0.010 109 17 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.010 109 17(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
0.010 109 17(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: 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: 0.010 109 17.

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) 0.010 109 17 × 2 = 0 + 0.020 218 34;
  • 2) 0.020 218 34 × 2 = 0 + 0.040 436 68;
  • 3) 0.040 436 68 × 2 = 0 + 0.080 873 36;
  • 4) 0.080 873 36 × 2 = 0 + 0.161 746 72;
  • 5) 0.161 746 72 × 2 = 0 + 0.323 493 44;
  • 6) 0.323 493 44 × 2 = 0 + 0.646 986 88;
  • 7) 0.646 986 88 × 2 = 1 + 0.293 973 76;
  • 8) 0.293 973 76 × 2 = 0 + 0.587 947 52;
  • 9) 0.587 947 52 × 2 = 1 + 0.175 895 04;
  • 10) 0.175 895 04 × 2 = 0 + 0.351 790 08;
  • 11) 0.351 790 08 × 2 = 0 + 0.703 580 16;
  • 12) 0.703 580 16 × 2 = 1 + 0.407 160 32;
  • 13) 0.407 160 32 × 2 = 0 + 0.814 320 64;
  • 14) 0.814 320 64 × 2 = 1 + 0.628 641 28;
  • 15) 0.628 641 28 × 2 = 1 + 0.257 282 56;
  • 16) 0.257 282 56 × 2 = 0 + 0.514 565 12;
  • 17) 0.514 565 12 × 2 = 1 + 0.029 130 24;
  • 18) 0.029 130 24 × 2 = 0 + 0.058 260 48;
  • 19) 0.058 260 48 × 2 = 0 + 0.116 520 96;
  • 20) 0.116 520 96 × 2 = 0 + 0.233 041 92;
  • 21) 0.233 041 92 × 2 = 0 + 0.466 083 84;
  • 22) 0.466 083 84 × 2 = 0 + 0.932 167 68;
  • 23) 0.932 167 68 × 2 = 1 + 0.864 335 36;
  • 24) 0.864 335 36 × 2 = 1 + 0.728 670 72;
  • 25) 0.728 670 72 × 2 = 1 + 0.457 341 44;
  • 26) 0.457 341 44 × 2 = 0 + 0.914 682 88;
  • 27) 0.914 682 88 × 2 = 1 + 0.829 365 76;
  • 28) 0.829 365 76 × 2 = 1 + 0.658 731 52;
  • 29) 0.658 731 52 × 2 = 1 + 0.317 463 04;
  • 30) 0.317 463 04 × 2 = 0 + 0.634 926 08;
  • 31) 0.634 926 08 × 2 = 1 + 0.269 852 16;
  • 32) 0.269 852 16 × 2 = 0 + 0.539 704 32;
  • 33) 0.539 704 32 × 2 = 1 + 0.079 408 64;
  • 34) 0.079 408 64 × 2 = 0 + 0.158 817 28;
  • 35) 0.158 817 28 × 2 = 0 + 0.317 634 56;
  • 36) 0.317 634 56 × 2 = 0 + 0.635 269 12;
  • 37) 0.635 269 12 × 2 = 1 + 0.270 538 24;
  • 38) 0.270 538 24 × 2 = 0 + 0.541 076 48;
  • 39) 0.541 076 48 × 2 = 1 + 0.082 152 96;
  • 40) 0.082 152 96 × 2 = 0 + 0.164 305 92;
  • 41) 0.164 305 92 × 2 = 0 + 0.328 611 84;
  • 42) 0.328 611 84 × 2 = 0 + 0.657 223 68;
  • 43) 0.657 223 68 × 2 = 1 + 0.314 447 36;
  • 44) 0.314 447 36 × 2 = 0 + 0.628 894 72;
  • 45) 0.628 894 72 × 2 = 1 + 0.257 789 44;
  • 46) 0.257 789 44 × 2 = 0 + 0.515 578 88;
  • 47) 0.515 578 88 × 2 = 1 + 0.031 157 76;
  • 48) 0.031 157 76 × 2 = 0 + 0.062 315 52;
  • 49) 0.062 315 52 × 2 = 0 + 0.124 631 04;
  • 50) 0.124 631 04 × 2 = 0 + 0.249 262 08;
  • 51) 0.249 262 08 × 2 = 0 + 0.498 524 16;
  • 52) 0.498 524 16 × 2 = 0 + 0.997 048 32;
  • 53) 0.997 048 32 × 2 = 1 + 0.994 096 64;
  • 54) 0.994 096 64 × 2 = 1 + 0.988 193 28;
  • 55) 0.988 193 28 × 2 = 1 + 0.976 386 56;
  • 56) 0.976 386 56 × 2 = 1 + 0.952 773 12;
  • 57) 0.952 773 12 × 2 = 1 + 0.905 546 24;
  • 58) 0.905 546 24 × 2 = 1 + 0.811 092 48;
  • 59) 0.811 092 48 × 2 = 1 + 0.622 184 96;

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:


0.010 109 17(10) =


0.0000 0010 1001 0110 1000 0011 1011 1010 1000 1010 0010 1010 0000 1111 111(2)

5. Positive number before normalization:

0.010 109 17(10) =


0.0000 0010 1001 0110 1000 0011 1011 1010 1000 1010 0010 1010 0000 1111 111(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 7 positions to the right, so that only one non zero digit remains to the left of it:


0.010 109 17(10) =


0.0000 0010 1001 0110 1000 0011 1011 1010 1000 1010 0010 1010 0000 1111 111(2) =


0.0000 0010 1001 0110 1000 0011 1011 1010 1000 1010 0010 1010 0000 1111 111(2) × 20 =


1.0100 1011 0100 0001 1101 1101 0100 0101 0001 0101 0000 0111 1111(2) × 2-7


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): -7


Mantissa (not normalized):
1.0100 1011 0100 0001 1101 1101 0100 0101 0001 0101 0000 0111 1111


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


-7 + 2(11-1) - 1 =


(-7 + 1 023)(10) =


1 016(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;
  • 1 016 ÷ 2 = 508 + 0;
  • 508 ÷ 2 = 254 + 0;
  • 254 ÷ 2 = 127 + 0;
  • 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) =


1016(10) =


011 1111 1000(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. 0100 1011 0100 0001 1101 1101 0100 0101 0001 0101 0000 0111 1111 =


0100 1011 0100 0001 1101 1101 0100 0101 0001 0101 0000 0111 1111


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 1000


Mantissa (52 bits) =
0100 1011 0100 0001 1101 1101 0100 0101 0001 0101 0000 0111 1111


Decimal number 0.010 109 17 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 011 1111 1000 - 0100 1011 0100 0001 1101 1101 0100 0101 0001 0101 0000 0111 1111


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