24.777 777 777 776 51 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 24.777 777 777 776 51(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
24.777 777 777 776 51(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: 0.777 777 777 776 51.

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) 0.777 777 777 776 51 × 2 = 1 + 0.555 555 555 553 02;
  • 2) 0.555 555 555 553 02 × 2 = 1 + 0.111 111 111 106 04;
  • 3) 0.111 111 111 106 04 × 2 = 0 + 0.222 222 222 212 08;
  • 4) 0.222 222 222 212 08 × 2 = 0 + 0.444 444 444 424 16;
  • 5) 0.444 444 444 424 16 × 2 = 0 + 0.888 888 888 848 32;
  • 6) 0.888 888 888 848 32 × 2 = 1 + 0.777 777 777 696 64;
  • 7) 0.777 777 777 696 64 × 2 = 1 + 0.555 555 555 393 28;
  • 8) 0.555 555 555 393 28 × 2 = 1 + 0.111 111 110 786 56;
  • 9) 0.111 111 110 786 56 × 2 = 0 + 0.222 222 221 573 12;
  • 10) 0.222 222 221 573 12 × 2 = 0 + 0.444 444 443 146 24;
  • 11) 0.444 444 443 146 24 × 2 = 0 + 0.888 888 886 292 48;
  • 12) 0.888 888 886 292 48 × 2 = 1 + 0.777 777 772 584 96;
  • 13) 0.777 777 772 584 96 × 2 = 1 + 0.555 555 545 169 92;
  • 14) 0.555 555 545 169 92 × 2 = 1 + 0.111 111 090 339 84;
  • 15) 0.111 111 090 339 84 × 2 = 0 + 0.222 222 180 679 68;
  • 16) 0.222 222 180 679 68 × 2 = 0 + 0.444 444 361 359 36;
  • 17) 0.444 444 361 359 36 × 2 = 0 + 0.888 888 722 718 72;
  • 18) 0.888 888 722 718 72 × 2 = 1 + 0.777 777 445 437 44;
  • 19) 0.777 777 445 437 44 × 2 = 1 + 0.555 554 890 874 88;
  • 20) 0.555 554 890 874 88 × 2 = 1 + 0.111 109 781 749 76;
  • 21) 0.111 109 781 749 76 × 2 = 0 + 0.222 219 563 499 52;
  • 22) 0.222 219 563 499 52 × 2 = 0 + 0.444 439 126 999 04;
  • 23) 0.444 439 126 999 04 × 2 = 0 + 0.888 878 253 998 08;
  • 24) 0.888 878 253 998 08 × 2 = 1 + 0.777 756 507 996 16;
  • 25) 0.777 756 507 996 16 × 2 = 1 + 0.555 513 015 992 32;
  • 26) 0.555 513 015 992 32 × 2 = 1 + 0.111 026 031 984 64;
  • 27) 0.111 026 031 984 64 × 2 = 0 + 0.222 052 063 969 28;
  • 28) 0.222 052 063 969 28 × 2 = 0 + 0.444 104 127 938 56;
  • 29) 0.444 104 127 938 56 × 2 = 0 + 0.888 208 255 877 12;
  • 30) 0.888 208 255 877 12 × 2 = 1 + 0.776 416 511 754 24;
  • 31) 0.776 416 511 754 24 × 2 = 1 + 0.552 833 023 508 48;
  • 32) 0.552 833 023 508 48 × 2 = 1 + 0.105 666 047 016 96;
  • 33) 0.105 666 047 016 96 × 2 = 0 + 0.211 332 094 033 92;
  • 34) 0.211 332 094 033 92 × 2 = 0 + 0.422 664 188 067 84;
  • 35) 0.422 664 188 067 84 × 2 = 0 + 0.845 328 376 135 68;
  • 36) 0.845 328 376 135 68 × 2 = 1 + 0.690 656 752 271 36;
  • 37) 0.690 656 752 271 36 × 2 = 1 + 0.381 313 504 542 72;
  • 38) 0.381 313 504 542 72 × 2 = 0 + 0.762 627 009 085 44;
  • 39) 0.762 627 009 085 44 × 2 = 1 + 0.525 254 018 170 88;
  • 40) 0.525 254 018 170 88 × 2 = 1 + 0.050 508 036 341 76;
  • 41) 0.050 508 036 341 76 × 2 = 0 + 0.101 016 072 683 52;
  • 42) 0.101 016 072 683 52 × 2 = 0 + 0.202 032 145 367 04;
  • 43) 0.202 032 145 367 04 × 2 = 0 + 0.404 064 290 734 08;
  • 44) 0.404 064 290 734 08 × 2 = 0 + 0.808 128 581 468 16;
  • 45) 0.808 128 581 468 16 × 2 = 1 + 0.616 257 162 936 32;
  • 46) 0.616 257 162 936 32 × 2 = 1 + 0.232 514 325 872 64;
  • 47) 0.232 514 325 872 64 × 2 = 0 + 0.465 028 651 745 28;
  • 48) 0.465 028 651 745 28 × 2 = 0 + 0.930 057 303 490 56;
  • 49) 0.930 057 303 490 56 × 2 = 1 + 0.860 114 606 981 12;
  • 50) 0.860 114 606 981 12 × 2 = 1 + 0.720 229 213 962 24;
  • 51) 0.720 229 213 962 24 × 2 = 1 + 0.440 458 427 924 48;
  • 52) 0.440 458 427 924 48 × 2 = 0 + 0.880 916 855 848 96;
  • 53) 0.880 916 855 848 96 × 2 = 1 + 0.761 833 711 697 92;

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:


0.777 777 777 776 51(10) =


0.1100 0111 0001 1100 0111 0001 1100 0111 0001 1011 0000 1100 1110 1(2)

5. Positive number before normalization:

24.777 777 777 776 51(10) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1011 0000 1100 1110 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:


24.777 777 777 776 51(10) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1011 0000 1100 1110 1(2) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1011 0000 1100 1110 1(2) × 20 =


1.1000 1100 0111 0001 1100 0111 0001 1100 0111 0001 1011 0000 1100 1110 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 1011 0000 1100 1110 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 1011 0000 1100 1 1101 =


1000 1100 0111 0001 1100 0111 0001 1100 0111 0001 1011 0000 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 1011 0000 1100


Decimal number 24.777 777 777 776 51 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 1011 0000 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