12 894.389 999 999 999 388 7 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 12 894.389 999 999 999 388 7(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
12 894.389 999 999 999 388 7(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: 12 894.
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;
  • 12 894 ÷ 2 = 6 447 + 0;
  • 6 447 ÷ 2 = 3 223 + 1;
  • 3 223 ÷ 2 = 1 611 + 1;
  • 1 611 ÷ 2 = 805 + 1;
  • 805 ÷ 2 = 402 + 1;
  • 402 ÷ 2 = 201 + 0;
  • 201 ÷ 2 = 100 + 1;
  • 100 ÷ 2 = 50 + 0;
  • 50 ÷ 2 = 25 + 0;
  • 25 ÷ 2 = 12 + 1;
  • 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.

12 894(10) =


11 0010 0101 1110(2)


3. Convert to binary (base 2) the fractional part: 0.389 999 999 999 388 7.

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) 0.389 999 999 999 388 7 × 2 = 0 + 0.779 999 999 998 777 4;
  • 2) 0.779 999 999 998 777 4 × 2 = 1 + 0.559 999 999 997 554 8;
  • 3) 0.559 999 999 997 554 8 × 2 = 1 + 0.119 999 999 995 109 6;
  • 4) 0.119 999 999 995 109 6 × 2 = 0 + 0.239 999 999 990 219 2;
  • 5) 0.239 999 999 990 219 2 × 2 = 0 + 0.479 999 999 980 438 4;
  • 6) 0.479 999 999 980 438 4 × 2 = 0 + 0.959 999 999 960 876 8;
  • 7) 0.959 999 999 960 876 8 × 2 = 1 + 0.919 999 999 921 753 6;
  • 8) 0.919 999 999 921 753 6 × 2 = 1 + 0.839 999 999 843 507 2;
  • 9) 0.839 999 999 843 507 2 × 2 = 1 + 0.679 999 999 687 014 4;
  • 10) 0.679 999 999 687 014 4 × 2 = 1 + 0.359 999 999 374 028 8;
  • 11) 0.359 999 999 374 028 8 × 2 = 0 + 0.719 999 998 748 057 6;
  • 12) 0.719 999 998 748 057 6 × 2 = 1 + 0.439 999 997 496 115 2;
  • 13) 0.439 999 997 496 115 2 × 2 = 0 + 0.879 999 994 992 230 4;
  • 14) 0.879 999 994 992 230 4 × 2 = 1 + 0.759 999 989 984 460 8;
  • 15) 0.759 999 989 984 460 8 × 2 = 1 + 0.519 999 979 968 921 6;
  • 16) 0.519 999 979 968 921 6 × 2 = 1 + 0.039 999 959 937 843 2;
  • 17) 0.039 999 959 937 843 2 × 2 = 0 + 0.079 999 919 875 686 4;
  • 18) 0.079 999 919 875 686 4 × 2 = 0 + 0.159 999 839 751 372 8;
  • 19) 0.159 999 839 751 372 8 × 2 = 0 + 0.319 999 679 502 745 6;
  • 20) 0.319 999 679 502 745 6 × 2 = 0 + 0.639 999 359 005 491 2;
  • 21) 0.639 999 359 005 491 2 × 2 = 1 + 0.279 998 718 010 982 4;
  • 22) 0.279 998 718 010 982 4 × 2 = 0 + 0.559 997 436 021 964 8;
  • 23) 0.559 997 436 021 964 8 × 2 = 1 + 0.119 994 872 043 929 6;
  • 24) 0.119 994 872 043 929 6 × 2 = 0 + 0.239 989 744 087 859 2;
  • 25) 0.239 989 744 087 859 2 × 2 = 0 + 0.479 979 488 175 718 4;
  • 26) 0.479 979 488 175 718 4 × 2 = 0 + 0.959 958 976 351 436 8;
  • 27) 0.959 958 976 351 436 8 × 2 = 1 + 0.919 917 952 702 873 6;
  • 28) 0.919 917 952 702 873 6 × 2 = 1 + 0.839 835 905 405 747 2;
  • 29) 0.839 835 905 405 747 2 × 2 = 1 + 0.679 671 810 811 494 4;
  • 30) 0.679 671 810 811 494 4 × 2 = 1 + 0.359 343 621 622 988 8;
  • 31) 0.359 343 621 622 988 8 × 2 = 0 + 0.718 687 243 245 977 6;
  • 32) 0.718 687 243 245 977 6 × 2 = 1 + 0.437 374 486 491 955 2;
  • 33) 0.437 374 486 491 955 2 × 2 = 0 + 0.874 748 972 983 910 4;
  • 34) 0.874 748 972 983 910 4 × 2 = 1 + 0.749 497 945 967 820 8;
  • 35) 0.749 497 945 967 820 8 × 2 = 1 + 0.498 995 891 935 641 6;
  • 36) 0.498 995 891 935 641 6 × 2 = 0 + 0.997 991 783 871 283 2;
  • 37) 0.997 991 783 871 283 2 × 2 = 1 + 0.995 983 567 742 566 4;
  • 38) 0.995 983 567 742 566 4 × 2 = 1 + 0.991 967 135 485 132 8;
  • 39) 0.991 967 135 485 132 8 × 2 = 1 + 0.983 934 270 970 265 6;
  • 40) 0.983 934 270 970 265 6 × 2 = 1 + 0.967 868 541 940 531 2;
  • 41) 0.967 868 541 940 531 2 × 2 = 1 + 0.935 737 083 881 062 4;
  • 42) 0.935 737 083 881 062 4 × 2 = 1 + 0.871 474 167 762 124 8;
  • 43) 0.871 474 167 762 124 8 × 2 = 1 + 0.742 948 335 524 249 6;
  • 44) 0.742 948 335 524 249 6 × 2 = 1 + 0.485 896 671 048 499 2;
  • 45) 0.485 896 671 048 499 2 × 2 = 0 + 0.971 793 342 096 998 4;
  • 46) 0.971 793 342 096 998 4 × 2 = 1 + 0.943 586 684 193 996 8;
  • 47) 0.943 586 684 193 996 8 × 2 = 1 + 0.887 173 368 387 993 6;
  • 48) 0.887 173 368 387 993 6 × 2 = 1 + 0.774 346 736 775 987 2;
  • 49) 0.774 346 736 775 987 2 × 2 = 1 + 0.548 693 473 551 974 4;
  • 50) 0.548 693 473 551 974 4 × 2 = 1 + 0.097 386 947 103 948 8;
  • 51) 0.097 386 947 103 948 8 × 2 = 0 + 0.194 773 894 207 897 6;
  • 52) 0.194 773 894 207 897 6 × 2 = 0 + 0.389 547 788 415 795 2;
  • 53) 0.389 547 788 415 795 2 × 2 = 0 + 0.779 095 576 831 590 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:


