12 894.389 999 999 999 381 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 12 894.389 999 999 999 381(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
12 894.389 999 999 999 381(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: 0.389 999 999 999 381.

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) 0.389 999 999 999 381 × 2 = 0 + 0.779 999 999 998 762;
  • 2) 0.779 999 999 998 762 × 2 = 1 + 0.559 999 999 997 524;
  • 3) 0.559 999 999 997 524 × 2 = 1 + 0.119 999 999 995 048;
  • 4) 0.119 999 999 995 048 × 2 = 0 + 0.239 999 999 990 096;
  • 5) 0.239 999 999 990 096 × 2 = 0 + 0.479 999 999 980 192;
  • 6) 0.479 999 999 980 192 × 2 = 0 + 0.959 999 999 960 384;
  • 7) 0.959 999 999 960 384 × 2 = 1 + 0.919 999 999 920 768;
  • 8) 0.919 999 999 920 768 × 2 = 1 + 0.839 999 999 841 536;
  • 9) 0.839 999 999 841 536 × 2 = 1 + 0.679 999 999 683 072;
  • 10) 0.679 999 999 683 072 × 2 = 1 + 0.359 999 999 366 144;
  • 11) 0.359 999 999 366 144 × 2 = 0 + 0.719 999 998 732 288;
  • 12) 0.719 999 998 732 288 × 2 = 1 + 0.439 999 997 464 576;
  • 13) 0.439 999 997 464 576 × 2 = 0 + 0.879 999 994 929 152;
  • 14) 0.879 999 994 929 152 × 2 = 1 + 0.759 999 989 858 304;
  • 15) 0.759 999 989 858 304 × 2 = 1 + 0.519 999 979 716 608;
  • 16) 0.519 999 979 716 608 × 2 = 1 + 0.039 999 959 433 216;
  • 17) 0.039 999 959 433 216 × 2 = 0 + 0.079 999 918 866 432;
  • 18) 0.079 999 918 866 432 × 2 = 0 + 0.159 999 837 732 864;
  • 19) 0.159 999 837 732 864 × 2 = 0 + 0.319 999 675 465 728;
  • 20) 0.319 999 675 465 728 × 2 = 0 + 0.639 999 350 931 456;
  • 21) 0.639 999 350 931 456 × 2 = 1 + 0.279 998 701 862 912;
  • 22) 0.279 998 701 862 912 × 2 = 0 + 0.559 997 403 725 824;
  • 23) 0.559 997 403 725 824 × 2 = 1 + 0.119 994 807 451 648;
  • 24) 0.119 994 807 451 648 × 2 = 0 + 0.239 989 614 903 296;
  • 25) 0.239 989 614 903 296 × 2 = 0 + 0.479 979 229 806 592;
  • 26) 0.479 979 229 806 592 × 2 = 0 + 0.959 958 459 613 184;
  • 27) 0.959 958 459 613 184 × 2 = 1 + 0.919 916 919 226 368;
  • 28) 0.919 916 919 226 368 × 2 = 1 + 0.839 833 838 452 736;
  • 29) 0.839 833 838 452 736 × 2 = 1 + 0.679 667 676 905 472;
  • 30) 0.679 667 676 905 472 × 2 = 1 + 0.359 335 353 810 944;
  • 31) 0.359 335 353 810 944 × 2 = 0 + 0.718 670 707 621 888;
  • 32) 0.718 670 707 621 888 × 2 = 1 + 0.437 341 415 243 776;
  • 33) 0.437 341 415 243 776 × 2 = 0 + 0.874 682 830 487 552;
  • 34) 0.874 682 830 487 552 × 2 = 1 + 0.749 365 660 975 104;
  • 35) 0.749 365 660 975 104 × 2 = 1 + 0.498 731 321 950 208;
  • 36) 0.498 731 321 950 208 × 2 = 0 + 0.997 462 643 900 416;
  • 37) 0.997 462 643 900 416 × 2 = 1 + 0.994 925 287 800 832;
  • 38) 0.994 925 287 800 832 × 2 = 1 + 0.989 850 575 601 664;
  • 39) 0.989 850 575 601 664 × 2 = 1 + 0.979 701 151 203 328;
  • 40) 0.979 701 151 203 328 × 2 = 1 + 0.959 402 302 406 656;
  • 41) 0.959 402 302 406 656 × 2 = 1 + 0.918 804 604 813 312;
  • 42) 0.918 804 604 813 312 × 2 = 1 + 0.837 609 209 626 624;
  • 43) 0.837 609 209 626 624 × 2 = 1 + 0.675 218 419 253 248;
  • 44) 0.675 218 419 253 248 × 2 = 1 + 0.350 436 838 506 496;
  • 45) 0.350 436 838 506 496 × 2 = 0 + 0.700 873 677 012 992;
  • 46) 0.700 873 677 012 992 × 2 = 1 + 0.401 747 354 025 984;
  • 47) 0.401 747 354 025 984 × 2 = 0 + 0.803 494 708 051 968;
  • 48) 0.803 494 708 051 968 × 2 = 1 + 0.606 989 416 103 936;
  • 49) 0.606 989 416 103 936 × 2 = 1 + 0.213 978 832 207 872;
  • 50) 0.213 978 832 207 872 × 2 = 0 + 0.427 957 664 415 744;
  • 51) 0.427 957 664 415 744 × 2 = 0 + 0.855 915 328 831 488;
  • 52) 0.855 915 328 831 488 × 2 = 1 + 0.711 830 657 662 976;
  • 53) 0.711 830 657 662 976 × 2 = 1 + 0.423 661 315 325 952;

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:


0.389 999 999 999 381(10) =


0.0110 0011 1101 0111 0000 1010 0011 1101 0110 1111 1111 0101 1001 1(2)

5. Positive number before normalization:

12 894.389 999 999 999 381(10) =


11 0010 0101 1110.0110 0011 1101 0111 0000 1010 0011 1101 0110 1111 1111 0101 1001 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:


12 894.389 999 999 999 381(10) =


11 0010 0101 1110.0110 0011 1101 0111 0000 1010 0011 1101 0110 1111 1111 0101 1001 1(2) =


11 0010 0101 1110.0110 0011 1101 0111 0000 1010 0011 1101 0110 1111 1111 0101 1001 1(2) × 20 =


1.1001 0010 1111 0011 0001 1110 1011 1000 0101 0001 1110 1011 0111 1111 1010 1100 11(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 1010 1100 11


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 1011 0011 =


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 12 894.389 999 999 999 381 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