24.777 777 777 777 645 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 24.777 777 777 777 645(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
24.777 777 777 777 645(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: 0.777 777 777 777 645.

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) 0.777 777 777 777 645 × 2 = 1 + 0.555 555 555 555 29;
  • 2) 0.555 555 555 555 29 × 2 = 1 + 0.111 111 111 110 58;
  • 3) 0.111 111 111 110 58 × 2 = 0 + 0.222 222 222 221 16;
  • 4) 0.222 222 222 221 16 × 2 = 0 + 0.444 444 444 442 32;
  • 5) 0.444 444 444 442 32 × 2 = 0 + 0.888 888 888 884 64;
  • 6) 0.888 888 888 884 64 × 2 = 1 + 0.777 777 777 769 28;
  • 7) 0.777 777 777 769 28 × 2 = 1 + 0.555 555 555 538 56;
  • 8) 0.555 555 555 538 56 × 2 = 1 + 0.111 111 111 077 12;
  • 9) 0.111 111 111 077 12 × 2 = 0 + 0.222 222 222 154 24;
  • 10) 0.222 222 222 154 24 × 2 = 0 + 0.444 444 444 308 48;
  • 11) 0.444 444 444 308 48 × 2 = 0 + 0.888 888 888 616 96;
  • 12) 0.888 888 888 616 96 × 2 = 1 + 0.777 777 777 233 92;
  • 13) 0.777 777 777 233 92 × 2 = 1 + 0.555 555 554 467 84;
  • 14) 0.555 555 554 467 84 × 2 = 1 + 0.111 111 108 935 68;
  • 15) 0.111 111 108 935 68 × 2 = 0 + 0.222 222 217 871 36;
  • 16) 0.222 222 217 871 36 × 2 = 0 + 0.444 444 435 742 72;
  • 17) 0.444 444 435 742 72 × 2 = 0 + 0.888 888 871 485 44;
  • 18) 0.888 888 871 485 44 × 2 = 1 + 0.777 777 742 970 88;
  • 19) 0.777 777 742 970 88 × 2 = 1 + 0.555 555 485 941 76;
  • 20) 0.555 555 485 941 76 × 2 = 1 + 0.111 110 971 883 52;
  • 21) 0.111 110 971 883 52 × 2 = 0 + 0.222 221 943 767 04;
  • 22) 0.222 221 943 767 04 × 2 = 0 + 0.444 443 887 534 08;
  • 23) 0.444 443 887 534 08 × 2 = 0 + 0.888 887 775 068 16;
  • 24) 0.888 887 775 068 16 × 2 = 1 + 0.777 775 550 136 32;
  • 25) 0.777 775 550 136 32 × 2 = 1 + 0.555 551 100 272 64;
  • 26) 0.555 551 100 272 64 × 2 = 1 + 0.111 102 200 545 28;
  • 27) 0.111 102 200 545 28 × 2 = 0 + 0.222 204 401 090 56;
  • 28) 0.222 204 401 090 56 × 2 = 0 + 0.444 408 802 181 12;
  • 29) 0.444 408 802 181 12 × 2 = 0 + 0.888 817 604 362 24;
  • 30) 0.888 817 604 362 24 × 2 = 1 + 0.777 635 208 724 48;
  • 31) 0.777 635 208 724 48 × 2 = 1 + 0.555 270 417 448 96;
  • 32) 0.555 270 417 448 96 × 2 = 1 + 0.110 540 834 897 92;
  • 33) 0.110 540 834 897 92 × 2 = 0 + 0.221 081 669 795 84;
  • 34) 0.221 081 669 795 84 × 2 = 0 + 0.442 163 339 591 68;
  • 35) 0.442 163 339 591 68 × 2 = 0 + 0.884 326 679 183 36;
  • 36) 0.884 326 679 183 36 × 2 = 1 + 0.768 653 358 366 72;
  • 37) 0.768 653 358 366 72 × 2 = 1 + 0.537 306 716 733 44;
  • 38) 0.537 306 716 733 44 × 2 = 1 + 0.074 613 433 466 88;
  • 39) 0.074 613 433 466 88 × 2 = 0 + 0.149 226 866 933 76;
  • 40) 0.149 226 866 933 76 × 2 = 0 + 0.298 453 733 867 52;
  • 41) 0.298 453 733 867 52 × 2 = 0 + 0.596 907 467 735 04;
  • 42) 0.596 907 467 735 04 × 2 = 1 + 0.193 814 935 470 08;
  • 43) 0.193 814 935 470 08 × 2 = 0 + 0.387 629 870 940 16;
  • 44) 0.387 629 870 940 16 × 2 = 0 + 0.775 259 741 880 32;
  • 45) 0.775 259 741 880 32 × 2 = 1 + 0.550 519 483 760 64;
  • 46) 0.550 519 483 760 64 × 2 = 1 + 0.101 038 967 521 28;
  • 47) 0.101 038 967 521 28 × 2 = 0 + 0.202 077 935 042 56;
  • 48) 0.202 077 935 042 56 × 2 = 0 + 0.404 155 870 085 12;
  • 49) 0.404 155 870 085 12 × 2 = 0 + 0.808 311 740 170 24;
  • 50) 0.808 311 740 170 24 × 2 = 1 + 0.616 623 480 340 48;
  • 51) 0.616 623 480 340 48 × 2 = 1 + 0.233 246 960 680 96;
  • 52) 0.233 246 960 680 96 × 2 = 0 + 0.466 493 921 361 92;
  • 53) 0.466 493 921 361 92 × 2 = 0 + 0.932 987 842 723 84;

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:


0.777 777 777 777 645(10) =


0.1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0100 1100 0110 0(2)

5. Positive number before normalization:

24.777 777 777 777 645(10) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0100 1100 0110 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:


24.777 777 777 777 645(10) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0100 1100 0110 0(2) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0100 1100 0110 0(2) × 20 =


1.1000 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0100 1100 0110 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 0100 1100 0110 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 0100 1100 0 1100 =


1000 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0100 1100


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 0100 1100


Decimal number 24.777 777 777 777 645 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 0100 1100


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