24.777 777 777 780 1 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 24.777 777 777 780 1(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
24.777 777 777 780 1(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: 0.777 777 777 780 1.

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) 0.777 777 777 780 1 × 2 = 1 + 0.555 555 555 560 2;
  • 2) 0.555 555 555 560 2 × 2 = 1 + 0.111 111 111 120 4;
  • 3) 0.111 111 111 120 4 × 2 = 0 + 0.222 222 222 240 8;
  • 4) 0.222 222 222 240 8 × 2 = 0 + 0.444 444 444 481 6;
  • 5) 0.444 444 444 481 6 × 2 = 0 + 0.888 888 888 963 2;
  • 6) 0.888 888 888 963 2 × 2 = 1 + 0.777 777 777 926 4;
  • 7) 0.777 777 777 926 4 × 2 = 1 + 0.555 555 555 852 8;
  • 8) 0.555 555 555 852 8 × 2 = 1 + 0.111 111 111 705 6;
  • 9) 0.111 111 111 705 6 × 2 = 0 + 0.222 222 223 411 2;
  • 10) 0.222 222 223 411 2 × 2 = 0 + 0.444 444 446 822 4;
  • 11) 0.444 444 446 822 4 × 2 = 0 + 0.888 888 893 644 8;
  • 12) 0.888 888 893 644 8 × 2 = 1 + 0.777 777 787 289 6;
  • 13) 0.777 777 787 289 6 × 2 = 1 + 0.555 555 574 579 2;
  • 14) 0.555 555 574 579 2 × 2 = 1 + 0.111 111 149 158 4;
  • 15) 0.111 111 149 158 4 × 2 = 0 + 0.222 222 298 316 8;
  • 16) 0.222 222 298 316 8 × 2 = 0 + 0.444 444 596 633 6;
  • 17) 0.444 444 596 633 6 × 2 = 0 + 0.888 889 193 267 2;
  • 18) 0.888 889 193 267 2 × 2 = 1 + 0.777 778 386 534 4;
  • 19) 0.777 778 386 534 4 × 2 = 1 + 0.555 556 773 068 8;
  • 20) 0.555 556 773 068 8 × 2 = 1 + 0.111 113 546 137 6;
  • 21) 0.111 113 546 137 6 × 2 = 0 + 0.222 227 092 275 2;
  • 22) 0.222 227 092 275 2 × 2 = 0 + 0.444 454 184 550 4;
  • 23) 0.444 454 184 550 4 × 2 = 0 + 0.888 908 369 100 8;
  • 24) 0.888 908 369 100 8 × 2 = 1 + 0.777 816 738 201 6;
  • 25) 0.777 816 738 201 6 × 2 = 1 + 0.555 633 476 403 2;
  • 26) 0.555 633 476 403 2 × 2 = 1 + 0.111 266 952 806 4;
  • 27) 0.111 266 952 806 4 × 2 = 0 + 0.222 533 905 612 8;
  • 28) 0.222 533 905 612 8 × 2 = 0 + 0.445 067 811 225 6;
  • 29) 0.445 067 811 225 6 × 2 = 0 + 0.890 135 622 451 2;
  • 30) 0.890 135 622 451 2 × 2 = 1 + 0.780 271 244 902 4;
  • 31) 0.780 271 244 902 4 × 2 = 1 + 0.560 542 489 804 8;
  • 32) 0.560 542 489 804 8 × 2 = 1 + 0.121 084 979 609 6;
  • 33) 0.121 084 979 609 6 × 2 = 0 + 0.242 169 959 219 2;
  • 34) 0.242 169 959 219 2 × 2 = 0 + 0.484 339 918 438 4;
  • 35) 0.484 339 918 438 4 × 2 = 0 + 0.968 679 836 876 8;
  • 36) 0.968 679 836 876 8 × 2 = 1 + 0.937 359 673 753 6;
  • 37) 0.937 359 673 753 6 × 2 = 1 + 0.874 719 347 507 2;
  • 38) 0.874 719 347 507 2 × 2 = 1 + 0.749 438 695 014 4;
  • 39) 0.749 438 695 014 4 × 2 = 1 + 0.498 877 390 028 8;
  • 40) 0.498 877 390 028 8 × 2 = 0 + 0.997 754 780 057 6;
  • 41) 0.997 754 780 057 6 × 2 = 1 + 0.995 509 560 115 2;
  • 42) 0.995 509 560 115 2 × 2 = 1 + 0.991 019 120 230 4;
  • 43) 0.991 019 120 230 4 × 2 = 1 + 0.982 038 240 460 8;
  • 44) 0.982 038 240 460 8 × 2 = 1 + 0.964 076 480 921 6;
  • 45) 0.964 076 480 921 6 × 2 = 1 + 0.928 152 961 843 2;
  • 46) 0.928 152 961 843 2 × 2 = 1 + 0.856 305 923 686 4;
  • 47) 0.856 305 923 686 4 × 2 = 1 + 0.712 611 847 372 8;
  • 48) 0.712 611 847 372 8 × 2 = 1 + 0.425 223 694 745 6;
  • 49) 0.425 223 694 745 6 × 2 = 0 + 0.850 447 389 491 2;
  • 50) 0.850 447 389 491 2 × 2 = 1 + 0.700 894 778 982 4;
  • 51) 0.700 894 778 982 4 × 2 = 1 + 0.401 789 557 964 8;
  • 52) 0.401 789 557 964 8 × 2 = 0 + 0.803 579 115 929 6;
  • 53) 0.803 579 115 929 6 × 2 = 1 + 0.607 158 231 859 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:


0.777 777 777 780 1(10) =


0.1100 0111 0001 1100 0111 0001 1100 0111 0001 1110 1111 1111 0110 1(2)

5. Positive number before normalization:

24.777 777 777 780 1(10) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1110 1111 1111 0110 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:


24.777 777 777 780 1(10) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1110 1111 1111 0110 1(2) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1110 1111 1111 0110 1(2) × 20 =


1.1000 1100 0111 0001 1100 0111 0001 1100 0111 0001 1110 1111 1111 0110 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 1110 1111 1111 0110 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 1110 1111 1111 0 1101 =


1000 1100 0111 0001 1100 0111 0001 1100 0111 0001 1110 1111 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 1110 1111 1111


Decimal number 24.777 777 777 780 1 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 1110 1111 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