2.825 013 658 729 97 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.825 013 658 729 97(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
2.825 013 658 729 97(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: 0.825 013 658 729 97.

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) 0.825 013 658 729 97 × 2 = 1 + 0.650 027 317 459 94;
  • 2) 0.650 027 317 459 94 × 2 = 1 + 0.300 054 634 919 88;
  • 3) 0.300 054 634 919 88 × 2 = 0 + 0.600 109 269 839 76;
  • 4) 0.600 109 269 839 76 × 2 = 1 + 0.200 218 539 679 52;
  • 5) 0.200 218 539 679 52 × 2 = 0 + 0.400 437 079 359 04;
  • 6) 0.400 437 079 359 04 × 2 = 0 + 0.800 874 158 718 08;
  • 7) 0.800 874 158 718 08 × 2 = 1 + 0.601 748 317 436 16;
  • 8) 0.601 748 317 436 16 × 2 = 1 + 0.203 496 634 872 32;
  • 9) 0.203 496 634 872 32 × 2 = 0 + 0.406 993 269 744 64;
  • 10) 0.406 993 269 744 64 × 2 = 0 + 0.813 986 539 489 28;
  • 11) 0.813 986 539 489 28 × 2 = 1 + 0.627 973 078 978 56;
  • 12) 0.627 973 078 978 56 × 2 = 1 + 0.255 946 157 957 12;
  • 13) 0.255 946 157 957 12 × 2 = 0 + 0.511 892 315 914 24;
  • 14) 0.511 892 315 914 24 × 2 = 1 + 0.023 784 631 828 48;
  • 15) 0.023 784 631 828 48 × 2 = 0 + 0.047 569 263 656 96;
  • 16) 0.047 569 263 656 96 × 2 = 0 + 0.095 138 527 313 92;
  • 17) 0.095 138 527 313 92 × 2 = 0 + 0.190 277 054 627 84;
  • 18) 0.190 277 054 627 84 × 2 = 0 + 0.380 554 109 255 68;
  • 19) 0.380 554 109 255 68 × 2 = 0 + 0.761 108 218 511 36;
  • 20) 0.761 108 218 511 36 × 2 = 1 + 0.522 216 437 022 72;
  • 21) 0.522 216 437 022 72 × 2 = 1 + 0.044 432 874 045 44;
  • 22) 0.044 432 874 045 44 × 2 = 0 + 0.088 865 748 090 88;
  • 23) 0.088 865 748 090 88 × 2 = 0 + 0.177 731 496 181 76;
  • 24) 0.177 731 496 181 76 × 2 = 0 + 0.355 462 992 363 52;
  • 25) 0.355 462 992 363 52 × 2 = 0 + 0.710 925 984 727 04;
  • 26) 0.710 925 984 727 04 × 2 = 1 + 0.421 851 969 454 08;
  • 27) 0.421 851 969 454 08 × 2 = 0 + 0.843 703 938 908 16;
  • 28) 0.843 703 938 908 16 × 2 = 1 + 0.687 407 877 816 32;
  • 29) 0.687 407 877 816 32 × 2 = 1 + 0.374 815 755 632 64;
  • 30) 0.374 815 755 632 64 × 2 = 0 + 0.749 631 511 265 28;
  • 31) 0.749 631 511 265 28 × 2 = 1 + 0.499 263 022 530 56;
  • 32) 0.499 263 022 530 56 × 2 = 0 + 0.998 526 045 061 12;
  • 33) 0.998 526 045 061 12 × 2 = 1 + 0.997 052 090 122 24;
  • 34) 0.997 052 090 122 24 × 2 = 1 + 0.994 104 180 244 48;
  • 35) 0.994 104 180 244 48 × 2 = 1 + 0.988 208 360 488 96;
  • 36) 0.988 208 360 488 96 × 2 = 1 + 0.976 416 720 977 92;
  • 37) 0.976 416 720 977 92 × 2 = 1 + 0.952 833 441 955 84;
  • 38) 0.952 833 441 955 84 × 2 = 1 + 0.905 666 883 911 68;
  • 39) 0.905 666 883 911 68 × 2 = 1 + 0.811 333 767 823 36;
  • 40) 0.811 333 767 823 36 × 2 = 1 + 0.622 667 535 646 72;
  • 41) 0.622 667 535 646 72 × 2 = 1 + 0.245 335 071 293 44;
  • 42) 0.245 335 071 293 44 × 2 = 0 + 0.490 670 142 586 88;
  • 43) 0.490 670 142 586 88 × 2 = 0 + 0.981 340 285 173 76;
  • 44) 0.981 340 285 173 76 × 2 = 1 + 0.962 680 570 347 52;
  • 45) 0.962 680 570 347 52 × 2 = 1 + 0.925 361 140 695 04;
  • 46) 0.925 361 140 695 04 × 2 = 1 + 0.850 722 281 390 08;
  • 47) 0.850 722 281 390 08 × 2 = 1 + 0.701 444 562 780 16;
  • 48) 0.701 444 562 780 16 × 2 = 1 + 0.402 889 125 560 32;
  • 49) 0.402 889 125 560 32 × 2 = 0 + 0.805 778 251 120 64;
  • 50) 0.805 778 251 120 64 × 2 = 1 + 0.611 556 502 241 28;
  • 51) 0.611 556 502 241 28 × 2 = 1 + 0.223 113 004 482 56;
  • 52) 0.223 113 004 482 56 × 2 = 0 + 0.446 226 008 965 12;
  • 53) 0.446 226 008 965 12 × 2 = 0 + 0.892 452 017 930 24;

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:


0.825 013 658 729 97(10) =


0.1101 0011 0011 0100 0001 1000 0101 1010 1111 1111 1001 1111 0110 0(2)

5. Positive number before normalization:

2.825 013 658 729 97(10) =


10.1101 0011 0011 0100 0001 1000 0101 1010 1111 1111 1001 1111 0110 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:


2.825 013 658 729 97(10) =


10.1101 0011 0011 0100 0001 1000 0101 1010 1111 1111 1001 1111 0110 0(2) =


10.1101 0011 0011 0100 0001 1000 0101 1010 1111 1111 1001 1111 0110 0(2) × 20 =


1.0110 1001 1001 1010 0000 1100 0010 1101 0111 1111 1100 1111 1011 00(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):
1.0110 1001 1001 1010 0000 1100 0010 1101 0111 1111 1100 1111 1011 00


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. 0110 1001 1001 1010 0000 1100 0010 1101 0111 1111 1100 1111 1011 00 =


0110 1001 1001 1010 0000 1100 0010 1101 0111 1111 1100 1111 1011


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) =
0110 1001 1001 1010 0000 1100 0010 1101 0111 1111 1100 1111 1011


Decimal number 2.825 013 658 729 97 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0000 - 0110 1001 1001 1010 0000 1100 0010 1101 0111 1111 1100 1111 1011


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