25.714 256 286 622 93 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 25.714 256 286 622 93(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 93(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 93.

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 93 × 2 = 1 + 0.428 512 573 245 86;
  • 2) 0.428 512 573 245 86 × 2 = 0 + 0.857 025 146 491 72;
  • 3) 0.857 025 146 491 72 × 2 = 1 + 0.714 050 292 983 44;
  • 4) 0.714 050 292 983 44 × 2 = 1 + 0.428 100 585 966 88;
  • 5) 0.428 100 585 966 88 × 2 = 0 + 0.856 201 171 933 76;
  • 6) 0.856 201 171 933 76 × 2 = 1 + 0.712 402 343 867 52;
  • 7) 0.712 402 343 867 52 × 2 = 1 + 0.424 804 687 735 04;
  • 8) 0.424 804 687 735 04 × 2 = 0 + 0.849 609 375 470 08;
  • 9) 0.849 609 375 470 08 × 2 = 1 + 0.699 218 750 940 16;
  • 10) 0.699 218 750 940 16 × 2 = 1 + 0.398 437 501 880 32;
  • 11) 0.398 437 501 880 32 × 2 = 0 + 0.796 875 003 760 64;
  • 12) 0.796 875 003 760 64 × 2 = 1 + 0.593 750 007 521 28;
  • 13) 0.593 750 007 521 28 × 2 = 1 + 0.187 500 015 042 56;
  • 14) 0.187 500 015 042 56 × 2 = 0 + 0.375 000 030 085 12;
  • 15) 0.375 000 030 085 12 × 2 = 0 + 0.750 000 060 170 24;
  • 16) 0.750 000 060 170 24 × 2 = 1 + 0.500 000 120 340 48;
  • 17) 0.500 000 120 340 48 × 2 = 1 + 0.000 000 240 680 96;
  • 18) 0.000 000 240 680 96 × 2 = 0 + 0.000 000 481 361 92;
  • 19) 0.000 000 481 361 92 × 2 = 0 + 0.000 000 962 723 84;
  • 20) 0.000 000 962 723 84 × 2 = 0 + 0.000 001 925 447 68;
  • 21) 0.000 001 925 447 68 × 2 = 0 + 0.000 003 850 895 36;
  • 22) 0.000 003 850 895 36 × 2 = 0 + 0.000 007 701 790 72;
  • 23) 0.000 007 701 790 72 × 2 = 0 + 0.000 015 403 581 44;
  • 24) 0.000 015 403 581 44 × 2 = 0 + 0.000 030 807 162 88;
  • 25) 0.000 030 807 162 88 × 2 = 0 + 0.000 061 614 325 76;
  • 26) 0.000 061 614 325 76 × 2 = 0 + 0.000 123 228 651 52;
  • 27) 0.000 123 228 651 52 × 2 = 0 + 0.000 246 457 303 04;
  • 28) 0.000 246 457 303 04 × 2 = 0 + 0.000 492 914 606 08;
  • 29) 0.000 492 914 606 08 × 2 = 0 + 0.000 985 829 212 16;
  • 30) 0.000 985 829 212 16 × 2 = 0 + 0.001 971 658 424 32;
  • 31) 0.001 971 658 424 32 × 2 = 0 + 0.003 943 316 848 64;
  • 32) 0.003 943 316 848 64 × 2 = 0 + 0.007 886 633 697 28;
  • 33) 0.007 886 633 697 28 × 2 = 0 + 0.015 773 267 394 56;
  • 34) 0.015 773 267 394 56 × 2 = 0 + 0.031 546 534 789 12;
  • 35) 0.031 546 534 789 12 × 2 = 0 + 0.063 093 069 578 24;
  • 36) 0.063 093 069 578 24 × 2 = 0 + 0.126 186 139 156 48;
  • 37) 0.126 186 139 156 48 × 2 = 0 + 0.252 372 278 312 96;
  • 38) 0.252 372 278 312 96 × 2 = 0 + 0.504 744 556 625 92;
  • 39) 0.504 744 556 625 92 × 2 = 1 + 0.009 489 113 251 84;
  • 40) 0.009 489 113 251 84 × 2 = 0 + 0.018 978 226 503 68;
  • 41) 0.018 978 226 503 68 × 2 = 0 + 0.037 956 453 007 36;
  • 42) 0.037 956 453 007 36 × 2 = 0 + 0.075 912 906 014 72;
  • 43) 0.075 912 906 014 72 × 2 = 0 + 0.151 825 812 029 44;
  • 44) 0.151 825 812 029 44 × 2 = 0 + 0.303 651 624 058 88;
  • 45) 0.303 651 624 058 88 × 2 = 0 + 0.607 303 248 117 76;
  • 46) 0.607 303 248 117 76 × 2 = 1 + 0.214 606 496 235 52;
  • 47) 0.214 606 496 235 52 × 2 = 0 + 0.429 212 992 471 04;
  • 48) 0.429 212 992 471 04 × 2 = 0 + 0.858 425 984 942 08;
  • 49) 0.858 425 984 942 08 × 2 = 1 + 0.716 851 969 884 16;
  • 50) 0.716 851 969 884 16 × 2 = 1 + 0.433 703 939 768 32;
  • 51) 0.433 703 939 768 32 × 2 = 0 + 0.867 407 879 536 64;
  • 52) 0.867 407 879 536 64 × 2 = 1 + 0.734 815 759 073 28;
  • 53) 0.734 815 759 073 28 × 2 = 1 + 0.469 631 518 146 56;

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 93(10) =


0.1011 0110 1101 1001 1000 0000 0000 0000 0000 0010 0000 0100 1101 1(2)

5. Positive number before normalization:

25.714 256 286 622 93(10) =


1 1001.1011 0110 1101 1001 1000 0000 0000 0000 0000 0010 0000 0100 1101 1(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 93(10) =


1 1001.1011 0110 1101 1001 1000 0000 0000 0000 0000 0010 0000 0100 1101 1(2) =


1 1001.1011 0110 1101 1001 1000 0000 0000 0000 0000 0010 0000 0100 1101 1(2) × 20 =


1.1001 1011 0110 1101 1001 1000 0000 0000 0000 0000 0010 0000 0100 1101 1(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 0010 0000 0100 1101 1


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 0010 0000 0100 1 1011 =


1001 1011 0110 1101 1001 1000 0000 0000 0000 0000 0010 0000 0100


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 0010 0000 0100


Decimal number 25.714 256 286 622 93 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 0010 0000 0100

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