512.160 000 000 000 31 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 512.160 000 000 000 31(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 31(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 31.

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 31 × 2 = 0 + 0.320 000 000 000 62;
  • 2) 0.320 000 000 000 62 × 2 = 0 + 0.640 000 000 001 24;
  • 3) 0.640 000 000 001 24 × 2 = 1 + 0.280 000 000 002 48;
  • 4) 0.280 000 000 002 48 × 2 = 0 + 0.560 000 000 004 96;
  • 5) 0.560 000 000 004 96 × 2 = 1 + 0.120 000 000 009 92;
  • 6) 0.120 000 000 009 92 × 2 = 0 + 0.240 000 000 019 84;
  • 7) 0.240 000 000 019 84 × 2 = 0 + 0.480 000 000 039 68;
  • 8) 0.480 000 000 039 68 × 2 = 0 + 0.960 000 000 079 36;
  • 9) 0.960 000 000 079 36 × 2 = 1 + 0.920 000 000 158 72;
  • 10) 0.920 000 000 158 72 × 2 = 1 + 0.840 000 000 317 44;
  • 11) 0.840 000 000 317 44 × 2 = 1 + 0.680 000 000 634 88;
  • 12) 0.680 000 000 634 88 × 2 = 1 + 0.360 000 001 269 76;
  • 13) 0.360 000 001 269 76 × 2 = 0 + 0.720 000 002 539 52;
  • 14) 0.720 000 002 539 52 × 2 = 1 + 0.440 000 005 079 04;
  • 15) 0.440 000 005 079 04 × 2 = 0 + 0.880 000 010 158 08;
  • 16) 0.880 000 010 158 08 × 2 = 1 + 0.760 000 020 316 16;
  • 17) 0.760 000 020 316 16 × 2 = 1 + 0.520 000 040 632 32;
  • 18) 0.520 000 040 632 32 × 2 = 1 + 0.040 000 081 264 64;
  • 19) 0.040 000 081 264 64 × 2 = 0 + 0.080 000 162 529 28;
  • 20) 0.080 000 162 529 28 × 2 = 0 + 0.160 000 325 058 56;
  • 21) 0.160 000 325 058 56 × 2 = 0 + 0.320 000 650 117 12;
  • 22) 0.320 000 650 117 12 × 2 = 0 + 0.640 001 300 234 24;
  • 23) 0.640 001 300 234 24 × 2 = 1 + 0.280 002 600 468 48;
  • 24) 0.280 002 600 468 48 × 2 = 0 + 0.560 005 200 936 96;
  • 25) 0.560 005 200 936 96 × 2 = 1 + 0.120 010 401 873 92;
  • 26) 0.120 010 401 873 92 × 2 = 0 + 0.240 020 803 747 84;
  • 27) 0.240 020 803 747 84 × 2 = 0 + 0.480 041 607 495 68;
  • 28) 0.480 041 607 495 68 × 2 = 0 + 0.960 083 214 991 36;
  • 29) 0.960 083 214 991 36 × 2 = 1 + 0.920 166 429 982 72;
  • 30) 0.920 166 429 982 72 × 2 = 1 + 0.840 332 859 965 44;
  • 31) 0.840 332 859 965 44 × 2 = 1 + 0.680 665 719 930 88;
  • 32) 0.680 665 719 930 88 × 2 = 1 + 0.361 331 439 861 76;
  • 33) 0.361 331 439 861 76 × 2 = 0 + 0.722 662 879 723 52;
  • 34) 0.722 662 879 723 52 × 2 = 1 + 0.445 325 759 447 04;
  • 35) 0.445 325 759 447 04 × 2 = 0 + 0.890 651 518 894 08;
  • 36) 0.890 651 518 894 08 × 2 = 1 + 0.781 303 037 788 16;
  • 37) 0.781 303 037 788 16 × 2 = 1 + 0.562 606 075 576 32;
  • 38) 0.562 606 075 576 32 × 2 = 1 + 0.125 212 151 152 64;
  • 39) 0.125 212 151 152 64 × 2 = 0 + 0.250 424 302 305 28;
  • 40) 0.250 424 302 305 28 × 2 = 0 + 0.500 848 604 610 56;
  • 41) 0.500 848 604 610 56 × 2 = 1 + 0.001 697 209 221 12;
  • 42) 0.001 697 209 221 12 × 2 = 0 + 0.003 394 418 442 24;
  • 43) 0.003 394 418 442 24 × 2 = 0 + 0.006 788 836 884 48;
  • 44) 0.006 788 836 884 48 × 2 = 0 + 0.013 577 673 768 96;
  • 45) 0.013 577 673 768 96 × 2 = 0 + 0.027 155 347 537 92;
  • 46) 0.027 155 347 537 92 × 2 = 0 + 0.054 310 695 075 84;
  • 47) 0.054 310 695 075 84 × 2 = 0 + 0.108 621 390 151 68;
  • 48) 0.108 621 390 151 68 × 2 = 0 + 0.217 242 780 303 36;
  • 49) 0.217 242 780 303 36 × 2 = 0 + 0.434 485 560 606 72;
  • 50) 0.434 485 560 606 72 × 2 = 0 + 0.868 971 121 213 44;
  • 51) 0.868 971 121 213 44 × 2 = 1 + 0.737 942 242 426 88;
  • 52) 0.737 942 242 426 88 × 2 = 1 + 0.475 884 484 853 76;
  • 53) 0.475 884 484 853 76 × 2 = 0 + 0.951 768 969 707 52;

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 31(10) =


0.0010 1000 1111 0101 1100 0010 1000 1111 0101 1100 1000 0000 0011 0(2)

5. Positive number before normalization:

512.160 000 000 000 31(10) =


10 0000 0000.0010 1000 1111 0101 1100 0010 1000 1111 0101 1100 1000 0000 0011 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 31(10) =


10 0000 0000.0010 1000 1111 0101 1100 0010 1000 1111 0101 1100 1000 0000 0011 0(2) =


10 0000 0000.0010 1000 1111 0101 1100 0010 1000 1111 0101 1100 1000 0000 0011 0(2) × 20 =


1.0000 0000 0001 0100 0111 1010 1110 0001 0100 0111 1010 1110 0100 0000 0001 10(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 0100 0000 0001 10


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 0100 00 0000 0110 =


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


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 0100


Decimal number 512.160 000 000 000 31 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 0100


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