12 894.389 999 999 999 372 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 12 894.389 999 999 999 372(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
12 894.389 999 999 999 372(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: 0.389 999 999 999 372.

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) 0.389 999 999 999 372 × 2 = 0 + 0.779 999 999 998 744;
  • 2) 0.779 999 999 998 744 × 2 = 1 + 0.559 999 999 997 488;
  • 3) 0.559 999 999 997 488 × 2 = 1 + 0.119 999 999 994 976;
  • 4) 0.119 999 999 994 976 × 2 = 0 + 0.239 999 999 989 952;
  • 5) 0.239 999 999 989 952 × 2 = 0 + 0.479 999 999 979 904;
  • 6) 0.479 999 999 979 904 × 2 = 0 + 0.959 999 999 959 808;
  • 7) 0.959 999 999 959 808 × 2 = 1 + 0.919 999 999 919 616;
  • 8) 0.919 999 999 919 616 × 2 = 1 + 0.839 999 999 839 232;
  • 9) 0.839 999 999 839 232 × 2 = 1 + 0.679 999 999 678 464;
  • 10) 0.679 999 999 678 464 × 2 = 1 + 0.359 999 999 356 928;
  • 11) 0.359 999 999 356 928 × 2 = 0 + 0.719 999 998 713 856;
  • 12) 0.719 999 998 713 856 × 2 = 1 + 0.439 999 997 427 712;
  • 13) 0.439 999 997 427 712 × 2 = 0 + 0.879 999 994 855 424;
  • 14) 0.879 999 994 855 424 × 2 = 1 + 0.759 999 989 710 848;
  • 15) 0.759 999 989 710 848 × 2 = 1 + 0.519 999 979 421 696;
  • 16) 0.519 999 979 421 696 × 2 = 1 + 0.039 999 958 843 392;
  • 17) 0.039 999 958 843 392 × 2 = 0 + 0.079 999 917 686 784;
  • 18) 0.079 999 917 686 784 × 2 = 0 + 0.159 999 835 373 568;
  • 19) 0.159 999 835 373 568 × 2 = 0 + 0.319 999 670 747 136;
  • 20) 0.319 999 670 747 136 × 2 = 0 + 0.639 999 341 494 272;
  • 21) 0.639 999 341 494 272 × 2 = 1 + 0.279 998 682 988 544;
  • 22) 0.279 998 682 988 544 × 2 = 0 + 0.559 997 365 977 088;
  • 23) 0.559 997 365 977 088 × 2 = 1 + 0.119 994 731 954 176;
  • 24) 0.119 994 731 954 176 × 2 = 0 + 0.239 989 463 908 352;
  • 25) 0.239 989 463 908 352 × 2 = 0 + 0.479 978 927 816 704;
  • 26) 0.479 978 927 816 704 × 2 = 0 + 0.959 957 855 633 408;
  • 27) 0.959 957 855 633 408 × 2 = 1 + 0.919 915 711 266 816;
  • 28) 0.919 915 711 266 816 × 2 = 1 + 0.839 831 422 533 632;
  • 29) 0.839 831 422 533 632 × 2 = 1 + 0.679 662 845 067 264;
  • 30) 0.679 662 845 067 264 × 2 = 1 + 0.359 325 690 134 528;
  • 31) 0.359 325 690 134 528 × 2 = 0 + 0.718 651 380 269 056;
  • 32) 0.718 651 380 269 056 × 2 = 1 + 0.437 302 760 538 112;
  • 33) 0.437 302 760 538 112 × 2 = 0 + 0.874 605 521 076 224;
  • 34) 0.874 605 521 076 224 × 2 = 1 + 0.749 211 042 152 448;
  • 35) 0.749 211 042 152 448 × 2 = 1 + 0.498 422 084 304 896;
  • 36) 0.498 422 084 304 896 × 2 = 0 + 0.996 844 168 609 792;
  • 37) 0.996 844 168 609 792 × 2 = 1 + 0.993 688 337 219 584;
  • 38) 0.993 688 337 219 584 × 2 = 1 + 0.987 376 674 439 168;
  • 39) 0.987 376 674 439 168 × 2 = 1 + 0.974 753 348 878 336;
  • 40) 0.974 753 348 878 336 × 2 = 1 + 0.949 506 697 756 672;
  • 41) 0.949 506 697 756 672 × 2 = 1 + 0.899 013 395 513 344;
  • 42) 0.899 013 395 513 344 × 2 = 1 + 0.798 026 791 026 688;
  • 43) 0.798 026 791 026 688 × 2 = 1 + 0.596 053 582 053 376;
  • 44) 0.596 053 582 053 376 × 2 = 1 + 0.192 107 164 106 752;
  • 45) 0.192 107 164 106 752 × 2 = 0 + 0.384 214 328 213 504;
  • 46) 0.384 214 328 213 504 × 2 = 0 + 0.768 428 656 427 008;
  • 47) 0.768 428 656 427 008 × 2 = 1 + 0.536 857 312 854 016;
  • 48) 0.536 857 312 854 016 × 2 = 1 + 0.073 714 625 708 032;
  • 49) 0.073 714 625 708 032 × 2 = 0 + 0.147 429 251 416 064;
  • 50) 0.147 429 251 416 064 × 2 = 0 + 0.294 858 502 832 128;
  • 51) 0.294 858 502 832 128 × 2 = 0 + 0.589 717 005 664 256;
  • 52) 0.589 717 005 664 256 × 2 = 1 + 0.179 434 011 328 512;
  • 53) 0.179 434 011 328 512 × 2 = 0 + 0.358 868 022 657 024;

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:


0.389 999 999 999 372(10) =


0.0110 0011 1101 0111 0000 1010 0011 1101 0110 1111 1111 0011 0001 0(2)

5. Positive number before normalization:

12 894.389 999 999 999 372(10) =


11 0010 0101 1110.0110 0011 1101 0111 0000 1010 0011 1101 0110 1111 1111 0011 0001 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:


12 894.389 999 999 999 372(10) =


11 0010 0101 1110.0110 0011 1101 0111 0000 1010 0011 1101 0110 1111 1111 0011 0001 0(2) =


11 0010 0101 1110.0110 0011 1101 0111 0000 1010 0011 1101 0110 1111 1111 0011 0001 0(2) × 20 =


1.1001 0010 1111 0011 0001 1110 1011 1000 0101 0001 1110 1011 0111 1111 1001 1000 10(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 1001 1000 10


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 0110 0010 =


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 12 894.389 999 999 999 372 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