0.389 999 999 999 388 7(10) =


0.0110 0011 1101 0111 0000 1010 0011 1101 0110 1111 1111 0111 1100 0(2)

5. Positive number before normalization:

12 894.389 999 999 999 388 7(10) =


11 0010 0101 1110.0110 0011 1101 0111 0000 1010 0011 1101 0110 1111 1111 0111 1100 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 13 positions to the left, so that only one non zero digit remains to the left of it:


12 894.389 999 999 999 388 7(10) =


11 0010 0101 1110.0110 0011 1101 0111 0000 1010 0011 1101 0110 1111 1111 0111 1100 0(2) =


11 0010 0101 1110.0110 0011 1101 0111 0000 1010 0011 1101 0110 1111 1111 0111 1100 0(2) × 20 =


1.1001 0010 1111 0011 0001 1110 1011 1000 0101 0001 1110 1011 0111 1111 1011 1110 00(2) × 213


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): 13


Mantissa (not normalized):
1.1001 0010 1111 0011 0001 1110 1011 1000 0101 0001 1110 1011 0111 1111 1011 1110 00


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(11-1) - 1 =


13 + 2(11-1) - 1 =


(13 + 1 023)(10) =


1 036(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;
  • 1 036 ÷ 2 = 518 + 0;
  • 518 ÷ 2 = 259 + 0;
  • 259 ÷ 2 = 129 + 1;
  • 129 ÷ 2 = 64 + 1;
  • 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) =


1036(10) =


100 0000 1100(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. 1001 0010 1111 0011 0001 1110 1011 1000 0101 0001 1110 1011 0111 11 1110 1111 1000 =


1001 0010 1111 0011 0001 1110 1011 1000 0101 0001 1110 1011 0111


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 1100


Mantissa (52 bits) =
1001 0010 1111 0011 0001 1110 1011 1000 0101 0001 1110 1011 0111


Decimal number 12 894.389 999 999 999 388 7 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 1100 - 1001 0010 1111 0011 0001 1110 1011 1000 0101 0001 1110 1011 0111


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