13 781 290.158 489 992 725 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 13 781 290.158 489 992 725(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
13 781 290.158 489 992 725(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: 13 781 290.
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;
  • 13 781 290 ÷ 2 = 6 890 645 + 0;
  • 6 890 645 ÷ 2 = 3 445 322 + 1;
  • 3 445 322 ÷ 2 = 1 722 661 + 0;
  • 1 722 661 ÷ 2 = 861 330 + 1;
  • 861 330 ÷ 2 = 430 665 + 0;
  • 430 665 ÷ 2 = 215 332 + 1;
  • 215 332 ÷ 2 = 107 666 + 0;
  • 107 666 ÷ 2 = 53 833 + 0;
  • 53 833 ÷ 2 = 26 916 + 1;
  • 26 916 ÷ 2 = 13 458 + 0;
  • 13 458 ÷ 2 = 6 729 + 0;
  • 6 729 ÷ 2 = 3 364 + 1;
  • 3 364 ÷ 2 = 1 682 + 0;
  • 1 682 ÷ 2 = 841 + 0;
  • 841 ÷ 2 = 420 + 1;
  • 420 ÷ 2 = 210 + 0;
  • 210 ÷ 2 = 105 + 0;
  • 105 ÷ 2 = 52 + 1;
  • 52 ÷ 2 = 26 + 0;
  • 26 ÷ 2 = 13 + 0;
  • 13 ÷ 2 = 6 + 1;
  • 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.

13 781 290(10) =


1101 0010 0100 1001 0010 1010(2)


3. Convert to binary (base 2) the fractional part: 0.158 489 992 725.

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) 0.158 489 992 725 × 2 = 0 + 0.316 979 985 45;
  • 2) 0.316 979 985 45 × 2 = 0 + 0.633 959 970 9;
  • 3) 0.633 959 970 9 × 2 = 1 + 0.267 919 941 8;
  • 4) 0.267 919 941 8 × 2 = 0 + 0.535 839 883 6;
  • 5) 0.535 839 883 6 × 2 = 1 + 0.071 679 767 2;
  • 6) 0.071 679 767 2 × 2 = 0 + 0.143 359 534 4;
  • 7) 0.143 359 534 4 × 2 = 0 + 0.286 719 068 8;
  • 8) 0.286 719 068 8 × 2 = 0 + 0.573 438 137 6;
  • 9) 0.573 438 137 6 × 2 = 1 + 0.146 876 275 2;
  • 10) 0.146 876 275 2 × 2 = 0 + 0.293 752 550 4;
  • 11) 0.293 752 550 4 × 2 = 0 + 0.587 505 100 8;
  • 12) 0.587 505 100 8 × 2 = 1 + 0.175 010 201 6;
  • 13) 0.175 010 201 6 × 2 = 0 + 0.350 020 403 2;
  • 14) 0.350 020 403 2 × 2 = 0 + 0.700 040 806 4;
  • 15) 0.700 040 806 4 × 2 = 1 + 0.400 081 612 8;
  • 16) 0.400 081 612 8 × 2 = 0 + 0.800 163 225 6;
  • 17) 0.800 163 225 6 × 2 = 1 + 0.600 326 451 2;
  • 18) 0.600 326 451 2 × 2 = 1 + 0.200 652 902 4;
  • 19) 0.200 652 902 4 × 2 = 0 + 0.401 305 804 8;
  • 20) 0.401 305 804 8 × 2 = 0 + 0.802 611 609 6;
  • 21) 0.802 611 609 6 × 2 = 1 + 0.605 223 219 2;
  • 22) 0.605 223 219 2 × 2 = 1 + 0.210 446 438 4;
  • 23) 0.210 446 438 4 × 2 = 0 + 0.420 892 876 8;
  • 24) 0.420 892 876 8 × 2 = 0 + 0.841 785 753 6;
  • 25) 0.841 785 753 6 × 2 = 1 + 0.683 571 507 2;
  • 26) 0.683 571 507 2 × 2 = 1 + 0.367 143 014 4;
  • 27) 0.367 143 014 4 × 2 = 0 + 0.734 286 028 8;
  • 28) 0.734 286 028 8 × 2 = 1 + 0.468 572 057 6;
  • 29) 0.468 572 057 6 × 2 = 0 + 0.937 144 115 2;
  • 30) 0.937 144 115 2 × 2 = 1 + 0.874 288 230 4;
  • 31) 0.874 288 230 4 × 2 = 1 + 0.748 576 460 8;
  • 32) 0.748 576 460 8 × 2 = 1 + 0.497 152 921 6;
  • 33) 0.497 152 921 6 × 2 = 0 + 0.994 305 843 2;
  • 34) 0.994 305 843 2 × 2 = 1 + 0.988 611 686 4;
  • 35) 0.988 611 686 4 × 2 = 1 + 0.977 223 372 8;
  • 36) 0.977 223 372 8 × 2 = 1 + 0.954 446 745 6;
  • 37) 0.954 446 745 6 × 2 = 1 + 0.908 893 491 2;
  • 38) 0.908 893 491 2 × 2 = 1 + 0.817 786 982 4;
  • 39) 0.817 786 982 4 × 2 = 1 + 0.635 573 964 8;
  • 40) 0.635 573 964 8 × 2 = 1 + 0.271 147 929 6;
  • 41) 0.271 147 929 6 × 2 = 0 + 0.542 295 859 2;
  • 42) 0.542 295 859 2 × 2 = 1 + 0.084 591 718 4;
  • 43) 0.084 591 718 4 × 2 = 0 + 0.169 183 436 8;
  • 44) 0.169 183 436 8 × 2 = 0 + 0.338 366 873 6;
  • 45) 0.338 366 873 6 × 2 = 0 + 0.676 733 747 2;
  • 46) 0.676 733 747 2 × 2 = 1 + 0.353 467 494 4;
  • 47) 0.353 467 494 4 × 2 = 0 + 0.706 934 988 8;
  • 48) 0.706 934 988 8 × 2 = 1 + 0.413 869 977 6;
  • 49) 0.413 869 977 6 × 2 = 0 + 0.827 739 955 2;
  • 50) 0.827 739 955 2 × 2 = 1 + 0.655 479 910 4;
  • 51) 0.655 479 910 4 × 2 = 1 + 0.310 959 820 8;
  • 52) 0.310 959 820 8 × 2 = 0 + 0.621 919 641 6;
  • 53) 0.621 919 641 6 × 2 = 1 + 0.243 839 283 2;

