512.160 000 000 000 82 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 512.160 000 000 000 82(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
512.160 000 000 000 82(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: 512.
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;
  • 512 ÷ 2 = 256 + 0;
  • 256 ÷ 2 = 128 + 0;
  • 128 ÷ 2 = 64 + 0;
  • 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;

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.

512(10) =


10 0000 0000(2)


3. Convert to binary (base 2) the fractional part: 0.160 000 000 000 82.

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) 0.160 000 000 000 82 × 2 = 0 + 0.320 000 000 001 64;
  • 2) 0.320 000 000 001 64 × 2 = 0 + 0.640 000 000 003 28;
  • 3) 0.640 000 000 003 28 × 2 = 1 + 0.280 000 000 006 56;
  • 4) 0.280 000 000 006 56 × 2 = 0 + 0.560 000 000 013 12;
  • 5) 0.560 000 000 013 12 × 2 = 1 + 0.120 000 000 026 24;
  • 6) 0.120 000 000 026 24 × 2 = 0 + 0.240 000 000 052 48;
  • 7) 0.240 000 000 052 48 × 2 = 0 + 0.480 000 000 104 96;
  • 8) 0.480 000 000 104 96 × 2 = 0 + 0.960 000 000 209 92;
  • 9) 0.960 000 000 209 92 × 2 = 1 + 0.920 000 000 419 84;
  • 10) 0.920 000 000 419 84 × 2 = 1 + 0.840 000 000 839 68;
  • 11) 0.840 000 000 839 68 × 2 = 1 + 0.680 000 001 679 36;
  • 12) 0.680 000 001 679 36 × 2 = 1 + 0.360 000 003 358 72;
  • 13) 0.360 000 003 358 72 × 2 = 0 + 0.720 000 006 717 44;
  • 14) 0.720 000 006 717 44 × 2 = 1 + 0.440 000 013 434 88;
  • 15) 0.440 000 013 434 88 × 2 = 0 + 0.880 000 026 869 76;
  • 16) 0.880 000 026 869 76 × 2 = 1 + 0.760 000 053 739 52;
  • 17) 0.760 000 053 739 52 × 2 = 1 + 0.520 000 107 479 04;
  • 18) 0.520 000 107 479 04 × 2 = 1 + 0.040 000 214 958 08;
  • 19) 0.040 000 214 958 08 × 2 = 0 + 0.080 000 429 916 16;
  • 20) 0.080 000 429 916 16 × 2 = 0 + 0.160 000 859 832 32;
  • 21) 0.160 000 859 832 32 × 2 = 0 + 0.320 001 719 664 64;
  • 22) 0.320 001 719 664 64 × 2 = 0 + 0.640 003 439 329 28;
  • 23) 0.640 003 439 329 28 × 2 = 1 + 0.280 006 878 658 56;
  • 24) 0.280 006 878 658 56 × 2 = 0 + 0.560 013 757 317 12;
  • 25) 0.560 013 757 317 12 × 2 = 1 + 0.120 027 514 634 24;
  • 26) 0.120 027 514 634 24 × 2 = 0 + 0.240 055 029 268 48;
  • 27) 0.240 055 029 268 48 × 2 = 0 + 0.480 110 058 536 96;
  • 28) 0.480 110 058 536 96 × 2 = 0 + 0.960 220 117 073 92;
  • 29) 0.960 220 117 073 92 × 2 = 1 + 0.920 440 234 147 84;
  • 30) 0.920 440 234 147 84 × 2 = 1 + 0.840 880 468 295 68;
  • 31) 0.840 880 468 295 68 × 2 = 1 + 0.681 760 936 591 36;
  • 32) 0.681 760 936 591 36 × 2 = 1 + 0.363 521 873 182 72;
  • 33) 0.363 521 873 182 72 × 2 = 0 + 0.727 043 746 365 44;
  • 34) 0.727 043 746 365 44 × 2 = 1 + 0.454 087 492 730 88;
  • 35) 0.454 087 492 730 88 × 2 = 0 + 0.908 174 985 461 76;
  • 36) 0.908 174 985 461 76 × 2 = 1 + 0.816 349 970 923 52;
  • 37) 0.816 349 970 923 52 × 2 = 1 + 0.632 699 941 847 04;
  • 38) 0.632 699 941 847 04 × 2 = 1 + 0.265 399 883 694 08;
  • 39) 0.265 399 883 694 08 × 2 = 0 + 0.530 799 767 388 16;
  • 40) 0.530 799 767 388 16 × 2 = 1 + 0.061 599 534 776 32;
  • 41) 0.061 599 534 776 32 × 2 = 0 + 0.123 199 069 552 64;
  • 42) 0.123 199 069 552 64 × 2 = 0 + 0.246 398 139 105 28;
  • 43) 0.246 398 139 105 28 × 2 = 0 + 0.492 796 278 210 56;
  • 44) 0.492 796 278 210 56 × 2 = 0 + 0.985 592 556 421 12;
  • 45) 0.985 592 556 421 12 × 2 = 1 + 0.971 185 112 842 24;
  • 46) 0.971 185 112 842 24 × 2 = 1 + 0.942 370 225 684 48;
  • 47) 0.942 370 225 684 48 × 2 = 1 + 0.884 740 451 368 96;
  • 48) 0.884 740 451 368 96 × 2 = 1 + 0.769 480 902 737 92;
  • 49) 0.769 480 902 737 92 × 2 = 1 + 0.538 961 805 475 84;
  • 50) 0.538 961 805 475 84 × 2 = 1 + 0.077 923 610 951 68;
  • 51) 0.077 923 610 951 68 × 2 = 0 + 0.155 847 221 903 36;
  • 52) 0.155 847 221 903 36 × 2 = 0 + 0.311 694 443 806 72;
  • 53) 0.311 694 443 806 72 × 2 = 0 + 0.623 388 887 613 44;

