888 893 303 160 832 × 2 = 1 + 0.777 786 606 321 664;
  • 30) 0.777 786 606 321 664 × 2 = 1 + 0.555 573 212 643 328;
  • 31) 0.555 573 212 643 328 × 2 = 1 + 0.111 146 425 286 656;
  • 32) 0.111 146 425 286 656 × 2 = 0 + 0.222 292 850 573 312;
  • 33) 0.222 292 850 573 312 × 2 = 0 + 0.444 585 701 146 624;
  • 34) 0.444 585 701 146 624 × 2 = 0 + 0.889 171 402 293 248;
  • 35) 0.889 171 402 293 248 × 2 = 1 + 0.778 342 804 586 496;
  • 36) 0.778 342 804 586 496 × 2 = 1 + 0.556 685 609 172 992;
  • 37) 0.556 685 609 172 992 × 2 = 1 + 0.113 371 218 345 984;
  • 38) 0.113 371 218 345 984 × 2 = 0 + 0.226 742 436 691 968;
  • 39) 0.226 742 436 691 968 × 2 = 0 + 0.453 484 873 383 936;
  • 40) 0.453 484 873 383 936 × 2 = 0 + 0.906 969 746 767 872;
  • 41) 0.906 969 746 767 872 × 2 = 1 + 0.813 939 493 535 744;
  • 42) 0.813 939 493 535 744 × 2 = 1 + 0.627 878 987 071 488;
  • 43) 0.627 878 987 071 488 × 2 = 1 + 0.255 757 974 142 976;
  • 44) 0.255 757 974 142 976 × 2 = 0 + 0.511 515 948 285 952;
  • 45) 0.511 515 948 285 952 × 2 = 1 + 0.023 031 896 571 904;
  • 46) 0.023 031 896 571 904 × 2 = 0 + 0.046 063 793 143 808;
  • 47) 0.046 063 793 143 808 × 2 = 0 + 0.092 127 586 287 616;
  • 48) 0.092 127 586 287 616 × 2 = 0 + 0.184 255 172 575 232;
  • 49) 0.184 255 172 575 232 × 2 = 0 + 0.368 510 345 150 464;
  • 50) 0.368 510 345 150 464 × 2 = 0 + 0.737 020 690 300 928;
  • 51) 0.737 020 690 300 928 × 2 = 1 + 0.474 041 380 601 856;
  • 52) 0.474 041 380 601 856 × 2 = 0 + 0.948 082 761 203 712;
  • 53) 0.948 082 761 203 712 × 2 = 1 + 0.896 165 522 407 424;

We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit) and at least one integer that was different from zero => FULL STOP (Losing precision - the converted number we get in the end will be just a very good approximation of the initial one).


4. Construct the base 2 representation of the fractional part of the number.

Take all the integer parts of the multiplying operations, starting from the top of the constructed list above:


0.555 555 555 555 572(10) =


0.1000 1110 0011 1000 1110 0011 1000 1110 0011 1000 1110 1000 0010 1(2)

5. Positive number before normalization:

10 000.555 555 555 555 572(10) =


10 0111 0001 0000.1000 1110 0011 1000 1110 0011 1000 1110 0011 1000 1110 1000 0010 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 13 positions to the left, so that only one non zero digit remains to the left of it:


10 000.555 555 555 555 572(10) =


10 0111 0001 0000.1000 1110 0011 1000 1110 0011 1000 1110 0011 1000 1110 1000 0010 1(2) =


10 0111 0001 0000.1000 1110 0011 1000 1110 0011 1000 1110 0011 1000 1110 1000 0010 1(2) × 20 =


1.0011 1000 1000 0100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0100 0001 01(2) × 213


7. Up to this moment, there are the following elements that would feed into the 64 bit double precision IEEE 754 binary floating point representation:

Sign 0 (a positive number)


Exponent (unadjusted): 13


Mantissa (not normalized):
1.0011 1000 1000 0100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0100 0001 01


