24.777 777 777 777 777 775 9 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 24.777 777 777 777 777 775 9(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
24.777 777 777 777 777 775 9(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: 0.777 777 777 777 777 775 9.

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) 0.777 777 777 777 777 775 9 × 2 = 1 + 0.555 555 555 555 555 551 8;
  • 2) 0.555 555 555 555 555 551 8 × 2 = 1 + 0.111 111 111 111 111 103 6;
  • 3) 0.111 111 111 111 111 103 6 × 2 = 0 + 0.222 222 222 222 222 207 2;
  • 4) 0.222 222 222 222 222 207 2 × 2 = 0 + 0.444 444 444 444 444 414 4;
  • 5) 0.444 444 444 444 444 414 4 × 2 = 0 + 0.888 888 888 888 888 828 8;
  • 6) 0.888 888 888 888 888 828 8 × 2 = 1 + 0.777 777 777 777 777 657 6;
  • 7) 0.777 777 777 777 777 657 6 × 2 = 1 + 0.555 555 555 555 555 315 2;
  • 8) 0.555 555 555 555 555 315 2 × 2 = 1 + 0.111 111 111 111 110 630 4;
  • 9) 0.111 111 111 111 110 630 4 × 2 = 0 + 0.222 222 222 222 221 260 8;
  • 10) 0.222 222 222 222 221 260 8 × 2 = 0 + 0.444 444 444 444 442 521 6;
  • 11) 0.444 444 444 444 442 521 6 × 2 = 0 + 0.888 888 888 888 885 043 2;
  • 12) 0.888 888 888 888 885 043 2 × 2 = 1 + 0.777 777 777 777 770 086 4;
  • 13) 0.777 777 777 777 770 086 4 × 2 = 1 + 0.555 555 555 555 540 172 8;
  • 14) 0.555 555 555 555 540 172 8 × 2 = 1 + 0.111 111 111 111 080 345 6;
  • 15) 0.111 111 111 111 080 345 6 × 2 = 0 + 0.222 222 222 222 160 691 2;
  • 16) 0.222 222 222 222 160 691 2 × 2 = 0 + 0.444 444 444 444 321 382 4;
  • 17) 0.444 444 444 444 321 382 4 × 2 = 0 + 0.888 888 888 888 642 764 8;
  • 18) 0.888 888 888 888 642 764 8 × 2 = 1 + 0.777 777 777 777 285 529 6;
  • 19) 0.777 777 777 777 285 529 6 × 2 = 1 + 0.555 555 555 554 571 059 2;
  • 20) 0.555 555 555 554 571 059 2 × 2 = 1 + 0.111 111 111 109 142 118 4;
  • 21) 0.111 111 111 109 142 118 4 × 2 = 0 + 0.222 222 222 218 284 236 8;
  • 22) 0.222 222 222 218 284 236 8 × 2 = 0 + 0.444 444 444 436 568 473 6;
  • 23) 0.444 444 444 436 568 473 6 × 2 = 0 + 0.888 888 888 873 136 947 2;
  • 24) 0.888 888 888 873 136 947 2 × 2 = 1 + 0.777 777 777 746 273 894 4;
  • 25) 0.777 777 777 746 273 894 4 × 2 = 1 + 0.555 555 555 492 547 788 8;
  • 26) 0.555 555 555 492 547 788 8 × 2 = 1 + 0.111 111 110 985 095 577 6;
  • 27) 0.111 111 110 985 095 577 6 × 2 = 0 + 0.222 222 221 970 191 155 2;
  • 28) 0.222 222 221 970 191 155 2 × 2 = 0 + 0.444 444 443 940 382 310 4;
  • 29) 0.444 444 443 940 382 310 4 × 2 = 0 + 0.888 888 887 880 764 620 8;
  • 30) 0.888 888 887 880 764 620 8 × 2 = 1 + 0.777 777 775 761 529 241 6;
  • 31) 0.777 777 775 761 529 241 6 × 2 = 1 + 0.555 555 551 523 058 483 2;
  • 32) 0.555 555 551 523 058 483 2 × 2 = 1 + 0.111 111 103 046 116 966 4;
  • 33) 0.111 111 103 046 116 966 4 × 2 = 0 + 0.222 222 206 092 233 932 8;
  • 34) 0.222 222 206 092 233 932 8 × 2 = 0 + 0.444 444 412 184 467 865 6;
  • 35) 0.444 444 412 184 467 865 6 × 2 = 0 + 0.888 888 824 368 935 731 2;
  • 36) 0.888 888 824 368 935 731 2 × 2 = 1 + 0.777 777 648 737 871 462 4;
  • 37) 0.777 777 648 737 871 462 4 × 2 = 1 + 0.555 555 297 475 742 924 8;
  • 38) 0.555 555 297 475 742 924 8 × 2 = 1 + 0.111 110 594 951 485 849 6;
  • 39) 0.111 110 594 951 485 849 6 × 2 = 0 + 0.222 221 189 902 971 699 2;
  • 40) 0.222 221 189 902 971 699 2 × 2 = 0 + 0.444 442 379 805 943 398 4;
  • 41) 0.444 442 379 805 943 398 4 × 2 = 0 + 0.888 884 759 611 886 796 8;
  • 42) 0.888 884 759 611 886 796 8 × 2 = 1 + 0.777 769 519 223 773 593 6;
  • 43) 0.777 769 519 223 773 593 6 × 2 = 1 + 0.555 539 038 447 547 187 2;
  • 44) 0.555 539 038 447 547 187 2 × 2 = 1 + 0.111 078 076 895 094 374 4;
  • 45) 0.111 078 076 895 094 374 4 × 2 = 0 + 0.222 156 153 790 188 748 8;
  • 46) 0.222 156 153 790 188 748 8 × 2 = 0 + 0.444 312 307 580 377 497 6;
  • 47) 0.444 312 307 580 377 497 6 × 2 = 0 + 0.888 624 615 160 754 995 2;
  • 48) 0.888 624 615 160 754 995 2 × 2 = 1 + 0.777 249 230 321 509 990 4;
  • 49) 0.777 249 230 321 509 990 4 × 2 = 1 + 0.554 498 460 643 019 980 8;
  • 50) 0.554 498 460 643 019 980 8 × 2 = 1 + 0.108 996 921 286 039 961 6;
  • 51) 0.108 996 921 286 039 961 6 × 2 = 0 + 0.217 993 842 572 079 923 2;
  • 52) 0.217 993 842 572 079 923 2 × 2 = 0 + 0.435 987 685 144 159 846 4;
  • 53) 0.435 987 685 144 159 846 4 × 2 = 0 + 0.871 975 370 288 319 692 8;

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:


0.777 777 777 777 777 775 9(10) =


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

5. Positive number before normalization:

24.777 777 777 777 777 775 9(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:


24.777 777 777 777 777 775 9(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 24.777 777 777 777 777 775 9 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