14 897.799 651 568 98 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 14 897.799 651 568 98(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
14 897.799 651 568 98(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: 14 897.
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;
  • 14 897 ÷ 2 = 7 448 + 1;
  • 7 448 ÷ 2 = 3 724 + 0;
  • 3 724 ÷ 2 = 1 862 + 0;
  • 1 862 ÷ 2 = 931 + 0;
  • 931 ÷ 2 = 465 + 1;
  • 465 ÷ 2 = 232 + 1;
  • 232 ÷ 2 = 116 + 0;
  • 116 ÷ 2 = 58 + 0;
  • 58 ÷ 2 = 29 + 0;
  • 29 ÷ 2 = 14 + 1;
  • 14 ÷ 2 = 7 + 0;
  • 7 ÷ 2 = 3 + 1;
  • 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.

14 897(10) =


11 1010 0011 0001(2)


3. Convert to binary (base 2) the fractional part: 0.799 651 568 98.

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) 0.799 651 568 98 × 2 = 1 + 0.599 303 137 96;
  • 2) 0.599 303 137 96 × 2 = 1 + 0.198 606 275 92;
  • 3) 0.198 606 275 92 × 2 = 0 + 0.397 212 551 84;
  • 4) 0.397 212 551 84 × 2 = 0 + 0.794 425 103 68;
  • 5) 0.794 425 103 68 × 2 = 1 + 0.588 850 207 36;
  • 6) 0.588 850 207 36 × 2 = 1 + 0.177 700 414 72;
  • 7) 0.177 700 414 72 × 2 = 0 + 0.355 400 829 44;
  • 8) 0.355 400 829 44 × 2 = 0 + 0.710 801 658 88;
  • 9) 0.710 801 658 88 × 2 = 1 + 0.421 603 317 76;
  • 10) 0.421 603 317 76 × 2 = 0 + 0.843 206 635 52;
  • 11) 0.843 206 635 52 × 2 = 1 + 0.686 413 271 04;
  • 12) 0.686 413 271 04 × 2 = 1 + 0.372 826 542 08;
  • 13) 0.372 826 542 08 × 2 = 0 + 0.745 653 084 16;
  • 14) 0.745 653 084 16 × 2 = 1 + 0.491 306 168 32;
  • 15) 0.491 306 168 32 × 2 = 0 + 0.982 612 336 64;
  • 16) 0.982 612 336 64 × 2 = 1 + 0.965 224 673 28;
  • 17) 0.965 224 673 28 × 2 = 1 + 0.930 449 346 56;
  • 18) 0.930 449 346 56 × 2 = 1 + 0.860 898 693 12;
  • 19) 0.860 898 693 12 × 2 = 1 + 0.721 797 386 24;
  • 20) 0.721 797 386 24 × 2 = 1 + 0.443 594 772 48;
  • 21) 0.443 594 772 48 × 2 = 0 + 0.887 189 544 96;
  • 22) 0.887 189 544 96 × 2 = 1 + 0.774 379 089 92;
  • 23) 0.774 379 089 92 × 2 = 1 + 0.548 758 179 84;
  • 24) 0.548 758 179 84 × 2 = 1 + 0.097 516 359 68;
  • 25) 0.097 516 359 68 × 2 = 0 + 0.195 032 719 36;
  • 26) 0.195 032 719 36 × 2 = 0 + 0.390 065 438 72;
  • 27) 0.390 065 438 72 × 2 = 0 + 0.780 130 877 44;
  • 28) 0.780 130 877 44 × 2 = 1 + 0.560 261 754 88;
  • 29) 0.560 261 754 88 × 2 = 1 + 0.120 523 509 76;
  • 30) 0.120 523 509 76 × 2 = 0 + 0.241 047 019 52;
  • 31) 0.241 047 019 52 × 2 = 0 + 0.482 094 039 04;
  • 32) 0.482 094 039 04 × 2 = 0 + 0.964 188 078 08;
  • 33) 0.964 188 078 08 × 2 = 1 + 0.928 376 156 16;
  • 34) 0.928 376 156 16 × 2 = 1 + 0.856 752 312 32;
  • 35) 0.856 752 312 32 × 2 = 1 + 0.713 504 624 64;
  • 36) 0.713 504 624 64 × 2 = 1 + 0.427 009 249 28;
  • 37) 0.427 009 249 28 × 2 = 0 + 0.854 018 498 56;
  • 38) 0.854 018 498 56 × 2 = 1 + 0.708 036 997 12;
  • 39) 0.708 036 997 12 × 2 = 1 + 0.416 073 994 24;
  • 40) 0.416 073 994 24 × 2 = 0 + 0.832 147 988 48;
  • 41) 0.832 147 988 48 × 2 = 1 + 0.664 295 976 96;
  • 42) 0.664 295 976 96 × 2 = 1 + 0.328 591 953 92;
  • 43) 0.328 591 953 92 × 2 = 0 + 0.657 183 907 84;
  • 44) 0.657 183 907 84 × 2 = 1 + 0.314 367 815 68;
  • 45) 0.314 367 815 68 × 2 = 0 + 0.628 735 631 36;
  • 46) 0.628 735 631 36 × 2 = 1 + 0.257 471 262 72;
  • 47) 0.257 471 262 72 × 2 = 0 + 0.514 942 525 44;
  • 48) 0.514 942 525 44 × 2 = 1 + 0.029 885 050 88;
  • 49) 0.029 885 050 88 × 2 = 0 + 0.059 770 101 76;
  • 50) 0.059 770 101 76 × 2 = 0 + 0.119 540 203 52;
  • 51) 0.119 540 203 52 × 2 = 0 + 0.239 080 407 04;
  • 52) 0.239 080 407 04 × 2 = 0 + 0.478 160 814 08;
  • 53) 0.478 160 814 08 × 2 = 0 + 0.956 321 628 16;

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:


0.799 651 568 98(10) =


0.1100 1100 1011 0101 1111 0111 0001 1000 1111 0110 1101 0101 0000 0(2)

5. Positive number before normalization:

14 897.799 651 568 98(10) =


11 1010 0011 0001.1100 1100 1011 0101 1111 0111 0001 1000 1111 0110 1101 0101 0000 0(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:


14 897.799 651 568 98(10) =


11 1010 0011 0001.1100 1100 1011 0101 1111 0111 0001 1000 1111 0110 1101 0101 0000 0(2) =


11 1010 0011 0001.1100 1100 1011 0101 1111 0111 0001 1000 1111 0110 1101 0101 0000 0(2) × 20 =


1.1101 0001 1000 1110 0110 0101 1010 1111 1011 1000 1100 0111 1011 0110 1010 1000 00(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):
1.1101 0001 1000 1110 0110 0101 1010 1111 1011 1000 1100 0111 1011 0110 1010 1000 00


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. 1101 0001 1000 1110 0110 0101 1010 1111 1011 1000 1100 0111 1011 01 1010 1010 0000 =


1101 0001 1000 1110 0110 0101 1010 1111 1011 1000 1100 0111 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) =
1101 0001 1000 1110 0110 0101 1010 1111 1011 1000 1100 0111 1011


Decimal number 14 897.799 651 568 98 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 1100 - 1101 0001 1000 1110 0110 0101 1010 1111 1011 1000 1100 0111 1011


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