25.714 256 286 622 28 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 25.714 256 286 622 28(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
25.714 256 286 622 28(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: 25.
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;
  • 25 ÷ 2 = 12 + 1;
  • 12 ÷ 2 = 6 + 0;
  • 6 ÷ 2 = 3 + 0;
  • 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.

25(10) =


1 1001(2)


3. Convert to binary (base 2) the fractional part: 0.714 256 286 622 28.

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) 0.714 256 286 622 28 × 2 = 1 + 0.428 512 573 244 56;
  • 2) 0.428 512 573 244 56 × 2 = 0 + 0.857 025 146 489 12;
  • 3) 0.857 025 146 489 12 × 2 = 1 + 0.714 050 292 978 24;
  • 4) 0.714 050 292 978 24 × 2 = 1 + 0.428 100 585 956 48;
  • 5) 0.428 100 585 956 48 × 2 = 0 + 0.856 201 171 912 96;
  • 6) 0.856 201 171 912 96 × 2 = 1 + 0.712 402 343 825 92;
  • 7) 0.712 402 343 825 92 × 2 = 1 + 0.424 804 687 651 84;
  • 8) 0.424 804 687 651 84 × 2 = 0 + 0.849 609 375 303 68;
  • 9) 0.849 609 375 303 68 × 2 = 1 + 0.699 218 750 607 36;
  • 10) 0.699 218 750 607 36 × 2 = 1 + 0.398 437 501 214 72;
  • 11) 0.398 437 501 214 72 × 2 = 0 + 0.796 875 002 429 44;
  • 12) 0.796 875 002 429 44 × 2 = 1 + 0.593 750 004 858 88;
  • 13) 0.593 750 004 858 88 × 2 = 1 + 0.187 500 009 717 76;
  • 14) 0.187 500 009 717 76 × 2 = 0 + 0.375 000 019 435 52;
  • 15) 0.375 000 019 435 52 × 2 = 0 + 0.750 000 038 871 04;
  • 16) 0.750 000 038 871 04 × 2 = 1 + 0.500 000 077 742 08;
  • 17) 0.500 000 077 742 08 × 2 = 1 + 0.000 000 155 484 16;
  • 18) 0.000 000 155 484 16 × 2 = 0 + 0.000 000 310 968 32;
  • 19) 0.000 000 310 968 32 × 2 = 0 + 0.000 000 621 936 64;
  • 20) 0.000 000 621 936 64 × 2 = 0 + 0.000 001 243 873 28;
  • 21) 0.000 001 243 873 28 × 2 = 0 + 0.000 002 487 746 56;
  • 22) 0.000 002 487 746 56 × 2 = 0 + 0.000 004 975 493 12;
  • 23) 0.000 004 975 493 12 × 2 = 0 + 0.000 009 950 986 24;
  • 24) 0.000 009 950 986 24 × 2 = 0 + 0.000 019 901 972 48;
  • 25) 0.000 019 901 972 48 × 2 = 0 + 0.000 039 803 944 96;
  • 26) 0.000 039 803 944 96 × 2 = 0 + 0.000 079 607 889 92;
  • 27) 0.000 079 607 889 92 × 2 = 0 + 0.000 159 215 779 84;
  • 28) 0.000 159 215 779 84 × 2 = 0 + 0.000 318 431 559 68;
  • 29) 0.000 318 431 559 68 × 2 = 0 + 0.000 636 863 119 36;
  • 30) 0.000 636 863 119 36 × 2 = 0 + 0.001 273 726 238 72;
  • 31) 0.001 273 726 238 72 × 2 = 0 + 0.002 547 452 477 44;
  • 32) 0.002 547 452 477 44 × 2 = 0 + 0.005 094 904 954 88;
  • 33) 0.005 094 904 954 88 × 2 = 0 + 0.010 189 809 909 76;
  • 34) 0.010 189 809 909 76 × 2 = 0 + 0.020 379 619 819 52;
  • 35) 0.020 379 619 819 52 × 2 = 0 + 0.040 759 239 639 04;
  • 36) 0.040 759 239 639 04 × 2 = 0 + 0.081 518 479 278 08;
  • 37) 0.081 518 479 278 08 × 2 = 0 + 0.163 036 958 556 16;
  • 38) 0.163 036 958 556 16 × 2 = 0 + 0.326 073 917 112 32;
  • 39) 0.326 073 917 112 32 × 2 = 0 + 0.652 147 834 224 64;
  • 40) 0.652 147 834 224 64 × 2 = 1 + 0.304 295 668 449 28;
  • 41) 0.304 295 668 449 28 × 2 = 0 + 0.608 591 336 898 56;
  • 42) 0.608 591 336 898 56 × 2 = 1 + 0.217 182 673 797 12;
  • 43) 0.217 182 673 797 12 × 2 = 0 + 0.434 365 347 594 24;
  • 44) 0.434 365 347 594 24 × 2 = 0 + 0.868 730 695 188 48;
  • 45) 0.868 730 695 188 48 × 2 = 1 + 0.737 461 390 376 96;
  • 46) 0.737 461 390 376 96 × 2 = 1 + 0.474 922 780 753 92;
  • 47) 0.474 922 780 753 92 × 2 = 0 + 0.949 845 561 507 84;
  • 48) 0.949 845 561 507 84 × 2 = 1 + 0.899 691 123 015 68;
  • 49) 0.899 691 123 015 68 × 2 = 1 + 0.799 382 246 031 36;
  • 50) 0.799 382 246 031 36 × 2 = 1 + 0.598 764 492 062 72;
  • 51) 0.598 764 492 062 72 × 2 = 1 + 0.197 528 984 125 44;
  • 52) 0.197 528 984 125 44 × 2 = 0 + 0.395 057 968 250 88;
  • 53) 0.395 057 968 250 88 × 2 = 0 + 0.790 115 936 501 76;

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:


0.714 256 286 622 28(10) =


0.1011 0110 1101 1001 1000 0000 0000 0000 0000 0001 0100 1101 1110 0(2)

5. Positive number before normalization:

25.714 256 286 622 28(10) =


1 1001.1011 0110 1101 1001 1000 0000 0000 0000 0000 0001 0100 1101 1110 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 4 positions to the left, so that only one non zero digit remains to the left of it:


25.714 256 286 622 28(10) =


1 1001.1011 0110 1101 1001 1000 0000 0000 0000 0000 0001 0100 1101 1110 0(2) =


1 1001.1011 0110 1101 1001 1000 0000 0000 0000 0000 0001 0100 1101 1110 0(2) × 20 =


1.1001 1011 0110 1101 1001 1000 0000 0000 0000 0000 0001 0100 1101 1110 0(2) × 24


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): 4


Mantissa (not normalized):
1.1001 1011 0110 1101 1001 1000 0000 0000 0000 0000 0001 0100 1101 1110 0


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


4 + 2(11-1) - 1 =


(4 + 1 023)(10) =


1 027(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;
  • 1 027 ÷ 2 = 513 + 1;
  • 513 ÷ 2 = 256 + 1;
  • 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) =


1027(10) =


100 0000 0011(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. 1001 1011 0110 1101 1001 1000 0000 0000 0000 0000 0001 0100 1101 1 1100 =


1001 1011 0110 1101 1001 1000 0000 0000 0000 0000 0001 0100 1101


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 0011


Mantissa (52 bits) =
1001 1011 0110 1101 1001 1000 0000 0000 0000 0000 0001 0100 1101


Decimal number 25.714 256 286 622 28 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0011 - 1001 1011 0110 1101 1001 1000 0000 0000 0000 0000 0001 0100 1101


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