257.813 607 931 850 3 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 257.813 607 931 850 3(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
257.813 607 931 850 3(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: 257.
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;
  • 257 ÷ 2 = 128 + 1;
  • 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.

257(10) =


1 0000 0001(2)


3. Convert to binary (base 2) the fractional part: 0.813 607 931 850 3.

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) 0.813 607 931 850 3 × 2 = 1 + 0.627 215 863 700 6;
  • 2) 0.627 215 863 700 6 × 2 = 1 + 0.254 431 727 401 2;
  • 3) 0.254 431 727 401 2 × 2 = 0 + 0.508 863 454 802 4;
  • 4) 0.508 863 454 802 4 × 2 = 1 + 0.017 726 909 604 8;
  • 5) 0.017 726 909 604 8 × 2 = 0 + 0.035 453 819 209 6;
  • 6) 0.035 453 819 209 6 × 2 = 0 + 0.070 907 638 419 2;
  • 7) 0.070 907 638 419 2 × 2 = 0 + 0.141 815 276 838 4;
  • 8) 0.141 815 276 838 4 × 2 = 0 + 0.283 630 553 676 8;
  • 9) 0.283 630 553 676 8 × 2 = 0 + 0.567 261 107 353 6;
  • 10) 0.567 261 107 353 6 × 2 = 1 + 0.134 522 214 707 2;
  • 11) 0.134 522 214 707 2 × 2 = 0 + 0.269 044 429 414 4;
  • 12) 0.269 044 429 414 4 × 2 = 0 + 0.538 088 858 828 8;
  • 13) 0.538 088 858 828 8 × 2 = 1 + 0.076 177 717 657 6;
  • 14) 0.076 177 717 657 6 × 2 = 0 + 0.152 355 435 315 2;
  • 15) 0.152 355 435 315 2 × 2 = 0 + 0.304 710 870 630 4;
  • 16) 0.304 710 870 630 4 × 2 = 0 + 0.609 421 741 260 8;
  • 17) 0.609 421 741 260 8 × 2 = 1 + 0.218 843 482 521 6;
  • 18) 0.218 843 482 521 6 × 2 = 0 + 0.437 686 965 043 2;
  • 19) 0.437 686 965 043 2 × 2 = 0 + 0.875 373 930 086 4;
  • 20) 0.875 373 930 086 4 × 2 = 1 + 0.750 747 860 172 8;
  • 21) 0.750 747 860 172 8 × 2 = 1 + 0.501 495 720 345 6;
  • 22) 0.501 495 720 345 6 × 2 = 1 + 0.002 991 440 691 2;
  • 23) 0.002 991 440 691 2 × 2 = 0 + 0.005 982 881 382 4;
  • 24) 0.005 982 881 382 4 × 2 = 0 + 0.011 965 762 764 8;
  • 25) 0.011 965 762 764 8 × 2 = 0 + 0.023 931 525 529 6;
  • 26) 0.023 931 525 529 6 × 2 = 0 + 0.047 863 051 059 2;
  • 27) 0.047 863 051 059 2 × 2 = 0 + 0.095 726 102 118 4;
  • 28) 0.095 726 102 118 4 × 2 = 0 + 0.191 452 204 236 8;
  • 29) 0.191 452 204 236 8 × 2 = 0 + 0.382 904 408 473 6;
  • 30) 0.382 904 408 473 6 × 2 = 0 + 0.765 808 816 947 2;
  • 31) 0.765 808 816 947 2 × 2 = 1 + 0.531 617 633 894 4;
  • 32) 0.531 617 633 894 4 × 2 = 1 + 0.063 235 267 788 8;
  • 33) 0.063 235 267 788 8 × 2 = 0 + 0.126 470 535 577 6;
  • 34) 0.126 470 535 577 6 × 2 = 0 + 0.252 941 071 155 2;
  • 35) 0.252 941 071 155 2 × 2 = 0 + 0.505 882 142 310 4;
  • 36) 0.505 882 142 310 4 × 2 = 1 + 0.011 764 284 620 8;
  • 37) 0.011 764 284 620 8 × 2 = 0 + 0.023 528 569 241 6;
  • 38) 0.023 528 569 241 6 × 2 = 0 + 0.047 057 138 483 2;
  • 39) 0.047 057 138 483 2 × 2 = 0 + 0.094 114 276 966 4;
  • 40) 0.094 114 276 966 4 × 2 = 0 + 0.188 228 553 932 8;
  • 41) 0.188 228 553 932 8 × 2 = 0 + 0.376 457 107 865 6;
  • 42) 0.376 457 107 865 6 × 2 = 0 + 0.752 914 215 731 2;
  • 43) 0.752 914 215 731 2 × 2 = 1 + 0.505 828 431 462 4;
  • 44) 0.505 828 431 462 4 × 2 = 1 + 0.011 656 862 924 8;
  • 45) 0.011 656 862 924 8 × 2 = 0 + 0.023 313 725 849 6;
  • 46) 0.023 313 725 849 6 × 2 = 0 + 0.046 627 451 699 2;
  • 47) 0.046 627 451 699 2 × 2 = 0 + 0.093 254 903 398 4;
  • 48) 0.093 254 903 398 4 × 2 = 0 + 0.186 509 806 796 8;
  • 49) 0.186 509 806 796 8 × 2 = 0 + 0.373 019 613 593 6;
  • 50) 0.373 019 613 593 6 × 2 = 0 + 0.746 039 227 187 2;
  • 51) 0.746 039 227 187 2 × 2 = 1 + 0.492 078 454 374 4;
  • 52) 0.492 078 454 374 4 × 2 = 0 + 0.984 156 908 748 8;
  • 53) 0.984 156 908 748 8 × 2 = 1 + 0.968 313 817 497 6;

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:


0.813 607 931 850 3(10) =


0.1101 0000 0100 1000 1001 1100 0000 0011 0001 0000 0011 0000 0010 1(2)

5. Positive number before normalization:

257.813 607 931 850 3(10) =


1 0000 0001.1101 0000 0100 1000 1001 1100 0000 0011 0001 0000 0011 0000 0010 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 8 positions to the left, so that only one non zero digit remains to the left of it:


257.813 607 931 850 3(10) =


1 0000 0001.1101 0000 0100 1000 1001 1100 0000 0011 0001 0000 0011 0000 0010 1(2) =


1 0000 0001.1101 0000 0100 1000 1001 1100 0000 0011 0001 0000 0011 0000 0010 1(2) × 20 =


1.0000 0001 1101 0000 0100 1000 1001 1100 0000 0011 0001 0000 0011 0000 0010 1(2) × 28


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): 8


Mantissa (not normalized):
1.0000 0001 1101 0000 0100 1000 1001 1100 0000 0011 0001 0000 0011 0000 0010 1


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


8 + 2(11-1) - 1 =


(8 + 1 023)(10) =


1 031(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;
  • 1 031 ÷ 2 = 515 + 1;
  • 515 ÷ 2 = 257 + 1;
  • 257 ÷ 2 = 128 + 1;
  • 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) =


1031(10) =


100 0000 0111(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 0001 1101 0000 0100 1000 1001 1100 0000 0011 0001 0000 0011 0 0000 0101 =


0000 0001 1101 0000 0100 1000 1001 1100 0000 0011 0001 0000 0011


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 0111


Mantissa (52 bits) =
0000 0001 1101 0000 0100 1000 1001 1100 0000 0011 0001 0000 0011


Decimal number 257.813 607 931 850 3 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0111 - 0000 0001 1101 0000 0100 1000 1001 1100 0000 0011 0001 0000 0011


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