24.777 777 777 775 95 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 24.777 777 777 775 95(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
24.777 777 777 775 95(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: 0.777 777 777 775 95.

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) 0.777 777 777 775 95 × 2 = 1 + 0.555 555 555 551 9;
  • 2) 0.555 555 555 551 9 × 2 = 1 + 0.111 111 111 103 8;
  • 3) 0.111 111 111 103 8 × 2 = 0 + 0.222 222 222 207 6;
  • 4) 0.222 222 222 207 6 × 2 = 0 + 0.444 444 444 415 2;
  • 5) 0.444 444 444 415 2 × 2 = 0 + 0.888 888 888 830 4;
  • 6) 0.888 888 888 830 4 × 2 = 1 + 0.777 777 777 660 8;
  • 7) 0.777 777 777 660 8 × 2 = 1 + 0.555 555 555 321 6;
  • 8) 0.555 555 555 321 6 × 2 = 1 + 0.111 111 110 643 2;
  • 9) 0.111 111 110 643 2 × 2 = 0 + 0.222 222 221 286 4;
  • 10) 0.222 222 221 286 4 × 2 = 0 + 0.444 444 442 572 8;
  • 11) 0.444 444 442 572 8 × 2 = 0 + 0.888 888 885 145 6;
  • 12) 0.888 888 885 145 6 × 2 = 1 + 0.777 777 770 291 2;
  • 13) 0.777 777 770 291 2 × 2 = 1 + 0.555 555 540 582 4;
  • 14) 0.555 555 540 582 4 × 2 = 1 + 0.111 111 081 164 8;
  • 15) 0.111 111 081 164 8 × 2 = 0 + 0.222 222 162 329 6;
  • 16) 0.222 222 162 329 6 × 2 = 0 + 0.444 444 324 659 2;
  • 17) 0.444 444 324 659 2 × 2 = 0 + 0.888 888 649 318 4;
  • 18) 0.888 888 649 318 4 × 2 = 1 + 0.777 777 298 636 8;
  • 19) 0.777 777 298 636 8 × 2 = 1 + 0.555 554 597 273 6;
  • 20) 0.555 554 597 273 6 × 2 = 1 + 0.111 109 194 547 2;
  • 21) 0.111 109 194 547 2 × 2 = 0 + 0.222 218 389 094 4;
  • 22) 0.222 218 389 094 4 × 2 = 0 + 0.444 436 778 188 8;
  • 23) 0.444 436 778 188 8 × 2 = 0 + 0.888 873 556 377 6;
  • 24) 0.888 873 556 377 6 × 2 = 1 + 0.777 747 112 755 2;
  • 25) 0.777 747 112 755 2 × 2 = 1 + 0.555 494 225 510 4;
  • 26) 0.555 494 225 510 4 × 2 = 1 + 0.110 988 451 020 8;
  • 27) 0.110 988 451 020 8 × 2 = 0 + 0.221 976 902 041 6;
  • 28) 0.221 976 902 041 6 × 2 = 0 + 0.443 953 804 083 2;
  • 29) 0.443 953 804 083 2 × 2 = 0 + 0.887 907 608 166 4;
  • 30) 0.887 907 608 166 4 × 2 = 1 + 0.775 815 216 332 8;
  • 31) 0.775 815 216 332 8 × 2 = 1 + 0.551 630 432 665 6;
  • 32) 0.551 630 432 665 6 × 2 = 1 + 0.103 260 865 331 2;
  • 33) 0.103 260 865 331 2 × 2 = 0 + 0.206 521 730 662 4;
  • 34) 0.206 521 730 662 4 × 2 = 0 + 0.413 043 461 324 8;
  • 35) 0.413 043 461 324 8 × 2 = 0 + 0.826 086 922 649 6;
  • 36) 0.826 086 922 649 6 × 2 = 1 + 0.652 173 845 299 2;
  • 37) 0.652 173 845 299 2 × 2 = 1 + 0.304 347 690 598 4;
  • 38) 0.304 347 690 598 4 × 2 = 0 + 0.608 695 381 196 8;
  • 39) 0.608 695 381 196 8 × 2 = 1 + 0.217 390 762 393 6;
  • 40) 0.217 390 762 393 6 × 2 = 0 + 0.434 781 524 787 2;
  • 41) 0.434 781 524 787 2 × 2 = 0 + 0.869 563 049 574 4;
  • 42) 0.869 563 049 574 4 × 2 = 1 + 0.739 126 099 148 8;
  • 43) 0.739 126 099 148 8 × 2 = 1 + 0.478 252 198 297 6;
  • 44) 0.478 252 198 297 6 × 2 = 0 + 0.956 504 396 595 2;
  • 45) 0.956 504 396 595 2 × 2 = 1 + 0.913 008 793 190 4;
  • 46) 0.913 008 793 190 4 × 2 = 1 + 0.826 017 586 380 8;
  • 47) 0.826 017 586 380 8 × 2 = 1 + 0.652 035 172 761 6;
  • 48) 0.652 035 172 761 6 × 2 = 1 + 0.304 070 345 523 2;
  • 49) 0.304 070 345 523 2 × 2 = 0 + 0.608 140 691 046 4;
  • 50) 0.608 140 691 046 4 × 2 = 1 + 0.216 281 382 092 8;
  • 51) 0.216 281 382 092 8 × 2 = 0 + 0.432 562 764 185 6;
  • 52) 0.432 562 764 185 6 × 2 = 0 + 0.865 125 528 371 2;
  • 53) 0.865 125 528 371 2 × 2 = 1 + 0.730 251 056 742 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:


0.777 777 777 775 95(10) =


0.1100 0111 0001 1100 0111 0001 1100 0111 0001 1010 0110 1111 0100 1(2)

5. Positive number before normalization:

24.777 777 777 775 95(10) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1010 0110 1111 0100 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:


24.777 777 777 775 95(10) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1010 0110 1111 0100 1(2) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1010 0110 1111 0100 1(2) × 20 =


1.1000 1100 0111 0001 1100 0111 0001 1100 0111 0001 1010 0110 1111 0100 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 1010 0110 1111 0100 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 1010 0110 1111 0 1001 =


1000 1100 0111 0001 1100 0111 0001 1100 0111 0001 1010 0110 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 1010 0110 1111


Decimal number 24.777 777 777 775 95 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 1010 0110 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