24.777 777 777 777 777 764 2 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 24.777 777 777 777 777 764 2(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
24.777 777 777 777 777 764 2(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: 0.777 777 777 777 777 764 2.

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) 0.777 777 777 777 777 764 2 × 2 = 1 + 0.555 555 555 555 555 528 4;
  • 2) 0.555 555 555 555 555 528 4 × 2 = 1 + 0.111 111 111 111 111 056 8;
  • 3) 0.111 111 111 111 111 056 8 × 2 = 0 + 0.222 222 222 222 222 113 6;
  • 4) 0.222 222 222 222 222 113 6 × 2 = 0 + 0.444 444 444 444 444 227 2;
  • 5) 0.444 444 444 444 444 227 2 × 2 = 0 + 0.888 888 888 888 888 454 4;
  • 6) 0.888 888 888 888 888 454 4 × 2 = 1 + 0.777 777 777 777 776 908 8;
  • 7) 0.777 777 777 777 776 908 8 × 2 = 1 + 0.555 555 555 555 553 817 6;
  • 8) 0.555 555 555 555 553 817 6 × 2 = 1 + 0.111 111 111 111 107 635 2;
  • 9) 0.111 111 111 111 107 635 2 × 2 = 0 + 0.222 222 222 222 215 270 4;
  • 10) 0.222 222 222 222 215 270 4 × 2 = 0 + 0.444 444 444 444 430 540 8;
  • 11) 0.444 444 444 444 430 540 8 × 2 = 0 + 0.888 888 888 888 861 081 6;
  • 12) 0.888 888 888 888 861 081 6 × 2 = 1 + 0.777 777 777 777 722 163 2;
  • 13) 0.777 777 777 777 722 163 2 × 2 = 1 + 0.555 555 555 555 444 326 4;
  • 14) 0.555 555 555 555 444 326 4 × 2 = 1 + 0.111 111 111 110 888 652 8;
  • 15) 0.111 111 111 110 888 652 8 × 2 = 0 + 0.222 222 222 221 777 305 6;
  • 16) 0.222 222 222 221 777 305 6 × 2 = 0 + 0.444 444 444 443 554 611 2;
  • 17) 0.444 444 444 443 554 611 2 × 2 = 0 + 0.888 888 888 887 109 222 4;
  • 18) 0.888 888 888 887 109 222 4 × 2 = 1 + 0.777 777 777 774 218 444 8;
  • 19) 0.777 777 777 774 218 444 8 × 2 = 1 + 0.555 555 555 548 436 889 6;
  • 20) 0.555 555 555 548 436 889 6 × 2 = 1 + 0.111 111 111 096 873 779 2;
  • 21) 0.111 111 111 096 873 779 2 × 2 = 0 + 0.222 222 222 193 747 558 4;
  • 22) 0.222 222 222 193 747 558 4 × 2 = 0 + 0.444 444 444 387 495 116 8;
  • 23) 0.444 444 444 387 495 116 8 × 2 = 0 + 0.888 888 888 774 990 233 6;
  • 24) 0.888 888 888 774 990 233 6 × 2 = 1 + 0.777 777 777 549 980 467 2;
  • 25) 0.777 777 777 549 980 467 2 × 2 = 1 + 0.555 555 555 099 960 934 4;
  • 26) 0.555 555 555 099 960 934 4 × 2 = 1 + 0.111 111 110 199 921 868 8;
  • 27) 0.111 111 110 199 921 868 8 × 2 = 0 + 0.222 222 220 399 843 737 6;
  • 28) 0.222 222 220 399 843 737 6 × 2 = 0 + 0.444 444 440 799 687 475 2;
  • 29) 0.444 444 440 799 687 475 2 × 2 = 0 + 0.888 888 881 599 374 950 4;
  • 30) 0.888 888 881 599 374 950 4 × 2 = 1 + 0.777 777 763 198 749 900 8;
  • 31) 0.777 777 763 198 749 900 8 × 2 = 1 + 0.555 555 526 397 499 801 6;
  • 32) 0.555 555 526 397 499 801 6 × 2 = 1 + 0.111 111 052 794 999 603 2;
  • 33) 0.111 111 052 794 999 603 2 × 2 = 0 + 0.222 222 105 589 999 206 4;
  • 34) 0.222 222 105 589 999 206 4 × 2 = 0 + 0.444 444 211 179 998 412 8;
  • 35) 0.444 444 211 179 998 412 8 × 2 = 0 + 0.888 888 422 359 996 825 6;
  • 36) 0.888 888 422 359 996 825 6 × 2 = 1 + 0.777 776 844 719 993 651 2;
  • 37) 0.777 776 844 719 993 651 2 × 2 = 1 + 0.555 553 689 439 987 302 4;
  • 38) 0.555 553 689 439 987 302 4 × 2 = 1 + 0.111 107 378 879 974 604 8;
  • 39) 0.111 107 378 879 974 604 8 × 2 = 0 + 0.222 214 757 759 949 209 6;
  • 40) 0.222 214 757 759 949 209 6 × 2 = 0 + 0.444 429 515 519 898 419 2;
  • 41) 0.444 429 515 519 898 419 2 × 2 = 0 + 0.888 859 031 039 796 838 4;
  • 42) 0.888 859 031 039 796 838 4 × 2 = 1 + 0.777 718 062 079 593 676 8;
  • 43) 0.777 718 062 079 593 676 8 × 2 = 1 + 0.555 436 124 159 187 353 6;
  • 44) 0.555 436 124 159 187 353 6 × 2 = 1 + 0.110 872 248 318 374 707 2;
  • 45) 0.110 872 248 318 374 707 2 × 2 = 0 + 0.221 744 496 636 749 414 4;
  • 46) 0.221 744 496 636 749 414 4 × 2 = 0 + 0.443 488 993 273 498 828 8;
  • 47) 0.443 488 993 273 498 828 8 × 2 = 0 + 0.886 977 986 546 997 657 6;
  • 48) 0.886 977 986 546 997 657 6 × 2 = 1 + 0.773 955 973 093 995 315 2;
  • 49) 0.773 955 973 093 995 315 2 × 2 = 1 + 0.547 911 946 187 990 630 4;
  • 50) 0.547 911 946 187 990 630 4 × 2 = 1 + 0.095 823 892 375 981 260 8;
  • 51) 0.095 823 892 375 981 260 8 × 2 = 0 + 0.191 647 784 751 962 521 6;
  • 52) 0.191 647 784 751 962 521 6 × 2 = 0 + 0.383 295 569 503 925 043 2;
  • 53) 0.383 295 569 503 925 043 2 × 2 = 0 + 0.766 591 139 007 850 086 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:


0.777 777 777 777 777 764 2(10) =


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

5. Positive number before normalization:

24.777 777 777 777 777 764 2(10) =


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


24.777 777 777 777 777 764 2(10) =


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


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


1.1000 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 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 0001 1100 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 0001 1 1000 =


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


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 0001


Decimal number 24.777 777 777 777 777 764 2 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 0001


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