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(11-1) - 1 =


13 + 2(11-1) - 1 =


(13 + 1 023)(10) =


1 036(10)


9. Convert the adjusted exponent from the decimal (base 10) to 11 bit binary.

Use the same technique of repeatedly dividing by 2:


  • division = quotient + remainder;
  • 1 036 ÷ 2 = 518 + 0;
  • 518 ÷ 2 = 259 + 0;
  • 259 ÷ 2 = 129 + 1;
  • 129 ÷ 2 = 64 + 1;
  • 64 ÷ 2 = 32 + 0;
  • 32 ÷ 2 = 16 + 0;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

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

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


Exponent (adjusted) =


1036(10) =


100 0000 1100(2)


11. 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 52 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. 0011 1000 1000 0100 0111 0001 1100 0111 0001 1100 0111 0001 1100 01 1101 0000 0101 =


0011 1000 1000 0100 0111 0001 1100 0111 0001 1100 0111 0001 1100


12. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

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


Exponent (11 bits) =
100 0000 1100


Mantissa (52 bits) =
0011 1000 1000 0100 0111 0001 1100 0111 0001 1100 0111 0001 1100


Decimal number 10 000.555 555 555 555 572 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 1100 - 0011 1000 1000 0100 0111 0001 1100 0111 0001 1100 0111 0001 1100


How to convert numbers from the decimal system (base ten) to 64 bit double precision IEEE 754 binary floating point standard

Follow the steps below to convert a base 10 decimal number to 64 bit double 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 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 from the previous 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 multiplying operations, starting from the top of the list constructed 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, shifting the decimal mark (the decimal point) "n" positions either to the left, or to the right, so that only one non zero digit remains to the left of the decimal mark.
  • 7. Adjust the exponent in 11 bit excess/bias notation and then convert it from decimal (base 10) to 11 bit binary, by using the same technique of repeatedly dividing by 2, as shown above:
    Exponent (adjusted) = Exponent (unadjusted) + 2(11-1) - 1
  • 8. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal mark, if the case) and adjust its length to 52 bits, either by removing the excess bits from the right (losing precision...) or by adding extra bits set on '0' 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 -31.640 215 from the decimal system (base ten) to 64 bit double precision IEEE 754 binary floating point:

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

    |-31.640 215| = 31.640 215

  • 2. First convert the integer part, 31. Divide it repeatedly by 2, keeping track of each remainder, until we get a quotient that is equal to zero:
    • division = quotient + remainder;
    • 31 ÷ 2 = 15 + 1;
    • 15 ÷ 2 = 7 + 1;
    • 7 ÷ 2 = 3 + 1;
    • 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:

    31(10) = 1 1111(2)

