24.777 777 777 777 777 775 2 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 24.777 777 777 777 777 775 2(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
24.777 777 777 777 777 775 2(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: 0.777 777 777 777 777 775 2.

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) 0.777 777 777 777 777 775 2 × 2 = 1 + 0.555 555 555 555 555 550 4;
  • 2) 0.555 555 555 555 555 550 4 × 2 = 1 + 0.111 111 111 111 111 100 8;
  • 3) 0.111 111 111 111 111 100 8 × 2 = 0 + 0.222 222 222 222 222 201 6;
  • 4) 0.222 222 222 222 222 201 6 × 2 = 0 + 0.444 444 444 444 444 403 2;
  • 5) 0.444 444 444 444 444 403 2 × 2 = 0 + 0.888 888 888 888 888 806 4;
  • 6) 0.888 888 888 888 888 806 4 × 2 = 1 + 0.777 777 777 777 777 612 8;
  • 7) 0.777 777 777 777 777 612 8 × 2 = 1 + 0.555 555 555 555 555 225 6;
  • 8) 0.555 555 555 555 555 225 6 × 2 = 1 + 0.111 111 111 111 110 451 2;
  • 9) 0.111 111 111 111 110 451 2 × 2 = 0 + 0.222 222 222 222 220 902 4;
  • 10) 0.222 222 222 222 220 902 4 × 2 = 0 + 0.444 444 444 444 441 804 8;
  • 11) 0.444 444 444 444 441 804 8 × 2 = 0 + 0.888 888 888 888 883 609 6;
  • 12) 0.888 888 888 888 883 609 6 × 2 = 1 + 0.777 777 777 777 767 219 2;
  • 13) 0.777 777 777 777 767 219 2 × 2 = 1 + 0.555 555 555 555 534 438 4;
  • 14) 0.555 555 555 555 534 438 4 × 2 = 1 + 0.111 111 111 111 068 876 8;
  • 15) 0.111 111 111 111 068 876 8 × 2 = 0 + 0.222 222 222 222 137 753 6;
  • 16) 0.222 222 222 222 137 753 6 × 2 = 0 + 0.444 444 444 444 275 507 2;
  • 17) 0.444 444 444 444 275 507 2 × 2 = 0 + 0.888 888 888 888 551 014 4;
  • 18) 0.888 888 888 888 551 014 4 × 2 = 1 + 0.777 777 777 777 102 028 8;
  • 19) 0.777 777 777 777 102 028 8 × 2 = 1 + 0.555 555 555 554 204 057 6;
  • 20) 0.555 555 555 554 204 057 6 × 2 = 1 + 0.111 111 111 108 408 115 2;
  • 21) 0.111 111 111 108 408 115 2 × 2 = 0 + 0.222 222 222 216 816 230 4;
  • 22) 0.222 222 222 216 816 230 4 × 2 = 0 + 0.444 444 444 433 632 460 8;
  • 23) 0.444 444 444 433 632 460 8 × 2 = 0 + 0.888 888 888 867 264 921 6;
  • 24) 0.888 888 888 867 264 921 6 × 2 = 1 + 0.777 777 777 734 529 843 2;
  • 25) 0.777 777 777 734 529 843 2 × 2 = 1 + 0.555 555 555 469 059 686 4;
  • 26) 0.555 555 555 469 059 686 4 × 2 = 1 + 0.111 111 110 938 119 372 8;
  • 27) 0.111 111 110 938 119 372 8 × 2 = 0 + 0.222 222 221 876 238 745 6;
  • 28) 0.222 222 221 876 238 745 6 × 2 = 0 + 0.444 444 443 752 477 491 2;
  • 29) 0.444 444 443 752 477 491 2 × 2 = 0 + 0.888 888 887 504 954 982 4;
  • 30) 0.888 888 887 504 954 982 4 × 2 = 1 + 0.777 777 775 009 909 964 8;
  • 31) 0.777 777 775 009 909 964 8 × 2 = 1 + 0.555 555 550 019 819 929 6;
  • 32) 0.555 555 550 019 819 929 6 × 2 = 1 + 0.111 111 100 039 639 859 2;
  • 33) 0.111 111 100 039 639 859 2 × 2 = 0 + 0.222 222 200 079 279 718 4;
  • 34) 0.222 222 200 079 279 718 4 × 2 = 0 + 0.444 444 400 158 559 436 8;
  • 35) 0.444 444 400 158 559 436 8 × 2 = 0 + 0.888 888 800 317 118 873 6;
  • 36) 0.888 888 800 317 118 873 6 × 2 = 1 + 0.777 777 600 634 237 747 2;
  • 37) 0.777 777 600 634 237 747 2 × 2 = 1 + 0.555 555 201 268 475 494 4;
  • 38) 0.555 555 201 268 475 494 4 × 2 = 1 + 0.111 110 402 536 950 988 8;
  • 39) 0.111 110 402 536 950 988 8 × 2 = 0 + 0.222 220 805 073 901 977 6;
  • 40) 0.222 220 805 073 901 977 6 × 2 = 0 + 0.444 441 610 147 803 955 2;
  • 41) 0.444 441 610 147 803 955 2 × 2 = 0 + 0.888 883 220 295 607 910 4;
  • 42) 0.888 883 220 295 607 910 4 × 2 = 1 + 0.777 766 440 591 215 820 8;
  • 43) 0.777 766 440 591 215 820 8 × 2 = 1 + 0.555 532 881 182 431 641 6;
  • 44) 0.555 532 881 182 431 641 6 × 2 = 1 + 0.111 065 762 364 863 283 2;
  • 45) 0.111 065 762 364 863 283 2 × 2 = 0 + 0.222 131 524 729 726 566 4;
  • 46) 0.222 131 524 729 726 566 4 × 2 = 0 + 0.444 263 049 459 453 132 8;
  • 47) 0.444 263 049 459 453 132 8 × 2 = 0 + 0.888 526 098 918 906 265 6;
  • 48) 0.888 526 098 918 906 265 6 × 2 = 1 + 0.777 052 197 837 812 531 2;
  • 49) 0.777 052 197 837 812 531 2 × 2 = 1 + 0.554 104 395 675 625 062 4;
  • 50) 0.554 104 395 675 625 062 4 × 2 = 1 + 0.108 208 791 351 250 124 8;
  • 51) 0.108 208 791 351 250 124 8 × 2 = 0 + 0.216 417 582 702 500 249 6;
  • 52) 0.216 417 582 702 500 249 6 × 2 = 0 + 0.432 835 165 405 000 499 2;
  • 53) 0.432 835 165 405 000 499 2 × 2 = 0 + 0.865 670 330 810 000 998 4;

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:


0.777 777 777 777 777 775 2(10) =


0.1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0(2)

5. Positive number before normalization:

24.777 777 777 777 777 775 2(10) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0(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:


24.777 777 777 777 777 775 2(10) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0(2) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0(2) × 20 =


1.1000 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0(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 0111 0001 1100 0


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 0111 0001 1 1000 =


1000 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0001


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 0111 0001


Decimal number 24.777 777 777 777 777 775 2 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 0111 0001


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