2.714 285 714 292 31 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.714 285 714 292 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
2.714 285 714 292 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: 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 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) 0.714 285 714 292 31 × 2 = 1 + 0.428 571 428 584 62;
  • 2) 0.428 571 428 584 62 × 2 = 0 + 0.857 142 857 169 24;
  • 3) 0.857 142 857 169 24 × 2 = 1 + 0.714 285 714 338 48;
  • 4) 0.714 285 714 338 48 × 2 = 1 + 0.428 571 428 676 96;
  • 5) 0.428 571 428 676 96 × 2 = 0 + 0.857 142 857 353 92;
  • 6) 0.857 142 857 353 92 × 2 = 1 + 0.714 285 714 707 84;
  • 7) 0.714 285 714 707 84 × 2 = 1 + 0.428 571 429 415 68;
  • 8) 0.428 571 429 415 68 × 2 = 0 + 0.857 142 858 831 36;
  • 9) 0.857 142 858 831 36 × 2 = 1 + 0.714 285 717 662 72;
  • 10) 0.714 285 717 662 72 × 2 = 1 + 0.428 571 435 325 44;
  • 11) 0.428 571 435 325 44 × 2 = 0 + 0.857 142 870 650 88;
  • 12) 0.857 142 870 650 88 × 2 = 1 + 0.714 285 741 301 76;
  • 13) 0.714 285 741 301 76 × 2 = 1 + 0.428 571 482 603 52;
  • 14) 0.428 571 482 603 52 × 2 = 0 + 0.857 142 965 207 04;
  • 15) 0.857 142 965 207 04 × 2 = 1 + 0.714 285 930 414 08;
  • 16) 0.714 285 930 414 08 × 2 = 1 + 0.428 571 860 828 16;
  • 17) 0.428 571 860 828 16 × 2 = 0 + 0.857 143 721 656 32;
  • 18) 0.857 143 721 656 32 × 2 = 1 + 0.714 287 443 312 64;
  • 19) 0.714 287 443 312 64 × 2 = 1 + 0.428 574 886 625 28;
  • 20) 0.428 574 886 625 28 × 2 = 0 + 0.857 149 773 250 56;
  • 21) 0.857 149 773 250 56 × 2 = 1 + 0.714 299 546 501 12;
  • 22) 0.714 299 546 501 12 × 2 = 1 + 0.428 599 093 002 24;
  • 23) 0.428 599 093 002 24 × 2 = 0 + 0.857 198 186 004 48;
  • 24) 0.857 198 186 004 48 × 2 = 1 + 0.714 396 372 008 96;
  • 25) 0.714 396 372 008 96 × 2 = 1 + 0.428 792 744 017 92;
  • 26) 0.428 792 744 017 92 × 2 = 0 + 0.857 585 488 035 84;
  • 27) 0.857 585 488 035 84 × 2 = 1 + 0.715 170 976 071 68;
  • 28) 0.715 170 976 071 68 × 2 = 1 + 0.430 341 952 143 36;
  • 29) 0.430 341 952 143 36 × 2 = 0 + 0.860 683 904 286 72;
  • 30) 0.860 683 904 286 72 × 2 = 1 + 0.721 367 808 573 44;
  • 31) 0.721 367 808 573 44 × 2 = 1 + 0.442 735 617 146 88;
  • 32) 0.442 735 617 146 88 × 2 = 0 + 0.885 471 234 293 76;
  • 33) 0.885 471 234 293 76 × 2 = 1 + 0.770 942 468 587 52;
  • 34) 0.770 942 468 587 52 × 2 = 1 + 0.541 884 937 175 04;
  • 35) 0.541 884 937 175 04 × 2 = 1 + 0.083 769 874 350 08;
  • 36) 0.083 769 874 350 08 × 2 = 0 + 0.167 539 748 700 16;
  • 37) 0.167 539 748 700 16 × 2 = 0 + 0.335 079 497 400 32;
  • 38) 0.335 079 497 400 32 × 2 = 0 + 0.670 158 994 800 64;
  • 39) 0.670 158 994 800 64 × 2 = 1 + 0.340 317 989 601 28;
  • 40) 0.340 317 989 601 28 × 2 = 0 + 0.680 635 979 202 56;
  • 41) 0.680 635 979 202 56 × 2 = 1 + 0.361 271 958 405 12;
  • 42) 0.361 271 958 405 12 × 2 = 0 + 0.722 543 916 810 24;
  • 43) 0.722 543 916 810 24 × 2 = 1 + 0.445 087 833 620 48;
  • 44) 0.445 087 833 620 48 × 2 = 0 + 0.890 175 667 240 96;
  • 45) 0.890 175 667 240 96 × 2 = 1 + 0.780 351 334 481 92;
  • 46) 0.780 351 334 481 92 × 2 = 1 + 0.560 702 668 963 84;
  • 47) 0.560 702 668 963 84 × 2 = 1 + 0.121 405 337 927 68;
  • 48) 0.121 405 337 927 68 × 2 = 0 + 0.242 810 675 855 36;
  • 49) 0.242 810 675 855 36 × 2 = 0 + 0.485 621 351 710 72;
  • 50) 0.485 621 351 710 72 × 2 = 0 + 0.971 242 703 421 44;
  • 51) 0.971 242 703 421 44 × 2 = 1 + 0.942 485 406 842 88;
  • 52) 0.942 485 406 842 88 × 2 = 1 + 0.884 970 813 685 76;
  • 53) 0.884 970 813 685 76 × 2 = 1 + 0.769 941 627 371 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:


0.714 285 714 292 31(10) =


0.1011 0110 1101 1011 0110 1101 1011 0110 1110 0010 1010 1110 0011 1(2)

5. Positive number before normalization:

2.714 285 714 292 31(10) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1110 0010 1010 1110 0011 1(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 31(10) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1110 0010 1010 1110 0011 1(2) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1110 0010 1010 1110 0011 1(2) × 20 =


1.0101 1011 0110 1101 1011 0110 1101 1011 0111 0001 0101 0111 0001 11(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 0101 0111 0001 11


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 0101 0111 0001 11 =


0101 1011 0110 1101 1011 0110 1101 1011 0111 0001 0101 0111 0001


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 0101 0111 0001


Decimal number 2.714 285 714 292 31 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 0101 0111 0001

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