  • 4. Then, convert the fractional part, 0.640 215. 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) 0.640 215 × 2 = 1 + 0.280 43;
    • 2) 0.280 43 × 2 = 0 + 0.560 86;
    • 3) 0.560 86 × 2 = 1 + 0.121 72;
    • 4) 0.121 72 × 2 = 0 + 0.243 44;
    • 5) 0.243 44 × 2 = 0 + 0.486 88;
    • 6) 0.486 88 × 2 = 0 + 0.973 76;
    • 7) 0.973 76 × 2 = 1 + 0.947 52;
    • 8) 0.947 52 × 2 = 1 + 0.895 04;
    • 9) 0.895 04 × 2 = 1 + 0.790 08;
    • 10) 0.790 08 × 2 = 1 + 0.580 16;
    • 11) 0.580 16 × 2 = 1 + 0.160 32;
    • 12) 0.160 32 × 2 = 0 + 0.320 64;
    • 13) 0.320 64 × 2 = 0 + 0.641 28;
    • 14) 0.641 28 × 2 = 1 + 0.282 56;
    • 15) 0.282 56 × 2 = 0 + 0.565 12;
    • 16) 0.565 12 × 2 = 1 + 0.130 24;
    • 17) 0.130 24 × 2 = 0 + 0.260 48;
    • 18) 0.260 48 × 2 = 0 + 0.520 96;
    • 19) 0.520 96 × 2 = 1 + 0.041 92;
    • 20) 0.041 92 × 2 = 0 + 0.083 84;
    • 21) 0.083 84 × 2 = 0 + 0.167 68;
    • 22) 0.167 68 × 2 = 0 + 0.335 36;
    • 23) 0.335 36 × 2 = 0 + 0.670 72;
    • 24) 0.670 72 × 2 = 1 + 0.341 44;
    • 25) 0.341 44 × 2 = 0 + 0.682 88;
    • 26) 0.682 88 × 2 = 1 + 0.365 76;
    • 27) 0.365 76 × 2 = 0 + 0.731 52;
    • 28) 0.731 52 × 2 = 1 + 0.463 04;
    • 29) 0.463 04 × 2 = 0 + 0.926 08;
    • 30) 0.926 08 × 2 = 1 + 0.852 16;
    • 31) 0.852 16 × 2 = 1 + 0.704 32;
    • 32) 0.704 32 × 2 = 1 + 0.408 64;
    • 33) 0.408 64 × 2 = 0 + 0.817 28;
    • 34) 0.817 28 × 2 = 1 + 0.634 56;
    • 35) 0.634 56 × 2 = 1 + 0.269 12;
    • 36) 0.269 12 × 2 = 0 + 0.538 24;
    • 37) 0.538 24 × 2 = 1 + 0.076 48;
    • 38) 0.076 48 × 2 = 0 + 0.152 96;
    • 39) 0.152 96 × 2 = 0 + 0.305 92;
    • 40) 0.305 92 × 2 = 0 + 0.611 84;
    • 41) 0.611 84 × 2 = 1 + 0.223 68;
    • 42) 0.223 68 × 2 = 0 + 0.447 36;
    • 43) 0.447 36 × 2 = 0 + 0.894 72;
    • 44) 0.894 72 × 2 = 1 + 0.789 44;
    • 45) 0.789 44 × 2 = 1 + 0.578 88;
    • 46) 0.578 88 × 2 = 1 + 0.157 76;
    • 47) 0.157 76 × 2 = 0 + 0.315 52;
    • 48) 0.315 52 × 2 = 0 + 0.631 04;
    • 49) 0.631 04 × 2 = 1 + 0.262 08;
    • 50) 0.262 08 × 2 = 0 + 0.524 16;
    • 51) 0.524 16 × 2 = 1 + 0.048 32;
    • 52) 0.048 32 × 2 = 0 + 0.096 64;
    • 53) 0.096 64 × 2 = 0 + 0.193 28;
    • We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit = 52) 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:

    0.640 215(10) = 0.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2)

  • 6. Summarizing - the positive number before normalization:

    31.640 215(10) = 1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2)

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

    31.640 215(10) =
    1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) =
    1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) × 20 =
    1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) × 24

  • 8. Up to this moment, there are the following elements that would feed into the 64 bit double precision IEEE 754 binary floating point representation:

    Sign: 1 (a negative number)

    Exponent (unadjusted): 4

    Mantissa (not-normalized): 1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0

  • 9. Adjust the exponent in 11 bit excess/bias notation and then convert it from decimal (base 10) to 11 bit binary (base 2), by using the same technique of repeatedly dividing it by 2, as shown above:

    Exponent (adjusted) = Exponent (unadjusted) + 2(11-1) - 1 = (4 + 1023)(10) = 1027(10) =
    100 0000 0011(2)

  • 10. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal sign) and adjust its length to 52 bits, by removing the excess bits, from the right (losing precision...):

    Mantissa (not-normalized): 1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0

    Mantissa (normalized): 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100

  • Conclusion:

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

    Exponent (8 bits) = 100 0000 0011

    Mantissa (52 bits) = 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100

  • Number -31.640 215, converted from decimal system (base 10) to 64 bit double precision IEEE 754 binary floating point =
    1 - 100 0000 0011 - 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100