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:


0.158 489 992 725(10) =


0.0010 1000 1001 0010 1100 1100 1101 0111 0111 1111 0100 0101 0110 1(2)

5. Positive number before normalization:

13 781 290.158 489 992 725(10) =


1101 0010 0100 1001 0010 1010.0010 1000 1001 0010 1100 1100 1101 0111 0111 1111 0100 0101 0110 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 23 positions to the left, so that only one non zero digit remains to the left of it:


13 781 290.158 489 992 725(10) =


1101 0010 0100 1001 0010 1010.0010 1000 1001 0010 1100 1100 1101 0111 0111 1111 0100 0101 0110 1(2) =


1101 0010 0100 1001 0010 1010.0010 1000 1001 0010 1100 1100 1101 0111 0111 1111 0100 0101 0110 1(2) × 20 =


1.1010 0100 1001 0010 0101 0100 0101 0001 0010 0101 1001 1001 1010 1110 1111 1110 1000 1010 1101(2) × 223


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): 23


Mantissa (not normalized):
1.1010 0100 1001 0010 0101 0100 0101 0001 0010 0101 1001 1001 1010 1110 1111 1110 1000 1010 1101


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


23 + 2(11-1) - 1 =


(23 + 1 023)(10) =


1 046(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;
  • 1 046 ÷ 2 = 523 + 0;
  • 523 ÷ 2 = 261 + 1;
  • 261 ÷ 2 = 130 + 1;
  • 130 ÷ 2 = 65 + 0;
  • 65 ÷ 2 = 32 + 1;
  • 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) =


1046(10) =


100 0001 0110(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. 1010 0100 1001 0010 0101 0100 0101 0001 0010 0101 1001 1001 1010 1110 1111 1110 1000 1010 1101 =


1010 0100 1001 0010 0101 0100 0101 0001 0010 0101 1001 1001 1010


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 0001 0110


Mantissa (52 bits) =
1010 0100 1001 0010 0101 0100 0101 0001 0010 0101 1001 1001 1010


Decimal number 13 781 290.158 489 992 725 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0001 0110 - 1010 0100 1001 0010 0101 0100 0101 0001 0010 0101 1001 1001 1010


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