2.000 000 611 26 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.000 000 611 26(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
2.000 000 611 26(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: 0.000 000 611 26.

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 26 × 2 = 0 + 0.000 001 222 52;
  • 2) 0.000 001 222 52 × 2 = 0 + 0.000 002 445 04;
  • 3) 0.000 002 445 04 × 2 = 0 + 0.000 004 890 08;
  • 4) 0.000 004 890 08 × 2 = 0 + 0.000 009 780 16;
  • 5) 0.000 009 780 16 × 2 = 0 + 0.000 019 560 32;
  • 6) 0.000 019 560 32 × 2 = 0 + 0.000 039 120 64;
  • 7) 0.000 039 120 64 × 2 = 0 + 0.000 078 241 28;
  • 8) 0.000 078 241 28 × 2 = 0 + 0.000 156 482 56;
  • 9) 0.000 156 482 56 × 2 = 0 + 0.000 312 965 12;
  • 10) 0.000 312 965 12 × 2 = 0 + 0.000 625 930 24;
  • 11) 0.000 625 930 24 × 2 = 0 + 0.001 251 860 48;
  • 12) 0.001 251 860 48 × 2 = 0 + 0.002 503 720 96;
  • 13) 0.002 503 720 96 × 2 = 0 + 0.005 007 441 92;
  • 14) 0.005 007 441 92 × 2 = 0 + 0.010 014 883 84;
  • 15) 0.010 014 883 84 × 2 = 0 + 0.020 029 767 68;
  • 16) 0.020 029 767 68 × 2 = 0 + 0.040 059 535 36;
  • 17) 0.040 059 535 36 × 2 = 0 + 0.080 119 070 72;
  • 18) 0.080 119 070 72 × 2 = 0 + 0.160 238 141 44;
  • 19) 0.160 238 141 44 × 2 = 0 + 0.320 476 282 88;
  • 20) 0.320 476 282 88 × 2 = 0 + 0.640 952 565 76;
  • 21) 0.640 952 565 76 × 2 = 1 + 0.281 905 131 52;
  • 22) 0.281 905 131 52 × 2 = 0 + 0.563 810 263 04;
  • 23) 0.563 810 263 04 × 2 = 1 + 0.127 620 526 08;
  • 24) 0.127 620 526 08 × 2 = 0 + 0.255 241 052 16;
  • 25) 0.255 241 052 16 × 2 = 0 + 0.510 482 104 32;
  • 26) 0.510 482 104 32 × 2 = 1 + 0.020 964 208 64;
  • 27) 0.020 964 208 64 × 2 = 0 + 0.041 928 417 28;
  • 28) 0.041 928 417 28 × 2 = 0 + 0.083 856 834 56;
  • 29) 0.083 856 834 56 × 2 = 0 + 0.167 713 669 12;
  • 30) 0.167 713 669 12 × 2 = 0 + 0.335 427 338 24;
  • 31) 0.335 427 338 24 × 2 = 0 + 0.670 854 676 48;
  • 32) 0.670 854 676 48 × 2 = 1 + 0.341 709 352 96;
  • 33) 0.341 709 352 96 × 2 = 0 + 0.683 418 705 92;
  • 34) 0.683 418 705 92 × 2 = 1 + 0.366 837 411 84;
  • 35) 0.366 837 411 84 × 2 = 0 + 0.733 674 823 68;
  • 36) 0.733 674 823 68 × 2 = 1 + 0.467 349 647 36;
  • 37) 0.467 349 647 36 × 2 = 0 + 0.934 699 294 72;
  • 38) 0.934 699 294 72 × 2 = 1 + 0.869 398 589 44;
  • 39) 0.869 398 589 44 × 2 = 1 + 0.738 797 178 88;
  • 40) 0.738 797 178 88 × 2 = 1 + 0.477 594 357 76;
  • 41) 0.477 594 357 76 × 2 = 0 + 0.955 188 715 52;
  • 42) 0.955 188 715 52 × 2 = 1 + 0.910 377 431 04;
  • 43) 0.910 377 431 04 × 2 = 1 + 0.820 754 862 08;
  • 44) 0.820 754 862 08 × 2 = 1 + 0.641 509 724 16;
  • 45) 0.641 509 724 16 × 2 = 1 + 0.283 019 448 32;
  • 46) 0.283 019 448 32 × 2 = 0 + 0.566 038 896 64;
  • 47) 0.566 038 896 64 × 2 = 1 + 0.132 077 793 28;
  • 48) 0.132 077 793 28 × 2 = 0 + 0.264 155 586 56;
  • 49) 0.264 155 586 56 × 2 = 0 + 0.528 311 173 12;
  • 50) 0.528 311 173 12 × 2 = 1 + 0.056 622 346 24;
  • 51) 0.056 622 346 24 × 2 = 0 + 0.113 244 692 48;
  • 52) 0.113 244 692 48 × 2 = 0 + 0.226 489 384 96;
  • 53) 0.226 489 384 96 × 2 = 0 + 0.452 978 769 92;

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 26(10) =


0.0000 0000 0000 0000 0000 1010 0100 0001 0101 0111 0111 1010 0100 0(2)

5. Positive number before normalization:

2.000 000 611 26(10) =


10.0000 0000 0000 0000 0000 1010 0100 0001 0101 0111 0111 1010 0100 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 26(10) =


10.0000 0000 0000 0000 0000 1010 0100 0001 0101 0111 0111 1010 0100 0(2) =


10.0000 0000 0000 0000 0000 1010 0100 0001 0101 0111 0111 1010 0100 0(2) × 20 =


1.0000 0000 0000 0000 0000 0101 0010 0000 1010 1011 1011 1101 0010 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 1010 1011 1011 1101 0010 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 1010 1011 1011 1101 0010 00 =


0000 0000 0000 0000 0000 0101 0010 0000 1010 1011 1011 1101 0010


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 1010 1011 1011 1101 0010


Decimal number 2.000 000 611 26 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0000 - 0000 0000 0000 0000 0000 0101 0010 0000 1010 1011 1011 1101 0010


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