64bit IEEE 754: Decimal ↗ Double Precision Floating Point Binary: 908 803 936.001 356 4 Convert the Number to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From a Base Ten Decimal System Number

Number 908 803 936.001 356 4(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: 908 803 936.
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;
  • 908 803 936 ÷ 2 = 454 401 968 + 0;
  • 454 401 968 ÷ 2 = 227 200 984 + 0;
  • 227 200 984 ÷ 2 = 113 600 492 + 0;
  • 113 600 492 ÷ 2 = 56 800 246 + 0;
  • 56 800 246 ÷ 2 = 28 400 123 + 0;
  • 28 400 123 ÷ 2 = 14 200 061 + 1;
  • 14 200 061 ÷ 2 = 7 100 030 + 1;
  • 7 100 030 ÷ 2 = 3 550 015 + 0;
  • 3 550 015 ÷ 2 = 1 775 007 + 1;
  • 1 775 007 ÷ 2 = 887 503 + 1;
  • 887 503 ÷ 2 = 443 751 + 1;
  • 443 751 ÷ 2 = 221 875 + 1;
  • 221 875 ÷ 2 = 110 937 + 1;
  • 110 937 ÷ 2 = 55 468 + 1;
  • 55 468 ÷ 2 = 27 734 + 0;
  • 27 734 ÷ 2 = 13 867 + 0;
  • 13 867 ÷ 2 = 6 933 + 1;
  • 6 933 ÷ 2 = 3 466 + 1;
  • 3 466 ÷ 2 = 1 733 + 0;
  • 1 733 ÷ 2 = 866 + 1;
  • 866 ÷ 2 = 433 + 0;
  • 433 ÷ 2 = 216 + 1;
  • 216 ÷ 2 = 108 + 0;
  • 108 ÷ 2 = 54 + 0;
  • 54 ÷ 2 = 27 + 0;
  • 27 ÷ 2 = 13 + 1;
  • 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.


908 803 936(10) =


11 0110 0010 1011 0011 1111 0110 0000(2)


3. Convert to binary (base 2) the fractional part: 0.001 356 4.

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) 0.001 356 4 × 2 = 0 + 0.002 712 8;
  • 2) 0.002 712 8 × 2 = 0 + 0.005 425 6;
  • 3) 0.005 425 6 × 2 = 0 + 0.010 851 2;
  • 4) 0.010 851 2 × 2 = 0 + 0.021 702 4;
  • 5) 0.021 702 4 × 2 = 0 + 0.043 404 8;
  • 6) 0.043 404 8 × 2 = 0 + 0.086 809 6;
  • 7) 0.086 809 6 × 2 = 0 + 0.173 619 2;
  • 8) 0.173 619 2 × 2 = 0 + 0.347 238 4;
  • 9) 0.347 238 4 × 2 = 0 + 0.694 476 8;
  • 10) 0.694 476 8 × 2 = 1 + 0.388 953 6;
  • 11) 0.388 953 6 × 2 = 0 + 0.777 907 2;
  • 12) 0.777 907 2 × 2 = 1 + 0.555 814 4;
  • 13) 0.555 814 4 × 2 = 1 + 0.111 628 8;
  • 14) 0.111 628 8 × 2 = 0 + 0.223 257 6;
  • 15) 0.223 257 6 × 2 = 0 + 0.446 515 2;
  • 16) 0.446 515 2 × 2 = 0 + 0.893 030 4;
  • 17) 0.893 030 4 × 2 = 1 + 0.786 060 8;
  • 18) 0.786 060 8 × 2 = 1 + 0.572 121 6;
  • 19) 0.572 121 6 × 2 = 1 + 0.144 243 2;
  • 20) 0.144 243 2 × 2 = 0 + 0.288 486 4;
  • 21) 0.288 486 4 × 2 = 0 + 0.576 972 8;
  • 22) 0.576 972 8 × 2 = 1 + 0.153 945 6;
  • 23) 0.153 945 6 × 2 = 0 + 0.307 891 2;
  • 24) 0.307 891 2 × 2 = 0 + 0.615 782 4;
  • 25) 0.615 782 4 × 2 = 1 + 0.231 564 8;
  • 26) 0.231 564 8 × 2 = 0 + 0.463 129 6;
  • 27) 0.463 129 6 × 2 = 0 + 0.926 259 2;
  • 28) 0.926 259 2 × 2 = 1 + 0.852 518 4;
  • 29) 0.852 518 4 × 2 = 1 + 0.705 036 8;
  • 30) 0.705 036 8 × 2 = 1 + 0.410 073 6;
  • 31) 0.410 073 6 × 2 = 0 + 0.820 147 2;
  • 32) 0.820 147 2 × 2 = 1 + 0.640 294 4;
  • 33) 0.640 294 4 × 2 = 1 + 0.280 588 8;
  • 34) 0.280 588 8 × 2 = 0 + 0.561 177 6;
  • 35) 0.561 177 6 × 2 = 1 + 0.122 355 2;
  • 36) 0.122 355 2 × 2 = 0 + 0.244 710 4;
  • 37) 0.244 710 4 × 2 = 0 + 0.489 420 8;
  • 38) 0.489 420 8 × 2 = 0 + 0.978 841 6;
  • 39) 0.978 841 6 × 2 = 1 + 0.957 683 2;
  • 40) 0.957 683 2 × 2 = 1 + 0.915 366 4;
  • 41) 0.915 366 4 × 2 = 1 + 0.830 732 8;
  • 42) 0.830 732 8 × 2 = 1 + 0.661 465 6;
  • 43) 0.661 465 6 × 2 = 1 + 0.322 931 2;
  • 44) 0.322 931 2 × 2 = 0 + 0.645 862 4;
  • 45) 0.645 862 4 × 2 = 1 + 0.291 724 8;
  • 46) 0.291 724 8 × 2 = 0 + 0.583 449 6;
  • 47) 0.583 449 6 × 2 = 1 + 0.166 899 2;
  • 48) 0.166 899 2 × 2 = 0 + 0.333 798 4;
  • 49) 0.333 798 4 × 2 = 0 + 0.667 596 8;
  • 50) 0.667 596 8 × 2 = 1 + 0.335 193 6;
  • 51) 0.335 193 6 × 2 = 0 + 0.670 387 2;
  • 52) 0.670 387 2 × 2 = 1 + 0.340 774 4;
  • 53) 0.340 774 4 × 2 = 0 + 0.681 548 8;

