12 894.389 999 999 999 401 2 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 12 894.389 999 999 999 401 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
12 894.389 999 999 999 401 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: 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: 0.389 999 999 999 401 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) 0.389 999 999 999 401 2 × 2 = 0 + 0.779 999 999 998 802 4;
  • 2) 0.779 999 999 998 802 4 × 2 = 1 + 0.559 999 999 997 604 8;
  • 3) 0.559 999 999 997 604 8 × 2 = 1 + 0.119 999 999 995 209 6;
  • 4) 0.119 999 999 995 209 6 × 2 = 0 + 0.239 999 999 990 419 2;
  • 5) 0.239 999 999 990 419 2 × 2 = 0 + 0.479 999 999 980 838 4;
  • 6) 0.479 999 999 980 838 4 × 2 = 0 + 0.959 999 999 961 676 8;
  • 7) 0.959 999 999 961 676 8 × 2 = 1 + 0.919 999 999 923 353 6;
  • 8) 0.919 999 999 923 353 6 × 2 = 1 + 0.839 999 999 846 707 2;
  • 9) 0.839 999 999 846 707 2 × 2 = 1 + 0.679 999 999 693 414 4;
  • 10) 0.679 999 999 693 414 4 × 2 = 1 + 0.359 999 999 386 828 8;
  • 11) 0.359 999 999 386 828 8 × 2 = 0 + 0.719 999 998 773 657 6;
  • 12) 0.719 999 998 773 657 6 × 2 = 1 + 0.439 999 997 547 315 2;
  • 13) 0.439 999 997 547 315 2 × 2 = 0 + 0.879 999 995 094 630 4;
  • 14) 0.879 999 995 094 630 4 × 2 = 1 + 0.759 999 990 189 260 8;
  • 15) 0.759 999 990 189 260 8 × 2 = 1 + 0.519 999 980 378 521 6;
  • 16) 0.519 999 980 378 521 6 × 2 = 1 + 0.039 999 960 757 043 2;
  • 17) 0.039 999 960 757 043 2 × 2 = 0 + 0.079 999 921 514 086 4;
  • 18) 0.079 999 921 514 086 4 × 2 = 0 + 0.159 999 843 028 172 8;
  • 19) 0.159 999 843 028 172 8 × 2 = 0 + 0.319 999 686 056 345 6;
  • 20) 0.319 999 686 056 345 6 × 2 = 0 + 0.639 999 372 112 691 2;
  • 21) 0.639 999 372 112 691 2 × 2 = 1 + 0.279 998 744 225 382 4;
  • 22) 0.279 998 744 225 382 4 × 2 = 0 + 0.559 997 488 450 764 8;
  • 23) 0.559 997 488 450 764 8 × 2 = 1 + 0.119 994 976 901 529 6;
  • 24) 0.119 994 976 901 529 6 × 2 = 0 + 0.239 989 953 803 059 2;
  • 25) 0.239 989 953 803 059 2 × 2 = 0 + 0.479 979 907 606 118 4;
  • 26) 0.479 979 907 606 118 4 × 2 = 0 + 0.959 959 815 212 236 8;
  • 27) 0.959 959 815 212 236 8 × 2 = 1 + 0.919 919 630 424 473 6;
  • 28) 0.919 919 630 424 473 6 × 2 = 1 + 0.839 839 260 848 947 2;
  • 29) 0.839 839 260 848 947 2 × 2 = 1 + 0.679 678 521 697 894 4;
  • 30) 0.679 678 521 697 894 4 × 2 = 1 + 0.359 357 043 395 788 8;
  • 31) 0.359 357 043 395 788 8 × 2 = 0 + 0.718 714 086 791 577 6;
  • 32) 0.718 714 086 791 577 6 × 2 = 1 + 0.437 428 173 583 155 2;
  • 33) 0.437 428 173 583 155 2 × 2 = 0 + 0.874 856 347 166 310 4;
  • 34) 0.874 856 347 166 310 4 × 2 = 1 + 0.749 712 694 332 620 8;
  • 35) 0.749 712 694 332 620 8 × 2 = 1 + 0.499 425 388 665 241 6;
  • 36) 0.499 425 388 665 241 6 × 2 = 0 + 0.998 850 777 330 483 2;
  • 37) 0.998 850 777 330 483 2 × 2 = 1 + 0.997 701 554 660 966 4;
  • 38) 0.997 701 554 660 966 4 × 2 = 1 + 0.995 403 109 321 932 8;
  • 39) 0.995 403 109 321 932 8 × 2 = 1 + 0.990 806 218 643 865 6;
  • 40) 0.990 806 218 643 865 6 × 2 = 1 + 0.981 612 437 287 731 2;
  • 41) 0.981 612 437 287 731 2 × 2 = 1 + 0.963 224 874 575 462 4;
  • 42) 0.963 224 874 575 462 4 × 2 = 1 + 0.926 449 749 150 924 8;
  • 43) 0.926 449 749 150 924 8 × 2 = 1 + 0.852 899 498 301 849 6;
  • 44) 0.852 899 498 301 849 6 × 2 = 1 + 0.705 798 996 603 699 2;
  • 45) 0.705 798 996 603 699 2 × 2 = 1 + 0.411 597 993 207 398 4;
  • 46) 0.411 597 993 207 398 4 × 2 = 0 + 0.823 195 986 414 796 8;
  • 47) 0.823 195 986 414 796 8 × 2 = 1 + 0.646 391 972 829 593 6;
  • 48) 0.646 391 972 829 593 6 × 2 = 1 + 0.292 783 945 659 187 2;
  • 49) 0.292 783 945 659 187 2 × 2 = 0 + 0.585 567 891 318 374 4;
  • 50) 0.585 567 891 318 374 4 × 2 = 1 + 0.171 135 782 636 748 8;
  • 51) 0.171 135 782 636 748 8 × 2 = 0 + 0.342 271 565 273 497 6;
  • 52) 0.342 271 565 273 497 6 × 2 = 0 + 0.684 543 130 546 995 2;
  • 53) 0.684 543 130 546 995 2 × 2 = 1 + 0.369 086 261 093 990 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:


0.389 999 999 999 401 2(10) =


0.0110 0011 1101 0111 0000 1010 0011 1101 0110 1111 1111 1011 0100 1(2)

5. Positive number before normalization:

12 894.389 999 999 999 401 2(10) =


11 0010 0101 1110.0110 0011 1101 0111 0000 1010 0011 1101 0110 1111 1111 1011 0100 1(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:


12 894.389 999 999 999 401 2(10) =


11 0010 0101 1110.0110 0011 1101 0111 0000 1010 0011 1101 0110 1111 1111 1011 0100 1(2) =


11 0010 0101 1110.0110 0011 1101 0111 0000 1010 0011 1101 0110 1111 1111 1011 0100 1(2) × 20 =


1.1001 0010 1111 0011 0001 1110 1011 1000 0101 0001 1110 1011 0111 1111 1101 1010 01(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 1101 1010 01


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 1111 0110 1001 =


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 12 894.389 999 999 999 401 2 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