24.777 777 777 777 769 8 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 24.777 777 777 777 769 8(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
24.777 777 777 777 769 8(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: 24.
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;
  • 24 ÷ 2 = 12 + 0;
  • 12 ÷ 2 = 6 + 0;
  • 6 ÷ 2 = 3 + 0;
  • 3 ÷ 2 = 1 + 1;
  • 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.

24(10) =


1 1000(2)


3. Convert to binary (base 2) the fractional part: 0.777 777 777 777 769 8.

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) 0.777 777 777 777 769 8 × 2 = 1 + 0.555 555 555 555 539 6;
  • 2) 0.555 555 555 555 539 6 × 2 = 1 + 0.111 111 111 111 079 2;
  • 3) 0.111 111 111 111 079 2 × 2 = 0 + 0.222 222 222 222 158 4;
  • 4) 0.222 222 222 222 158 4 × 2 = 0 + 0.444 444 444 444 316 8;
  • 5) 0.444 444 444 444 316 8 × 2 = 0 + 0.888 888 888 888 633 6;
  • 6) 0.888 888 888 888 633 6 × 2 = 1 + 0.777 777 777 777 267 2;
  • 7) 0.777 777 777 777 267 2 × 2 = 1 + 0.555 555 555 554 534 4;
  • 8) 0.555 555 555 554 534 4 × 2 = 1 + 0.111 111 111 109 068 8;
  • 9) 0.111 111 111 109 068 8 × 2 = 0 + 0.222 222 222 218 137 6;
  • 10) 0.222 222 222 218 137 6 × 2 = 0 + 0.444 444 444 436 275 2;
  • 11) 0.444 444 444 436 275 2 × 2 = 0 + 0.888 888 888 872 550 4;
  • 12) 0.888 888 888 872 550 4 × 2 = 1 + 0.777 777 777 745 100 8;
  • 13) 0.777 777 777 745 100 8 × 2 = 1 + 0.555 555 555 490 201 6;
  • 14) 0.555 555 555 490 201 6 × 2 = 1 + 0.111 111 110 980 403 2;
  • 15) 0.111 111 110 980 403 2 × 2 = 0 + 0.222 222 221 960 806 4;
  • 16) 0.222 222 221 960 806 4 × 2 = 0 + 0.444 444 443 921 612 8;
  • 17) 0.444 444 443 921 612 8 × 2 = 0 + 0.888 888 887 843 225 6;
  • 18) 0.888 888 887 843 225 6 × 2 = 1 + 0.777 777 775 686 451 2;
  • 19) 0.777 777 775 686 451 2 × 2 = 1 + 0.555 555 551 372 902 4;
  • 20) 0.555 555 551 372 902 4 × 2 = 1 + 0.111 111 102 745 804 8;
  • 21) 0.111 111 102 745 804 8 × 2 = 0 + 0.222 222 205 491 609 6;
  • 22) 0.222 222 205 491 609 6 × 2 = 0 + 0.444 444 410 983 219 2;
  • 23) 0.444 444 410 983 219 2 × 2 = 0 + 0.888 888 821 966 438 4;
  • 24) 0.888 888 821 966 438 4 × 2 = 1 + 0.777 777 643 932 876 8;
  • 25) 0.777 777 643 932 876 8 × 2 = 1 + 0.555 555 287 865 753 6;
  • 26) 0.555 555 287 865 753 6 × 2 = 1 + 0.111 110 575 731 507 2;
  • 27) 0.111 110 575 731 507 2 × 2 = 0 + 0.222 221 151 463 014 4;
  • 28) 0.222 221 151 463 014 4 × 2 = 0 + 0.444 442 302 926 028 8;
  • 29) 0.444 442 302 926 028 8 × 2 = 0 + 0.888 884 605 852 057 6;
  • 30) 0.888 884 605 852 057 6 × 2 = 1 + 0.777 769 211 704 115 2;
  • 31) 0.777 769 211 704 115 2 × 2 = 1 + 0.555 538 423 408 230 4;
  • 32) 0.555 538 423 408 230 4 × 2 = 1 + 0.111 076 846 816 460 8;
  • 33) 0.111 076 846 816 460 8 × 2 = 0 + 0.222 153 693 632 921 6;
  • 34) 0.222 153 693 632 921 6 × 2 = 0 + 0.444 307 387 265 843 2;
  • 35) 0.444 307 387 265 843 2 × 2 = 0 + 0.888 614 774 531 686 4;
  • 36) 0.888 614 774 531 686 4 × 2 = 1 + 0.777 229 549 063 372 8;
  • 37) 0.777 229 549 063 372 8 × 2 = 1 + 0.554 459 098 126 745 6;
  • 38) 0.554 459 098 126 745 6 × 2 = 1 + 0.108 918 196 253 491 2;
  • 39) 0.108 918 196 253 491 2 × 2 = 0 + 0.217 836 392 506 982 4;
  • 40) 0.217 836 392 506 982 4 × 2 = 0 + 0.435 672 785 013 964 8;
  • 41) 0.435 672 785 013 964 8 × 2 = 0 + 0.871 345 570 027 929 6;
  • 42) 0.871 345 570 027 929 6 × 2 = 1 + 0.742 691 140 055 859 2;
  • 43) 0.742 691 140 055 859 2 × 2 = 1 + 0.485 382 280 111 718 4;
  • 44) 0.485 382 280 111 718 4 × 2 = 0 + 0.970 764 560 223 436 8;
  • 45) 0.970 764 560 223 436 8 × 2 = 1 + 0.941 529 120 446 873 6;
  • 46) 0.941 529 120 446 873 6 × 2 = 1 + 0.883 058 240 893 747 2;
  • 47) 0.883 058 240 893 747 2 × 2 = 1 + 0.766 116 481 787 494 4;
  • 48) 0.766 116 481 787 494 4 × 2 = 1 + 0.532 232 963 574 988 8;
  • 49) 0.532 232 963 574 988 8 × 2 = 1 + 0.064 465 927 149 977 6;
  • 50) 0.064 465 927 149 977 6 × 2 = 0 + 0.128 931 854 299 955 2;
  • 51) 0.128 931 854 299 955 2 × 2 = 0 + 0.257 863 708 599 910 4;
  • 52) 0.257 863 708 599 910 4 × 2 = 0 + 0.515 727 417 199 820 8;
  • 53) 0.515 727 417 199 820 8 × 2 = 1 + 0.031 454 834 399 641 6;

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:


0.777 777 777 777 769 8(10) =


0.1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0110 1111 1000 1(2)

5. Positive number before normalization:

24.777 777 777 777 769 8(10) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0110 1111 1000 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 4 positions to the left, so that only one non zero digit remains to the left of it:


24.777 777 777 777 769 8(10) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0110 1111 1000 1(2) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0110 1111 1000 1(2) × 20 =


1.1000 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0110 1111 1000 1(2) × 24


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): 4


Mantissa (not normalized):
1.1000 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0110 1111 1000 1


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


4 + 2(11-1) - 1 =


(4 + 1 023)(10) =


1 027(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;
  • 1 027 ÷ 2 = 513 + 1;
  • 513 ÷ 2 = 256 + 1;
  • 256 ÷ 2 = 128 + 0;
  • 128 ÷ 2 = 64 + 0;
  • 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) =


1027(10) =


100 0000 0011(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. 1000 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0110 1111 1 0001 =


1000 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0110 1111


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 0011


Mantissa (52 bits) =
1000 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0110 1111


Decimal number 24.777 777 777 777 769 8 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0011 - 1000 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0110 1111


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