64bit IEEE 754: Decimal ↗ Double Precision Floating Point Binary: 8 564.363 636 36 Convert the Number to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From a Base Ten Decimal System Number

Number 8 564.363 636 36(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: 8 564.
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;
  • 8 564 ÷ 2 = 4 282 + 0;
  • 4 282 ÷ 2 = 2 141 + 0;
  • 2 141 ÷ 2 = 1 070 + 1;
  • 1 070 ÷ 2 = 535 + 0;
  • 535 ÷ 2 = 267 + 1;
  • 267 ÷ 2 = 133 + 1;
  • 133 ÷ 2 = 66 + 1;
  • 66 ÷ 2 = 33 + 0;
  • 33 ÷ 2 = 16 + 1;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 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.


8 564(10) =


10 0001 0111 0100(2)


3. Convert to binary (base 2) the fractional part: 0.363 636 36.

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) 0.363 636 36 × 2 = 0 + 0.727 272 72;
  • 2) 0.727 272 72 × 2 = 1 + 0.454 545 44;
  • 3) 0.454 545 44 × 2 = 0 + 0.909 090 88;
  • 4) 0.909 090 88 × 2 = 1 + 0.818 181 76;
  • 5) 0.818 181 76 × 2 = 1 + 0.636 363 52;
  • 6) 0.636 363 52 × 2 = 1 + 0.272 727 04;
  • 7) 0.272 727 04 × 2 = 0 + 0.545 454 08;
  • 8) 0.545 454 08 × 2 = 1 + 0.090 908 16;
  • 9) 0.090 908 16 × 2 = 0 + 0.181 816 32;
  • 10) 0.181 816 32 × 2 = 0 + 0.363 632 64;
  • 11) 0.363 632 64 × 2 = 0 + 0.727 265 28;
  • 12) 0.727 265 28 × 2 = 1 + 0.454 530 56;
  • 13) 0.454 530 56 × 2 = 0 + 0.909 061 12;
  • 14) 0.909 061 12 × 2 = 1 + 0.818 122 24;
  • 15) 0.818 122 24 × 2 = 1 + 0.636 244 48;
  • 16) 0.636 244 48 × 2 = 1 + 0.272 488 96;
  • 17) 0.272 488 96 × 2 = 0 + 0.544 977 92;
  • 18) 0.544 977 92 × 2 = 1 + 0.089 955 84;
  • 19) 0.089 955 84 × 2 = 0 + 0.179 911 68;
  • 20) 0.179 911 68 × 2 = 0 + 0.359 823 36;
  • 21) 0.359 823 36 × 2 = 0 + 0.719 646 72;
  • 22) 0.719 646 72 × 2 = 1 + 0.439 293 44;
  • 23) 0.439 293 44 × 2 = 0 + 0.878 586 88;
  • 24) 0.878 586 88 × 2 = 1 + 0.757 173 76;
  • 25) 0.757 173 76 × 2 = 1 + 0.514 347 52;
  • 26) 0.514 347 52 × 2 = 1 + 0.028 695 04;
  • 27) 0.028 695 04 × 2 = 0 + 0.057 390 08;
  • 28) 0.057 390 08 × 2 = 0 + 0.114 780 16;
  • 29) 0.114 780 16 × 2 = 0 + 0.229 560 32;
  • 30) 0.229 560 32 × 2 = 0 + 0.459 120 64;
  • 31) 0.459 120 64 × 2 = 0 + 0.918 241 28;
  • 32) 0.918 241 28 × 2 = 1 + 0.836 482 56;
  • 33) 0.836 482 56 × 2 = 1 + 0.672 965 12;
  • 34) 0.672 965 12 × 2 = 1 + 0.345 930 24;
  • 35) 0.345 930 24 × 2 = 0 + 0.691 860 48;
  • 36) 0.691 860 48 × 2 = 1 + 0.383 720 96;
  • 37) 0.383 720 96 × 2 = 0 + 0.767 441 92;
  • 38) 0.767 441 92 × 2 = 1 + 0.534 883 84;
  • 39) 0.534 883 84 × 2 = 1 + 0.069 767 68;
  • 40) 0.069 767 68 × 2 = 0 + 0.139 535 36;
  • 41) 0.139 535 36 × 2 = 0 + 0.279 070 72;
  • 42) 0.279 070 72 × 2 = 0 + 0.558 141 44;
  • 43) 0.558 141 44 × 2 = 1 + 0.116 282 88;
  • 44) 0.116 282 88 × 2 = 0 + 0.232 565 76;
  • 45) 0.232 565 76 × 2 = 0 + 0.465 131 52;
  • 46) 0.465 131 52 × 2 = 0 + 0.930 263 04;
  • 47) 0.930 263 04 × 2 = 1 + 0.860 526 08;
  • 48) 0.860 526 08 × 2 = 1 + 0.721 052 16;
  • 49) 0.721 052 16 × 2 = 1 + 0.442 104 32;
  • 50) 0.442 104 32 × 2 = 0 + 0.884 208 64;
  • 51) 0.884 208 64 × 2 = 1 + 0.768 417 28;
  • 52) 0.768 417 28 × 2 = 1 + 0.536 834 56;
  • 53) 0.536 834 56 × 2 = 1 + 0.073 669 12;

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:


0.363 636 36(10) =


0.0101 1101 0001 0111 0100 0101 1100 0001 1101 0110 0010 0011 1011 1(2)


5. Positive number before normalization:

8 564.363 636 36(10) =


10 0001 0111 0100.0101 1101 0001 0111 0100 0101 1100 0001 1101 0110 0010 0011 1011 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:


8 564.363 636 36(10) =


10 0001 0111 0100.0101 1101 0001 0111 0100 0101 1100 0001 1101 0110 0010 0011 1011 1(2) =


10 0001 0111 0100.0101 1101 0001 0111 0100 0101 1100 0001 1101 0110 0010 0011 1011 1(2) × 20 =


1.0000 1011 1010 0010 1110 1000 1011 1010 0010 1110 0000 1110 1011 0001 0001 1101 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):
1.0000 1011 1010 0010 1110 1000 1011 1010 0010 1110 0000 1110 1011 0001 0001 1101 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. 0000 1011 1010 0010 1110 1000 1011 1010 0010 1110 0000 1110 1011 00 0100 0111 0111 =


0000 1011 1010 0010 1110 1000 1011 1010 0010 1110 0000 1110 1011


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) =
0000 1011 1010 0010 1110 1000 1011 1010 0010 1110 0000 1110 1011


The base ten decimal number 8 564.363 636 36 converted and written in 64 bit double precision IEEE 754 binary floating point representation:
0 - 100 0000 1100 - 0000 1011 1010 0010 1110 1000 1011 1010 0010 1110 0000 1110 1011

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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