654.600 000 000 000 14 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 654.600 000 000 000 14(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
654.600 000 000 000 14(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: 654.
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;
  • 654 ÷ 2 = 327 + 0;
  • 327 ÷ 2 = 163 + 1;
  • 163 ÷ 2 = 81 + 1;
  • 81 ÷ 2 = 40 + 1;
  • 40 ÷ 2 = 20 + 0;
  • 20 ÷ 2 = 10 + 0;
  • 10 ÷ 2 = 5 + 0;
  • 5 ÷ 2 = 2 + 1;
  • 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.

654(10) =


10 1000 1110(2)


3. Convert to binary (base 2) the fractional part: 0.600 000 000 000 14.

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) 0.600 000 000 000 14 × 2 = 1 + 0.200 000 000 000 28;
  • 2) 0.200 000 000 000 28 × 2 = 0 + 0.400 000 000 000 56;
  • 3) 0.400 000 000 000 56 × 2 = 0 + 0.800 000 000 001 12;
  • 4) 0.800 000 000 001 12 × 2 = 1 + 0.600 000 000 002 24;
  • 5) 0.600 000 000 002 24 × 2 = 1 + 0.200 000 000 004 48;
  • 6) 0.200 000 000 004 48 × 2 = 0 + 0.400 000 000 008 96;
  • 7) 0.400 000 000 008 96 × 2 = 0 + 0.800 000 000 017 92;
  • 8) 0.800 000 000 017 92 × 2 = 1 + 0.600 000 000 035 84;
  • 9) 0.600 000 000 035 84 × 2 = 1 + 0.200 000 000 071 68;
  • 10) 0.200 000 000 071 68 × 2 = 0 + 0.400 000 000 143 36;
  • 11) 0.400 000 000 143 36 × 2 = 0 + 0.800 000 000 286 72;
  • 12) 0.800 000 000 286 72 × 2 = 1 + 0.600 000 000 573 44;
  • 13) 0.600 000 000 573 44 × 2 = 1 + 0.200 000 001 146 88;
  • 14) 0.200 000 001 146 88 × 2 = 0 + 0.400 000 002 293 76;
  • 15) 0.400 000 002 293 76 × 2 = 0 + 0.800 000 004 587 52;
  • 16) 0.800 000 004 587 52 × 2 = 1 + 0.600 000 009 175 04;
  • 17) 0.600 000 009 175 04 × 2 = 1 + 0.200 000 018 350 08;
  • 18) 0.200 000 018 350 08 × 2 = 0 + 0.400 000 036 700 16;
  • 19) 0.400 000 036 700 16 × 2 = 0 + 0.800 000 073 400 32;
  • 20) 0.800 000 073 400 32 × 2 = 1 + 0.600 000 146 800 64;
  • 21) 0.600 000 146 800 64 × 2 = 1 + 0.200 000 293 601 28;
  • 22) 0.200 000 293 601 28 × 2 = 0 + 0.400 000 587 202 56;
  • 23) 0.400 000 587 202 56 × 2 = 0 + 0.800 001 174 405 12;
  • 24) 0.800 001 174 405 12 × 2 = 1 + 0.600 002 348 810 24;
  • 25) 0.600 002 348 810 24 × 2 = 1 + 0.200 004 697 620 48;
  • 26) 0.200 004 697 620 48 × 2 = 0 + 0.400 009 395 240 96;
  • 27) 0.400 009 395 240 96 × 2 = 0 + 0.800 018 790 481 92;
  • 28) 0.800 018 790 481 92 × 2 = 1 + 0.600 037 580 963 84;
  • 29) 0.600 037 580 963 84 × 2 = 1 + 0.200 075 161 927 68;
  • 30) 0.200 075 161 927 68 × 2 = 0 + 0.400 150 323 855 36;
  • 31) 0.400 150 323 855 36 × 2 = 0 + 0.800 300 647 710 72;
  • 32) 0.800 300 647 710 72 × 2 = 1 + 0.600 601 295 421 44;
  • 33) 0.600 601 295 421 44 × 2 = 1 + 0.201 202 590 842 88;
  • 34) 0.201 202 590 842 88 × 2 = 0 + 0.402 405 181 685 76;
  • 35) 0.402 405 181 685 76 × 2 = 0 + 0.804 810 363 371 52;
  • 36) 0.804 810 363 371 52 × 2 = 1 + 0.609 620 726 743 04;
  • 37) 0.609 620 726 743 04 × 2 = 1 + 0.219 241 453 486 08;
  • 38) 0.219 241 453 486 08 × 2 = 0 + 0.438 482 906 972 16;
  • 39) 0.438 482 906 972 16 × 2 = 0 + 0.876 965 813 944 32;
  • 40) 0.876 965 813 944 32 × 2 = 1 + 0.753 931 627 888 64;
  • 41) 0.753 931 627 888 64 × 2 = 1 + 0.507 863 255 777 28;
  • 42) 0.507 863 255 777 28 × 2 = 1 + 0.015 726 511 554 56;
  • 43) 0.015 726 511 554 56 × 2 = 0 + 0.031 453 023 109 12;
  • 44) 0.031 453 023 109 12 × 2 = 0 + 0.062 906 046 218 24;
  • 45) 0.062 906 046 218 24 × 2 = 0 + 0.125 812 092 436 48;
  • 46) 0.125 812 092 436 48 × 2 = 0 + 0.251 624 184 872 96;
  • 47) 0.251 624 184 872 96 × 2 = 0 + 0.503 248 369 745 92;
  • 48) 0.503 248 369 745 92 × 2 = 1 + 0.006 496 739 491 84;
  • 49) 0.006 496 739 491 84 × 2 = 0 + 0.012 993 478 983 68;
  • 50) 0.012 993 478 983 68 × 2 = 0 + 0.025 986 957 967 36;
  • 51) 0.025 986 957 967 36 × 2 = 0 + 0.051 973 915 934 72;
  • 52) 0.051 973 915 934 72 × 2 = 0 + 0.103 947 831 869 44;
  • 53) 0.103 947 831 869 44 × 2 = 0 + 0.207 895 663 738 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:


0.600 000 000 000 14(10) =


0.1001 1001 1001 1001 1001 1001 1001 1001 1001 1001 1100 0001 0000 0(2)

5. Positive number before normalization:

654.600 000 000 000 14(10) =


10 1000 1110.1001 1001 1001 1001 1001 1001 1001 1001 1001 1001 1100 0001 0000 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 9 positions to the left, so that only one non zero digit remains to the left of it:


654.600 000 000 000 14(10) =


10 1000 1110.1001 1001 1001 1001 1001 1001 1001 1001 1001 1001 1100 0001 0000 0(2) =


10 1000 1110.1001 1001 1001 1001 1001 1001 1001 1001 1001 1001 1100 0001 0000 0(2) × 20 =


1.0100 0111 0100 1100 1100 1100 1100 1100 1100 1100 1100 1100 1110 0000 1000 00(2) × 29


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): 9


Mantissa (not normalized):
1.0100 0111 0100 1100 1100 1100 1100 1100 1100 1100 1100 1100 1110 0000 1000 00


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(11-1) - 1 =


9 + 2(11-1) - 1 =


(9 + 1 023)(10) =


1 032(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;
  • 1 032 ÷ 2 = 516 + 0;
  • 516 ÷ 2 = 258 + 0;
  • 258 ÷ 2 = 129 + 0;
  • 129 ÷ 2 = 64 + 1;
  • 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) =


1032(10) =


100 0000 1000(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. 0100 0111 0100 1100 1100 1100 1100 1100 1100 1100 1100 1100 1110 00 0010 0000 =


0100 0111 0100 1100 1100 1100 1100 1100 1100 1100 1100 1100 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 1000


Mantissa (52 bits) =
0100 0111 0100 1100 1100 1100 1100 1100 1100 1100 1100 1100 1110


Decimal number 654.600 000 000 000 14 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 1000 - 0100 0111 0100 1100 1100 1100 1100 1100 1100 1100 1100 1100 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