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:


0.160 000 000 000 82(10) =


0.0010 1000 1111 0101 1100 0010 1000 1111 0101 1101 0000 1111 1100 0(2)

5. Positive number before normalization:

512.160 000 000 000 82(10) =


10 0000 0000.0010 1000 1111 0101 1100 0010 1000 1111 0101 1101 0000 1111 1100 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 9 positions to the left, so that only one non zero digit remains to the left of it:


512.160 000 000 000 82(10) =


10 0000 0000.0010 1000 1111 0101 1100 0010 1000 1111 0101 1101 0000 1111 1100 0(2) =


10 0000 0000.0010 1000 1111 0101 1100 0010 1000 1111 0101 1101 0000 1111 1100 0(2) × 20 =


1.0000 0000 0001 0100 0111 1010 1110 0001 0100 0111 1010 1110 1000 0111 1110 00(2) × 29


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): 9


Mantissa (not normalized):
1.0000 0000 0001 0100 0111 1010 1110 0001 0100 0111 1010 1110 1000 0111 1110 00


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


9 + 2(11-1) - 1 =


(9 + 1 023)(10) =


1 032(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;
  • 1 032 ÷ 2 = 516 + 0;
  • 516 ÷ 2 = 258 + 0;
  • 258 ÷ 2 = 129 + 0;
  • 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) =


1032(10) =


100 0000 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, 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 0000 0001 0100 0111 1010 1110 0001 0100 0111 1010 1110 1000 01 1111 1000 =


0000 0000 0001 0100 0111 1010 1110 0001 0100 0111 1010 1110 1000


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 1000


Mantissa (52 bits) =
0000 0000 0001 0100 0111 1010 1110 0001 0100 0111 1010 1110 1000


Decimal number 512.160 000 000 000 82 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 1000 - 0000 0000 0001 0100 0111 1010 1110 0001 0100 0111 1010 1110 1000


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