Decimal to 64 Bit IEEE 754 Binary: Convert Number 2.000 000 611 03 to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From Base Ten Decimal System

Number 2.000 000 611 03(10) converted and written in 64 bit double precision IEEE 754 binary floating point representation standard (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: 0.000 000 611 03.

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) 0.000 000 611 03 × 2 = 0 + 0.000 001 222 06;
  • 2) 0.000 001 222 06 × 2 = 0 + 0.000 002 444 12;
  • 3) 0.000 002 444 12 × 2 = 0 + 0.000 004 888 24;
  • 4) 0.000 004 888 24 × 2 = 0 + 0.000 009 776 48;
  • 5) 0.000 009 776 48 × 2 = 0 + 0.000 019 552 96;
  • 6) 0.000 019 552 96 × 2 = 0 + 0.000 039 105 92;
  • 7) 0.000 039 105 92 × 2 = 0 + 0.000 078 211 84;
  • 8) 0.000 078 211 84 × 2 = 0 + 0.000 156 423 68;
  • 9) 0.000 156 423 68 × 2 = 0 + 0.000 312 847 36;
  • 10) 0.000 312 847 36 × 2 = 0 + 0.000 625 694 72;
  • 11) 0.000 625 694 72 × 2 = 0 + 0.001 251 389 44;
  • 12) 0.001 251 389 44 × 2 = 0 + 0.002 502 778 88;
  • 13) 0.002 502 778 88 × 2 = 0 + 0.005 005 557 76;
  • 14) 0.005 005 557 76 × 2 = 0 + 0.010 011 115 52;
  • 15) 0.010 011 115 52 × 2 = 0 + 0.020 022 231 04;
  • 16) 0.020 022 231 04 × 2 = 0 + 0.040 044 462 08;
  • 17) 0.040 044 462 08 × 2 = 0 + 0.080 088 924 16;
  • 18) 0.080 088 924 16 × 2 = 0 + 0.160 177 848 32;
  • 19) 0.160 177 848 32 × 2 = 0 + 0.320 355 696 64;
  • 20) 0.320 355 696 64 × 2 = 0 + 0.640 711 393 28;
  • 21) 0.640 711 393 28 × 2 = 1 + 0.281 422 786 56;
  • 22) 0.281 422 786 56 × 2 = 0 + 0.562 845 573 12;
  • 23) 0.562 845 573 12 × 2 = 1 + 0.125 691 146 24;
  • 24) 0.125 691 146 24 × 2 = 0 + 0.251 382 292 48;
  • 25) 0.251 382 292 48 × 2 = 0 + 0.502 764 584 96;
  • 26) 0.502 764 584 96 × 2 = 1 + 0.005 529 169 92;
  • 27) 0.005 529 169 92 × 2 = 0 + 0.011 058 339 84;
  • 28) 0.011 058 339 84 × 2 = 0 + 0.022 116 679 68;
  • 29) 0.022 116 679 68 × 2 = 0 + 0.044 233 359 36;
  • 30) 0.044 233 359 36 × 2 = 0 + 0.088 466 718 72;
  • 31) 0.088 466 718 72 × 2 = 0 + 0.176 933 437 44;
  • 32) 0.176 933 437 44 × 2 = 0 + 0.353 866 874 88;
  • 33) 0.353 866 874 88 × 2 = 0 + 0.707 733 749 76;
  • 34) 0.707 733 749 76 × 2 = 1 + 0.415 467 499 52;
  • 35) 0.415 467 499 52 × 2 = 0 + 0.830 934 999 04;
  • 36) 0.830 934 999 04 × 2 = 1 + 0.661 869 998 08;
  • 37) 0.661 869 998 08 × 2 = 1 + 0.323 739 996 16;
  • 38) 0.323 739 996 16 × 2 = 0 + 0.647 479 992 32;
  • 39) 0.647 479 992 32 × 2 = 1 + 0.294 959 984 64;
  • 40) 0.294 959 984 64 × 2 = 0 + 0.589 919 969 28;
  • 41) 0.589 919 969 28 × 2 = 1 + 0.179 839 938 56;
  • 42) 0.179 839 938 56 × 2 = 0 + 0.359 679 877 12;
  • 43) 0.359 679 877 12 × 2 = 0 + 0.719 359 754 24;
  • 44) 0.719 359 754 24 × 2 = 1 + 0.438 719 508 48;
  • 45) 0.438 719 508 48 × 2 = 0 + 0.877 439 016 96;
  • 46) 0.877 439 016 96 × 2 = 1 + 0.754 878 033 92;
  • 47) 0.754 878 033 92 × 2 = 1 + 0.509 756 067 84;
  • 48) 0.509 756 067 84 × 2 = 1 + 0.019 512 135 68;
  • 49) 0.019 512 135 68 × 2 = 0 + 0.039 024 271 36;
  • 50) 0.039 024 271 36 × 2 = 0 + 0.078 048 542 72;
  • 51) 0.078 048 542 72 × 2 = 0 + 0.156 097 085 44;
  • 52) 0.156 097 085 44 × 2 = 0 + 0.312 194 170 88;
  • 53) 0.312 194 170 88 × 2 = 0 + 0.624 388 341 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:


0.000 000 611 03(10) =


0.0000 0000 0000 0000 0000 1010 0100 0000 0101 1010 1001 0111 0000 0(2)

5. Positive number before normalization:

2.000 000 611 03(10) =


10.0000 0000 0000 0000 0000 1010 0100 0000 0101 1010 1001 0111 0000 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:


2.000 000 611 03(10) =


10.0000 0000 0000 0000 0000 1010 0100 0000 0101 1010 1001 0111 0000 0(2) =


10.0000 0000 0000 0000 0000 1010 0100 0000 0101 1010 1001 0111 0000 0(2) × 20 =


1.0000 0000 0000 0000 0000 0101 0010 0000 0010 1101 0100 1011 1000 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):
1.0000 0000 0000 0000 0000 0101 0010 0000 0010 1101 0100 1011 1000 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. 0000 0000 0000 0000 0000 0101 0010 0000 0010 1101 0100 1011 1000 00 =


0000 0000 0000 0000 0000 0101 0010 0000 0010 1101 0100 1011 1000


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) =
0000 0000 0000 0000 0000 0101 0010 0000 0010 1101 0100 1011 1000


The base ten decimal number 2.000 000 611 03 converted and written in 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0000 - 0000 0000 0000 0000 0000 0101 0010 0000 0010 1101 0100 1011 1000

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