2.714 285 714 292 69 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.714 285 714 292 69(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
2.714 285 714 292 69(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: 2.
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;
  • 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.

2(10) =


10(2)


3. Convert to binary (base 2) the fractional part: 0.714 285 714 292 69.

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) 0.714 285 714 292 69 × 2 = 1 + 0.428 571 428 585 38;
  • 2) 0.428 571 428 585 38 × 2 = 0 + 0.857 142 857 170 76;
  • 3) 0.857 142 857 170 76 × 2 = 1 + 0.714 285 714 341 52;
  • 4) 0.714 285 714 341 52 × 2 = 1 + 0.428 571 428 683 04;
  • 5) 0.428 571 428 683 04 × 2 = 0 + 0.857 142 857 366 08;
  • 6) 0.857 142 857 366 08 × 2 = 1 + 0.714 285 714 732 16;
  • 7) 0.714 285 714 732 16 × 2 = 1 + 0.428 571 429 464 32;
  • 8) 0.428 571 429 464 32 × 2 = 0 + 0.857 142 858 928 64;
  • 9) 0.857 142 858 928 64 × 2 = 1 + 0.714 285 717 857 28;
  • 10) 0.714 285 717 857 28 × 2 = 1 + 0.428 571 435 714 56;
  • 11) 0.428 571 435 714 56 × 2 = 0 + 0.857 142 871 429 12;
  • 12) 0.857 142 871 429 12 × 2 = 1 + 0.714 285 742 858 24;
  • 13) 0.714 285 742 858 24 × 2 = 1 + 0.428 571 485 716 48;
  • 14) 0.428 571 485 716 48 × 2 = 0 + 0.857 142 971 432 96;
  • 15) 0.857 142 971 432 96 × 2 = 1 + 0.714 285 942 865 92;
  • 16) 0.714 285 942 865 92 × 2 = 1 + 0.428 571 885 731 84;
  • 17) 0.428 571 885 731 84 × 2 = 0 + 0.857 143 771 463 68;
  • 18) 0.857 143 771 463 68 × 2 = 1 + 0.714 287 542 927 36;
  • 19) 0.714 287 542 927 36 × 2 = 1 + 0.428 575 085 854 72;
  • 20) 0.428 575 085 854 72 × 2 = 0 + 0.857 150 171 709 44;
  • 21) 0.857 150 171 709 44 × 2 = 1 + 0.714 300 343 418 88;
  • 22) 0.714 300 343 418 88 × 2 = 1 + 0.428 600 686 837 76;
  • 23) 0.428 600 686 837 76 × 2 = 0 + 0.857 201 373 675 52;
  • 24) 0.857 201 373 675 52 × 2 = 1 + 0.714 402 747 351 04;
  • 25) 0.714 402 747 351 04 × 2 = 1 + 0.428 805 494 702 08;
  • 26) 0.428 805 494 702 08 × 2 = 0 + 0.857 610 989 404 16;
  • 27) 0.857 610 989 404 16 × 2 = 1 + 0.715 221 978 808 32;
  • 28) 0.715 221 978 808 32 × 2 = 1 + 0.430 443 957 616 64;
  • 29) 0.430 443 957 616 64 × 2 = 0 + 0.860 887 915 233 28;
  • 30) 0.860 887 915 233 28 × 2 = 1 + 0.721 775 830 466 56;
  • 31) 0.721 775 830 466 56 × 2 = 1 + 0.443 551 660 933 12;
  • 32) 0.443 551 660 933 12 × 2 = 0 + 0.887 103 321 866 24;
  • 33) 0.887 103 321 866 24 × 2 = 1 + 0.774 206 643 732 48;
  • 34) 0.774 206 643 732 48 × 2 = 1 + 0.548 413 287 464 96;
  • 35) 0.548 413 287 464 96 × 2 = 1 + 0.096 826 574 929 92;
  • 36) 0.096 826 574 929 92 × 2 = 0 + 0.193 653 149 859 84;
  • 37) 0.193 653 149 859 84 × 2 = 0 + 0.387 306 299 719 68;
  • 38) 0.387 306 299 719 68 × 2 = 0 + 0.774 612 599 439 36;
  • 39) 0.774 612 599 439 36 × 2 = 1 + 0.549 225 198 878 72;
  • 40) 0.549 225 198 878 72 × 2 = 1 + 0.098 450 397 757 44;
  • 41) 0.098 450 397 757 44 × 2 = 0 + 0.196 900 795 514 88;
  • 42) 0.196 900 795 514 88 × 2 = 0 + 0.393 801 591 029 76;
  • 43) 0.393 801 591 029 76 × 2 = 0 + 0.787 603 182 059 52;
  • 44) 0.787 603 182 059 52 × 2 = 1 + 0.575 206 364 119 04;
  • 45) 0.575 206 364 119 04 × 2 = 1 + 0.150 412 728 238 08;
  • 46) 0.150 412 728 238 08 × 2 = 0 + 0.300 825 456 476 16;
  • 47) 0.300 825 456 476 16 × 2 = 0 + 0.601 650 912 952 32;
  • 48) 0.601 650 912 952 32 × 2 = 1 + 0.203 301 825 904 64;
  • 49) 0.203 301 825 904 64 × 2 = 0 + 0.406 603 651 809 28;
  • 50) 0.406 603 651 809 28 × 2 = 0 + 0.813 207 303 618 56;
  • 51) 0.813 207 303 618 56 × 2 = 1 + 0.626 414 607 237 12;
  • 52) 0.626 414 607 237 12 × 2 = 1 + 0.252 829 214 474 24;
  • 53) 0.252 829 214 474 24 × 2 = 0 + 0.505 658 428 948 48;

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:


0.714 285 714 292 69(10) =


0.1011 0110 1101 1011 0110 1101 1011 0110 1110 0011 0001 1001 0011 0(2)

5. Positive number before normalization:

2.714 285 714 292 69(10) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1110 0011 0001 1001 0011 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 1 positions to the left, so that only one non zero digit remains to the left of it:


2.714 285 714 292 69(10) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1110 0011 0001 1001 0011 0(2) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1110 0011 0001 1001 0011 0(2) × 20 =


1.0101 1011 0110 1101 1011 0110 1101 1011 0111 0001 1000 1100 1001 10(2) × 21


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): 1


Mantissa (not normalized):
1.0101 1011 0110 1101 1011 0110 1101 1011 0111 0001 1000 1100 1001 10


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


1 + 2(11-1) - 1 =


(1 + 1 023)(10) =


1 024(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;
  • 1 024 ÷ 2 = 512 + 0;
  • 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;

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) =


1024(10) =


100 0000 0000(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. 0101 1011 0110 1101 1011 0110 1101 1011 0111 0001 1000 1100 1001 10 =


0101 1011 0110 1101 1011 0110 1101 1011 0111 0001 1000 1100 1001


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 0000


Mantissa (52 bits) =
0101 1011 0110 1101 1011 0110 1101 1011 0111 0001 1000 1100 1001


Decimal number 2.714 285 714 292 69 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0000 - 0101 1011 0110 1101 1011 0110 1101 1011 0111 0001 1000 1100 1001

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