2.000 000 610 64 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.000 000 610 64(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
2.000 000 610 64(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: 0.000 000 610 64.

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) 0.000 000 610 64 × 2 = 0 + 0.000 001 221 28;
  • 2) 0.000 001 221 28 × 2 = 0 + 0.000 002 442 56;
  • 3) 0.000 002 442 56 × 2 = 0 + 0.000 004 885 12;
  • 4) 0.000 004 885 12 × 2 = 0 + 0.000 009 770 24;
  • 5) 0.000 009 770 24 × 2 = 0 + 0.000 019 540 48;
  • 6) 0.000 019 540 48 × 2 = 0 + 0.000 039 080 96;
  • 7) 0.000 039 080 96 × 2 = 0 + 0.000 078 161 92;
  • 8) 0.000 078 161 92 × 2 = 0 + 0.000 156 323 84;
  • 9) 0.000 156 323 84 × 2 = 0 + 0.000 312 647 68;
  • 10) 0.000 312 647 68 × 2 = 0 + 0.000 625 295 36;
  • 11) 0.000 625 295 36 × 2 = 0 + 0.001 250 590 72;
  • 12) 0.001 250 590 72 × 2 = 0 + 0.002 501 181 44;
  • 13) 0.002 501 181 44 × 2 = 0 + 0.005 002 362 88;
  • 14) 0.005 002 362 88 × 2 = 0 + 0.010 004 725 76;
  • 15) 0.010 004 725 76 × 2 = 0 + 0.020 009 451 52;
  • 16) 0.020 009 451 52 × 2 = 0 + 0.040 018 903 04;
  • 17) 0.040 018 903 04 × 2 = 0 + 0.080 037 806 08;
  • 18) 0.080 037 806 08 × 2 = 0 + 0.160 075 612 16;
  • 19) 0.160 075 612 16 × 2 = 0 + 0.320 151 224 32;
  • 20) 0.320 151 224 32 × 2 = 0 + 0.640 302 448 64;
  • 21) 0.640 302 448 64 × 2 = 1 + 0.280 604 897 28;
  • 22) 0.280 604 897 28 × 2 = 0 + 0.561 209 794 56;
  • 23) 0.561 209 794 56 × 2 = 1 + 0.122 419 589 12;
  • 24) 0.122 419 589 12 × 2 = 0 + 0.244 839 178 24;
  • 25) 0.244 839 178 24 × 2 = 0 + 0.489 678 356 48;
  • 26) 0.489 678 356 48 × 2 = 0 + 0.979 356 712 96;
  • 27) 0.979 356 712 96 × 2 = 1 + 0.958 713 425 92;
  • 28) 0.958 713 425 92 × 2 = 1 + 0.917 426 851 84;
  • 29) 0.917 426 851 84 × 2 = 1 + 0.834 853 703 68;
  • 30) 0.834 853 703 68 × 2 = 1 + 0.669 707 407 36;
  • 31) 0.669 707 407 36 × 2 = 1 + 0.339 414 814 72;
  • 32) 0.339 414 814 72 × 2 = 0 + 0.678 829 629 44;
  • 33) 0.678 829 629 44 × 2 = 1 + 0.357 659 258 88;
  • 34) 0.357 659 258 88 × 2 = 0 + 0.715 318 517 76;
  • 35) 0.715 318 517 76 × 2 = 1 + 0.430 637 035 52;
  • 36) 0.430 637 035 52 × 2 = 0 + 0.861 274 071 04;
  • 37) 0.861 274 071 04 × 2 = 1 + 0.722 548 142 08;
  • 38) 0.722 548 142 08 × 2 = 1 + 0.445 096 284 16;
  • 39) 0.445 096 284 16 × 2 = 0 + 0.890 192 568 32;
  • 40) 0.890 192 568 32 × 2 = 1 + 0.780 385 136 64;
  • 41) 0.780 385 136 64 × 2 = 1 + 0.560 770 273 28;
  • 42) 0.560 770 273 28 × 2 = 1 + 0.121 540 546 56;
  • 43) 0.121 540 546 56 × 2 = 0 + 0.243 081 093 12;
  • 44) 0.243 081 093 12 × 2 = 0 + 0.486 162 186 24;
  • 45) 0.486 162 186 24 × 2 = 0 + 0.972 324 372 48;
  • 46) 0.972 324 372 48 × 2 = 1 + 0.944 648 744 96;
  • 47) 0.944 648 744 96 × 2 = 1 + 0.889 297 489 92;
  • 48) 0.889 297 489 92 × 2 = 1 + 0.778 594 979 84;
  • 49) 0.778 594 979 84 × 2 = 1 + 0.557 189 959 68;
  • 50) 0.557 189 959 68 × 2 = 1 + 0.114 379 919 36;
  • 51) 0.114 379 919 36 × 2 = 0 + 0.228 759 838 72;
  • 52) 0.228 759 838 72 × 2 = 0 + 0.457 519 677 44;
  • 53) 0.457 519 677 44 × 2 = 0 + 0.915 039 354 88;

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:


0.000 000 610 64(10) =


0.0000 0000 0000 0000 0000 1010 0011 1110 1010 1101 1100 0111 1100 0(2)

5. Positive number before normalization:

2.000 000 610 64(10) =


10.0000 0000 0000 0000 0000 1010 0011 1110 1010 1101 1100 0111 1100 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:


2.000 000 610 64(10) =


10.0000 0000 0000 0000 0000 1010 0011 1110 1010 1101 1100 0111 1100 0(2) =


10.0000 0000 0000 0000 0000 1010 0011 1110 1010 1101 1100 0111 1100 0(2) × 20 =


1.0000 0000 0000 0000 0000 0101 0001 1111 0101 0110 1110 0011 1110 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 0001 1111 0101 0110 1110 0011 1110 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 0001 1111 0101 0110 1110 0011 1110 00 =


0000 0000 0000 0000 0000 0101 0001 1111 0101 0110 1110 0011 1110


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 0001 1111 0101 0110 1110 0011 1110


Decimal number 2.000 000 610 64 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0000 - 0000 0000 0000 0000 0000 0101 0001 1111 0101 0110 1110 0011 1110


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