64bit IEEE 754: Decimal ↗ Double Precision Floating Point Binary: 22 313.037 89 Convert the Number to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From a Base Ten Decimal System Number

Number 22 313.037 89(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: 22 313.
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;
  • 22 313 ÷ 2 = 11 156 + 1;
  • 11 156 ÷ 2 = 5 578 + 0;
  • 5 578 ÷ 2 = 2 789 + 0;
  • 2 789 ÷ 2 = 1 394 + 1;
  • 1 394 ÷ 2 = 697 + 0;
  • 697 ÷ 2 = 348 + 1;
  • 348 ÷ 2 = 174 + 0;
  • 174 ÷ 2 = 87 + 0;
  • 87 ÷ 2 = 43 + 1;
  • 43 ÷ 2 = 21 + 1;
  • 21 ÷ 2 = 10 + 1;
  • 10 ÷ 2 = 5 + 0;
  • 5 ÷ 2 = 2 + 1;
  • 2 ÷ 2 = 1 + 0;
  • 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.


22 313(10) =


101 0111 0010 1001(2)


3. Convert to binary (base 2) the fractional part: 0.037 89.

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) 0.037 89 × 2 = 0 + 0.075 78;
  • 2) 0.075 78 × 2 = 0 + 0.151 56;
  • 3) 0.151 56 × 2 = 0 + 0.303 12;
  • 4) 0.303 12 × 2 = 0 + 0.606 24;
  • 5) 0.606 24 × 2 = 1 + 0.212 48;
  • 6) 0.212 48 × 2 = 0 + 0.424 96;
  • 7) 0.424 96 × 2 = 0 + 0.849 92;
  • 8) 0.849 92 × 2 = 1 + 0.699 84;
  • 9) 0.699 84 × 2 = 1 + 0.399 68;
  • 10) 0.399 68 × 2 = 0 + 0.799 36;
  • 11) 0.799 36 × 2 = 1 + 0.598 72;
  • 12) 0.598 72 × 2 = 1 + 0.197 44;
  • 13) 0.197 44 × 2 = 0 + 0.394 88;
  • 14) 0.394 88 × 2 = 0 + 0.789 76;
  • 15) 0.789 76 × 2 = 1 + 0.579 52;
  • 16) 0.579 52 × 2 = 1 + 0.159 04;
  • 17) 0.159 04 × 2 = 0 + 0.318 08;
  • 18) 0.318 08 × 2 = 0 + 0.636 16;
  • 19) 0.636 16 × 2 = 1 + 0.272 32;
  • 20) 0.272 32 × 2 = 0 + 0.544 64;
  • 21) 0.544 64 × 2 = 1 + 0.089 28;
  • 22) 0.089 28 × 2 = 0 + 0.178 56;
  • 23) 0.178 56 × 2 = 0 + 0.357 12;
  • 24) 0.357 12 × 2 = 0 + 0.714 24;
  • 25) 0.714 24 × 2 = 1 + 0.428 48;
  • 26) 0.428 48 × 2 = 0 + 0.856 96;
  • 27) 0.856 96 × 2 = 1 + 0.713 92;
  • 28) 0.713 92 × 2 = 1 + 0.427 84;
  • 29) 0.427 84 × 2 = 0 + 0.855 68;
  • 30) 0.855 68 × 2 = 1 + 0.711 36;
  • 31) 0.711 36 × 2 = 1 + 0.422 72;
  • 32) 0.422 72 × 2 = 0 + 0.845 44;
  • 33) 0.845 44 × 2 = 1 + 0.690 88;
  • 34) 0.690 88 × 2 = 1 + 0.381 76;
  • 35) 0.381 76 × 2 = 0 + 0.763 52;
  • 36) 0.763 52 × 2 = 1 + 0.527 04;
  • 37) 0.527 04 × 2 = 1 + 0.054 08;
  • 38) 0.054 08 × 2 = 0 + 0.108 16;
  • 39) 0.108 16 × 2 = 0 + 0.216 32;
  • 40) 0.216 32 × 2 = 0 + 0.432 64;
  • 41) 0.432 64 × 2 = 0 + 0.865 28;
  • 42) 0.865 28 × 2 = 1 + 0.730 56;
  • 43) 0.730 56 × 2 = 1 + 0.461 12;
  • 44) 0.461 12 × 2 = 0 + 0.922 24;
  • 45) 0.922 24 × 2 = 1 + 0.844 48;
  • 46) 0.844 48 × 2 = 1 + 0.688 96;
  • 47) 0.688 96 × 2 = 1 + 0.377 92;
  • 48) 0.377 92 × 2 = 0 + 0.755 84;
  • 49) 0.755 84 × 2 = 1 + 0.511 68;
  • 50) 0.511 68 × 2 = 1 + 0.023 36;
  • 51) 0.023 36 × 2 = 0 + 0.046 72;
  • 52) 0.046 72 × 2 = 0 + 0.093 44;
  • 53) 0.093 44 × 2 = 0 + 0.186 88;

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:


0.037 89(10) =


0.0000 1001 1011 0011 0010 1000 1011 0110 1101 1000 0110 1110 1100 0(2)


5. Positive number before normalization:

22 313.037 89(10) =


101 0111 0010 1001.0000 1001 1011 0011 0010 1000 1011 0110 1101 1000 0110 1110 1100 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 14 positions to the left, so that only one non zero digit remains to the left of it:


22 313.037 89(10) =


101 0111 0010 1001.0000 1001 1011 0011 0010 1000 1011 0110 1101 1000 0110 1110 1100 0(2) =


101 0111 0010 1001.0000 1001 1011 0011 0010 1000 1011 0110 1101 1000 0110 1110 1100 0(2) × 20 =


1.0101 1100 1010 0100 0010 0110 1100 1100 1010 0010 1101 1011 0110 0001 1011 1011 000(2) × 214


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): 14


Mantissa (not normalized):
1.0101 1100 1010 0100 0010 0110 1100 1100 1010 0010 1101 1011 0110 0001 1011 1011 000


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


14 + 2(11-1) - 1 =


(14 + 1 023)(10) =


1 037(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;
  • 1 037 ÷ 2 = 518 + 1;
  • 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) =


1037(10) =


100 0000 1101(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. 0101 1100 1010 0100 0010 0110 1100 1100 1010 0010 1101 1011 0110 000 1101 1101 1000 =


0101 1100 1010 0100 0010 0110 1100 1100 1010 0010 1101 1011 0110


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 1101


Mantissa (52 bits) =
0101 1100 1010 0100 0010 0110 1100 1100 1010 0010 1101 1011 0110


The base ten decimal number 22 313.037 89 converted and written in 64 bit double precision IEEE 754 binary floating point representation:
0 - 100 0000 1101 - 0101 1100 1010 0100 0010 0110 1100 1100 1010 0010 1101 1011 0110

The latest decimal numbers converted from base ten to 64 bit double precision IEEE 754 floating point binary standard representation

Number 1 301 116 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 18 12:07 UTC (GMT)
Number 79 865 123 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 18 12:07 UTC (GMT)
Number -20 971 523 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 18 12:07 UTC (GMT)
Number -2 456.15 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 18 12:07 UTC (GMT)
Number -3 611 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 18 12:07 UTC (GMT)
Number 243 154.126 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 18 12:07 UTC (GMT)
Number 888 861 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 18 12:07 UTC (GMT)
Number 126.718 281 82 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 18 12:06 UTC (GMT)
Number 63.4 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 18 12:06 UTC (GMT)
Number -31 293 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 18 12:06 UTC (GMT)
All base ten decimal numbers converted to 64 bit double precision IEEE 754 binary floating point

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