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:


0.001 356 4(10) =


0.0000 0000 0101 1000 1110 0100 1001 1101 1010 0011 1110 1010 0101 0(2)


5. Positive number before normalization:

908 803 936.001 356 4(10) =


11 0110 0010 1011 0011 1111 0110 0000.0000 0000 0101 1000 1110 0100 1001 1101 1010 0011 1110 1010 0101 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 29 positions to the left, so that only one non zero digit remains to the left of it:


908 803 936.001 356 4(10) =


11 0110 0010 1011 0011 1111 0110 0000.0000 0000 0101 1000 1110 0100 1001 1101 1010 0011 1110 1010 0101 0(2) =


11 0110 0010 1011 0011 1111 0110 0000.0000 0000 0101 1000 1110 0100 1001 1101 1010 0011 1110 1010 0101 0(2) × 20 =


1.1011 0001 0101 1001 1111 1011 0000 0000 0000 0010 1100 0111 0010 0100 1110 1101 0001 1111 0101 0010 10(2) × 229


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): 29


Mantissa (not normalized):
1.1011 0001 0101 1001 1111 1011 0000 0000 0000 0010 1100 0111 0010 0100 1110 1101 0001 1111 0101 0010 10


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


29 + 2(11-1) - 1 =


(29 + 1 023)(10) =


1 052(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;
  • 1 052 ÷ 2 = 526 + 0;
  • 526 ÷ 2 = 263 + 0;
  • 263 ÷ 2 = 131 + 1;
  • 131 ÷ 2 = 65 + 1;
  • 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) =


1052(10) =


100 0001 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. 1011 0001 0101 1001 1111 1011 0000 0000 0000 0010 1100 0111 0010 01 0011 1011 0100 0111 1101 0100 1010 =


1011 0001 0101 1001 1111 1011 0000 0000 0000 0010 1100 0111 0010


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 1100


Mantissa (52 bits) =
1011 0001 0101 1001 1111 1011 0000 0000 0000 0010 1100 0111 0010


The base ten decimal number 908 803 936.001 356 4 converted and written in 64 bit double precision IEEE 754 binary floating point representation:
0 - 100 0001 1100 - 1011 0001 0101 1001 1111 1011 0000 0000 0000 0010 1100 0111 0010

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

Number -84 593 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 19 17:26 UTC (GMT)
Number 0.967 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 19 17:26 UTC (GMT)
Number -101 010 110 109 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 19 17:26 UTC (GMT)
Number 8.129 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 19 17:26 UTC (GMT)
Number -5 555.625 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 19 17:25 UTC (GMT)
Number 1 052 046 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 19 17:25 UTC (GMT)
Number 62 763 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 19 17:25 UTC (GMT)
Number 0.265 626 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 19 17:25 UTC (GMT)
Number -740 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 19 17:25 UTC (GMT)
Number 284.55 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 19 17:24 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