24.777 777 777 777 777 777 85 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 24.777 777 777 777 777 777 85(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
24.777 777 777 777 777 777 85(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: 0.777 777 777 777 777 777 85.

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) 0.777 777 777 777 777 777 85 × 2 = 1 + 0.555 555 555 555 555 555 7;
  • 2) 0.555 555 555 555 555 555 7 × 2 = 1 + 0.111 111 111 111 111 111 4;
  • 3) 0.111 111 111 111 111 111 4 × 2 = 0 + 0.222 222 222 222 222 222 8;
  • 4) 0.222 222 222 222 222 222 8 × 2 = 0 + 0.444 444 444 444 444 445 6;
  • 5) 0.444 444 444 444 444 445 6 × 2 = 0 + 0.888 888 888 888 888 891 2;
  • 6) 0.888 888 888 888 888 891 2 × 2 = 1 + 0.777 777 777 777 777 782 4;
  • 7) 0.777 777 777 777 777 782 4 × 2 = 1 + 0.555 555 555 555 555 564 8;
  • 8) 0.555 555 555 555 555 564 8 × 2 = 1 + 0.111 111 111 111 111 129 6;
  • 9) 0.111 111 111 111 111 129 6 × 2 = 0 + 0.222 222 222 222 222 259 2;
  • 10) 0.222 222 222 222 222 259 2 × 2 = 0 + 0.444 444 444 444 444 518 4;
  • 11) 0.444 444 444 444 444 518 4 × 2 = 0 + 0.888 888 888 888 889 036 8;
  • 12) 0.888 888 888 888 889 036 8 × 2 = 1 + 0.777 777 777 777 778 073 6;
  • 13) 0.777 777 777 777 778 073 6 × 2 = 1 + 0.555 555 555 555 556 147 2;
  • 14) 0.555 555 555 555 556 147 2 × 2 = 1 + 0.111 111 111 111 112 294 4;
  • 15) 0.111 111 111 111 112 294 4 × 2 = 0 + 0.222 222 222 222 224 588 8;
  • 16) 0.222 222 222 222 224 588 8 × 2 = 0 + 0.444 444 444 444 449 177 6;
  • 17) 0.444 444 444 444 449 177 6 × 2 = 0 + 0.888 888 888 888 898 355 2;
  • 18) 0.888 888 888 888 898 355 2 × 2 = 1 + 0.777 777 777 777 796 710 4;
  • 19) 0.777 777 777 777 796 710 4 × 2 = 1 + 0.555 555 555 555 593 420 8;
  • 20) 0.555 555 555 555 593 420 8 × 2 = 1 + 0.111 111 111 111 186 841 6;
  • 21) 0.111 111 111 111 186 841 6 × 2 = 0 + 0.222 222 222 222 373 683 2;
  • 22) 0.222 222 222 222 373 683 2 × 2 = 0 + 0.444 444 444 444 747 366 4;
  • 23) 0.444 444 444 444 747 366 4 × 2 = 0 + 0.888 888 888 889 494 732 8;
  • 24) 0.888 888 888 889 494 732 8 × 2 = 1 + 0.777 777 777 778 989 465 6;
  • 25) 0.777 777 777 778 989 465 6 × 2 = 1 + 0.555 555 555 557 978 931 2;
  • 26) 0.555 555 555 557 978 931 2 × 2 = 1 + 0.111 111 111 115 957 862 4;
  • 27) 0.111 111 111 115 957 862 4 × 2 = 0 + 0.222 222 222 231 915 724 8;
  • 28) 0.222 222 222 231 915 724 8 × 2 = 0 + 0.444 444 444 463 831 449 6;
  • 29) 0.444 444 444 463 831 449 6 × 2 = 0 + 0.888 888 888 927 662 899 2;
  • 30) 0.888 888 888 927 662 899 2 × 2 = 1 + 0.777 777 777 855 325 798 4;
  • 31) 0.777 777 777 855 325 798 4 × 2 = 1 + 0.555 555 555 710 651 596 8;
  • 32) 0.555 555 555 710 651 596 8 × 2 = 1 + 0.111 111 111 421 303 193 6;
  • 33) 0.111 111 111 421 303 193 6 × 2 = 0 + 0.222 222 222 842 606 387 2;
  • 34) 0.222 222 222 842 606 387 2 × 2 = 0 + 0.444 444 445 685 212 774 4;
  • 35) 0.444 444 445 685 212 774 4 × 2 = 0 + 0.888 888 891 370 425 548 8;
  • 36) 0.888 888 891 370 425 548 8 × 2 = 1 + 0.777 777 782 740 851 097 6;
  • 37) 0.777 777 782 740 851 097 6 × 2 = 1 + 0.555 555 565 481 702 195 2;
  • 38) 0.555 555 565 481 702 195 2 × 2 = 1 + 0.111 111 130 963 404 390 4;
  • 39) 0.111 111 130 963 404 390 4 × 2 = 0 + 0.222 222 261 926 808 780 8;
  • 40) 0.222 222 261 926 808 780 8 × 2 = 0 + 0.444 444 523 853 617 561 6;
  • 41) 0.444 444 523 853 617 561 6 × 2 = 0 + 0.888 889 047 707 235 123 2;
  • 42) 0.888 889 047 707 235 123 2 × 2 = 1 + 0.777 778 095 414 470 246 4;
  • 43) 0.777 778 095 414 470 246 4 × 2 = 1 + 0.555 556 190 828 940 492 8;
  • 44) 0.555 556 190 828 940 492 8 × 2 = 1 + 0.111 112 381 657 880 985 6;
  • 45) 0.111 112 381 657 880 985 6 × 2 = 0 + 0.222 224 763 315 761 971 2;
  • 46) 0.222 224 763 315 761 971 2 × 2 = 0 + 0.444 449 526 631 523 942 4;
  • 47) 0.444 449 526 631 523 942 4 × 2 = 0 + 0.888 899 053 263 047 884 8;
  • 48) 0.888 899 053 263 047 884 8 × 2 = 1 + 0.777 798 106 526 095 769 6;
  • 49) 0.777 798 106 526 095 769 6 × 2 = 1 + 0.555 596 213 052 191 539 2;
  • 50) 0.555 596 213 052 191 539 2 × 2 = 1 + 0.111 192 426 104 383 078 4;
  • 51) 0.111 192 426 104 383 078 4 × 2 = 0 + 0.222 384 852 208 766 156 8;
  • 52) 0.222 384 852 208 766 156 8 × 2 = 0 + 0.444 769 704 417 532 313 6;
  • 53) 0.444 769 704 417 532 313 6 × 2 = 0 + 0.889 539 408 835 064 627 2;

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:


0.777 777 777 777 777 777 85(10) =


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

5. Positive number before normalization:

24.777 777 777 777 777 777 85(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:


24.777 777 777 777 777 777 85(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 24.777 777 777 777 777 777 85 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