64bit IEEE 754: Decimal ↗ Double Precision Floating Point Binary: 0.666 503 906 26 Convert the Number to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From a Base Ten Decimal System Number

Number 0.666 503 906 26(10) converted and written in 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: 0.
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;
  • 0 ÷ 2 = 0 + 0;

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.


0(10) =


0(2)


3. Convert to binary (base 2) the fractional part: 0.666 503 906 26.

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) 0.666 503 906 26 × 2 = 1 + 0.333 007 812 52;
  • 2) 0.333 007 812 52 × 2 = 0 + 0.666 015 625 04;
  • 3) 0.666 015 625 04 × 2 = 1 + 0.332 031 250 08;
  • 4) 0.332 031 250 08 × 2 = 0 + 0.664 062 500 16;
  • 5) 0.664 062 500 16 × 2 = 1 + 0.328 125 000 32;
  • 6) 0.328 125 000 32 × 2 = 0 + 0.656 250 000 64;
  • 7) 0.656 250 000 64 × 2 = 1 + 0.312 500 001 28;
  • 8) 0.312 500 001 28 × 2 = 0 + 0.625 000 002 56;
  • 9) 0.625 000 002 56 × 2 = 1 + 0.250 000 005 12;
  • 10) 0.250 000 005 12 × 2 = 0 + 0.500 000 010 24;
  • 11) 0.500 000 010 24 × 2 = 1 + 0.000 000 020 48;
  • 12) 0.000 000 020 48 × 2 = 0 + 0.000 000 040 96;
  • 13) 0.000 000 040 96 × 2 = 0 + 0.000 000 081 92;
  • 14) 0.000 000 081 92 × 2 = 0 + 0.000 000 163 84;
  • 15) 0.000 000 163 84 × 2 = 0 + 0.000 000 327 68;
  • 16) 0.000 000 327 68 × 2 = 0 + 0.000 000 655 36;
  • 17) 0.000 000 655 36 × 2 = 0 + 0.000 001 310 72;
  • 18) 0.000 001 310 72 × 2 = 0 + 0.000 002 621 44;
  • 19) 0.000 002 621 44 × 2 = 0 + 0.000 005 242 88;
  • 20) 0.000 005 242 88 × 2 = 0 + 0.000 010 485 76;
  • 21) 0.000 010 485 76 × 2 = 0 + 0.000 020 971 52;
  • 22) 0.000 020 971 52 × 2 = 0 + 0.000 041 943 04;
  • 23) 0.000 041 943 04 × 2 = 0 + 0.000 083 886 08;
  • 24) 0.000 083 886 08 × 2 = 0 + 0.000 167 772 16;
  • 25) 0.000 167 772 16 × 2 = 0 + 0.000 335 544 32;
  • 26) 0.000 335 544 32 × 2 = 0 + 0.000 671 088 64;
  • 27) 0.000 671 088 64 × 2 = 0 + 0.001 342 177 28;
  • 28) 0.001 342 177 28 × 2 = 0 + 0.002 684 354 56;
  • 29) 0.002 684 354 56 × 2 = 0 + 0.005 368 709 12;
  • 30) 0.005 368 709 12 × 2 = 0 + 0.010 737 418 24;
  • 31) 0.010 737 418 24 × 2 = 0 + 0.021 474 836 48;
  • 32) 0.021 474 836 48 × 2 = 0 + 0.042 949 672 96;
  • 33) 0.042 949 672 96 × 2 = 0 + 0.085 899 345 92;
  • 34) 0.085 899 345 92 × 2 = 0 + 0.171 798 691 84;
  • 35) 0.171 798 691 84 × 2 = 0 + 0.343 597 383 68;
  • 36) 0.343 597 383 68 × 2 = 0 + 0.687 194 767 36;
  • 37) 0.687 194 767 36 × 2 = 1 + 0.374 389 534 72;
  • 38) 0.374 389 534 72 × 2 = 0 + 0.748 779 069 44;
  • 39) 0.748 779 069 44 × 2 = 1 + 0.497 558 138 88;
  • 40) 0.497 558 138 88 × 2 = 0 + 0.995 116 277 76;
  • 41) 0.995 116 277 76 × 2 = 1 + 0.990 232 555 52;
  • 42) 0.990 232 555 52 × 2 = 1 + 0.980 465 111 04;
  • 43) 0.980 465 111 04 × 2 = 1 + 0.960 930 222 08;
  • 44) 0.960 930 222 08 × 2 = 1 + 0.921 860 444 16;
  • 45) 0.921 860 444 16 × 2 = 1 + 0.843 720 888 32;
  • 46) 0.843 720 888 32 × 2 = 1 + 0.687 441 776 64;
  • 47) 0.687 441 776 64 × 2 = 1 + 0.374 883 553 28;
  • 48) 0.374 883 553 28 × 2 = 0 + 0.749 767 106 56;
  • 49) 0.749 767 106 56 × 2 = 1 + 0.499 534 213 12;
  • 50) 0.499 534 213 12 × 2 = 0 + 0.999 068 426 24;
  • 51) 0.999 068 426 24 × 2 = 1 + 0.998 136 852 48;
  • 52) 0.998 136 852 48 × 2 = 1 + 0.996 273 704 96;
  • 53) 0.996 273 704 96 × 2 = 1 + 0.992 547 409 92;

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...)


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:


0.666 503 906 26(10) =


0.1010 1010 1010 0000 0000 0000 0000 0000 0000 1010 1111 1110 1011 1(2)


5. Positive number before normalization:

0.666 503 906 26(10) =


0.1010 1010 1010 0000 0000 0000 0000 0000 0000 1010 1111 1110 1011 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 1 positions to the right, so that only one non zero digit remains to the left of it:


0.666 503 906 26(10) =


0.1010 1010 1010 0000 0000 0000 0000 0000 0000 1010 1111 1110 1011 1(2) =


0.1010 1010 1010 0000 0000 0000 0000 0000 0000 1010 1111 1110 1011 1(2) × 20 =


1.0101 0101 0100 0000 0000 0000 0000 0000 0001 0101 1111 1101 0111(2) × 2-1


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): -1


Mantissa (not normalized):
1.0101 0101 0100 0000 0000 0000 0000 0000 0001 0101 1111 1101 0111


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


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


(-1 + 1 023)(10) =


1 022(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;
  • 1 022 ÷ 2 = 511 + 0;
  • 511 ÷ 2 = 255 + 1;
  • 255 ÷ 2 = 127 + 1;
  • 127 ÷ 2 = 63 + 1;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 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) =


1022(10) =


011 1111 1110(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, only if necessary (not the case here).


Mantissa (normalized) =


1. 0101 0101 0100 0000 0000 0000 0000 0000 0001 0101 1111 1101 0111 =


0101 0101 0100 0000 0000 0000 0000 0000 0001 0101 1111 1101 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) =
011 1111 1110


Mantissa (52 bits) =
0101 0101 0100 0000 0000 0000 0000 0000 0001 0101 1111 1101 0111


The base ten decimal number 0.666 503 906 26 converted and written in 64 bit double precision IEEE 754 binary floating point representation:
0 - 011 1111 1110 - 0101 0101 0100 0000 0000 0000 0000 0000 0001 0101 1111 1101 0111

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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