24.777 777 777 777 778 85 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 24.777 777 777 777 778 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
24.777 777 777 777 778 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: 0.777 777 777 777 778 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) 0.777 777 777 777 778 85 × 2 = 1 + 0.555 555 555 555 557 7;
  • 2) 0.555 555 555 555 557 7 × 2 = 1 + 0.111 111 111 111 115 4;
  • 3) 0.111 111 111 111 115 4 × 2 = 0 + 0.222 222 222 222 230 8;
  • 4) 0.222 222 222 222 230 8 × 2 = 0 + 0.444 444 444 444 461 6;
  • 5) 0.444 444 444 444 461 6 × 2 = 0 + 0.888 888 888 888 923 2;
  • 6) 0.888 888 888 888 923 2 × 2 = 1 + 0.777 777 777 777 846 4;
  • 7) 0.777 777 777 777 846 4 × 2 = 1 + 0.555 555 555 555 692 8;
  • 8) 0.555 555 555 555 692 8 × 2 = 1 + 0.111 111 111 111 385 6;
  • 9) 0.111 111 111 111 385 6 × 2 = 0 + 0.222 222 222 222 771 2;
  • 10) 0.222 222 222 222 771 2 × 2 = 0 + 0.444 444 444 445 542 4;
  • 11) 0.444 444 444 445 542 4 × 2 = 0 + 0.888 888 888 891 084 8;
  • 12) 0.888 888 888 891 084 8 × 2 = 1 + 0.777 777 777 782 169 6;
  • 13) 0.777 777 777 782 169 6 × 2 = 1 + 0.555 555 555 564 339 2;
  • 14) 0.555 555 555 564 339 2 × 2 = 1 + 0.111 111 111 128 678 4;
  • 15) 0.111 111 111 128 678 4 × 2 = 0 + 0.222 222 222 257 356 8;
  • 16) 0.222 222 222 257 356 8 × 2 = 0 + 0.444 444 444 514 713 6;
  • 17) 0.444 444 444 514 713 6 × 2 = 0 + 0.888 888 889 029 427 2;
  • 18) 0.888 888 889 029 427 2 × 2 = 1 + 0.777 777 778 058 854 4;
  • 19) 0.777 777 778 058 854 4 × 2 = 1 + 0.555 555 556 117 708 8;
  • 20) 0.555 555 556 117 708 8 × 2 = 1 + 0.111 111 112 235 417 6;
  • 21) 0.111 111 112 235 417 6 × 2 = 0 + 0.222 222 224 470 835 2;
  • 22) 0.222 222 224 470 835 2 × 2 = 0 + 0.444 444 448 941 670 4;
  • 23) 0.444 444 448 941 670 4 × 2 = 0 + 0.888 888 897 883 340 8;
  • 24) 0.888 888 897 883 340 8 × 2 = 1 + 0.777 777 795 766 681 6;
  • 25) 0.777 777 795 766 681 6 × 2 = 1 + 0.555 555 591 533 363 2;
  • 26) 0.555 555 591 533 363 2 × 2 = 1 + 0.111 111 183 066 726 4;
  • 27) 0.111 111 183 066 726 4 × 2 = 0 + 0.222 222 366 133 452 8;
  • 28) 0.222 222 366 133 452 8 × 2 = 0 + 0.444 444 732 266 905 6;
  • 29) 0.444 444 732 266 905 6 × 2 = 0 + 0.888 889 464 533 811 2;
  • 30) 0.888 889 464 533 811 2 × 2 = 1 + 0.777 778 929 067 622 4;
  • 31) 0.777 778 929 067 622 4 × 2 = 1 + 0.555 557 858 135 244 8;
  • 32) 0.555 557 858 135 244 8 × 2 = 1 + 0.111 115 716 270 489 6;
  • 33) 0.111 115 716 270 489 6 × 2 = 0 + 0.222 231 432 540 979 2;
  • 34) 0.222 231 432 540 979 2 × 2 = 0 + 0.444 462 865 081 958 4;
  • 35) 0.444 462 865 081 958 4 × 2 = 0 + 0.888 925 730 163 916 8;
  • 36) 0.888 925 730 163 916 8 × 2 = 1 + 0.777 851 460 327 833 6;
  • 37) 0.777 851 460 327 833 6 × 2 = 1 + 0.555 702 920 655 667 2;
  • 38) 0.555 702 920 655 667 2 × 2 = 1 + 0.111 405 841 311 334 4;
  • 39) 0.111 405 841 311 334 4 × 2 = 0 + 0.222 811 682 622 668 8;
  • 40) 0.222 811 682 622 668 8 × 2 = 0 + 0.445 623 365 245 337 6;
  • 41) 0.445 623 365 245 337 6 × 2 = 0 + 0.891 246 730 490 675 2;
  • 42) 0.891 246 730 490 675 2 × 2 = 1 + 0.782 493 460 981 350 4;
  • 43) 0.782 493 460 981 350 4 × 2 = 1 + 0.564 986 921 962 700 8;
  • 44) 0.564 986 921 962 700 8 × 2 = 1 + 0.129 973 843 925 401 6;
  • 45) 0.129 973 843 925 401 6 × 2 = 0 + 0.259 947 687 850 803 2;
  • 46) 0.259 947 687 850 803 2 × 2 = 0 + 0.519 895 375 701 606 4;
  • 47) 0.519 895 375 701 606 4 × 2 = 1 + 0.039 790 751 403 212 8;
  • 48) 0.039 790 751 403 212 8 × 2 = 0 + 0.079 581 502 806 425 6;
  • 49) 0.079 581 502 806 425 6 × 2 = 0 + 0.159 163 005 612 851 2;
  • 50) 0.159 163 005 612 851 2 × 2 = 0 + 0.318 326 011 225 702 4;
  • 51) 0.318 326 011 225 702 4 × 2 = 0 + 0.636 652 022 451 404 8;
  • 52) 0.636 652 022 451 404 8 × 2 = 1 + 0.273 304 044 902 809 6;
  • 53) 0.273 304 044 902 809 6 × 2 = 0 + 0.546 608 089 805 619 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:


0.777 777 777 777 778 85(10) =


0.1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0010 0001 0(2)

5. Positive number before normalization:

24.777 777 777 777 778 85(10) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0010 0001 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:


24.777 777 777 777 778 85(10) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0010 0001 0(2) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0010 0001 0(2) × 20 =


1.1000 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0010 0001 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 0010 0001 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 0010 0 0010 =


1000 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0010


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 0010


Decimal number 24.777 777 777 777 778 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 0010


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