-80.298 375 123 481 41 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -80.298 375 123 481 41(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
-80.298 375 123 481 41(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. Start with the positive version of the number:

|-80.298 375 123 481 41| = 80.298 375 123 481 41


2. First, convert to binary (in base 2) the integer part: 80.
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;
  • 80 ÷ 2 = 40 + 0;
  • 40 ÷ 2 = 20 + 0;
  • 20 ÷ 2 = 10 + 0;
  • 10 ÷ 2 = 5 + 0;
  • 5 ÷ 2 = 2 + 1;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

3. 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.

80(10) =


101 0000(2)


4. Convert to binary (base 2) the fractional part: 0.298 375 123 481 41.

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) 0.298 375 123 481 41 × 2 = 0 + 0.596 750 246 962 82;
  • 2) 0.596 750 246 962 82 × 2 = 1 + 0.193 500 493 925 64;
  • 3) 0.193 500 493 925 64 × 2 = 0 + 0.387 000 987 851 28;
  • 4) 0.387 000 987 851 28 × 2 = 0 + 0.774 001 975 702 56;
  • 5) 0.774 001 975 702 56 × 2 = 1 + 0.548 003 951 405 12;
  • 6) 0.548 003 951 405 12 × 2 = 1 + 0.096 007 902 810 24;
  • 7) 0.096 007 902 810 24 × 2 = 0 + 0.192 015 805 620 48;
  • 8) 0.192 015 805 620 48 × 2 = 0 + 0.384 031 611 240 96;
  • 9) 0.384 031 611 240 96 × 2 = 0 + 0.768 063 222 481 92;
  • 10) 0.768 063 222 481 92 × 2 = 1 + 0.536 126 444 963 84;
  • 11) 0.536 126 444 963 84 × 2 = 1 + 0.072 252 889 927 68;
  • 12) 0.072 252 889 927 68 × 2 = 0 + 0.144 505 779 855 36;
  • 13) 0.144 505 779 855 36 × 2 = 0 + 0.289 011 559 710 72;
  • 14) 0.289 011 559 710 72 × 2 = 0 + 0.578 023 119 421 44;
  • 15) 0.578 023 119 421 44 × 2 = 1 + 0.156 046 238 842 88;
  • 16) 0.156 046 238 842 88 × 2 = 0 + 0.312 092 477 685 76;
  • 17) 0.312 092 477 685 76 × 2 = 0 + 0.624 184 955 371 52;
  • 18) 0.624 184 955 371 52 × 2 = 1 + 0.248 369 910 743 04;
  • 19) 0.248 369 910 743 04 × 2 = 0 + 0.496 739 821 486 08;
  • 20) 0.496 739 821 486 08 × 2 = 0 + 0.993 479 642 972 16;
  • 21) 0.993 479 642 972 16 × 2 = 1 + 0.986 959 285 944 32;
  • 22) 0.986 959 285 944 32 × 2 = 1 + 0.973 918 571 888 64;
  • 23) 0.973 918 571 888 64 × 2 = 1 + 0.947 837 143 777 28;
  • 24) 0.947 837 143 777 28 × 2 = 1 + 0.895 674 287 554 56;
  • 25) 0.895 674 287 554 56 × 2 = 1 + 0.791 348 575 109 12;
  • 26) 0.791 348 575 109 12 × 2 = 1 + 0.582 697 150 218 24;
  • 27) 0.582 697 150 218 24 × 2 = 1 + 0.165 394 300 436 48;
  • 28) 0.165 394 300 436 48 × 2 = 0 + 0.330 788 600 872 96;
  • 29) 0.330 788 600 872 96 × 2 = 0 + 0.661 577 201 745 92;
  • 30) 0.661 577 201 745 92 × 2 = 1 + 0.323 154 403 491 84;
  • 31) 0.323 154 403 491 84 × 2 = 0 + 0.646 308 806 983 68;
  • 32) 0.646 308 806 983 68 × 2 = 1 + 0.292 617 613 967 36;
  • 33) 0.292 617 613 967 36 × 2 = 0 + 0.585 235 227 934 72;
  • 34) 0.585 235 227 934 72 × 2 = 1 + 0.170 470 455 869 44;
  • 35) 0.170 470 455 869 44 × 2 = 0 + 0.340 940 911 738 88;
  • 36) 0.340 940 911 738 88 × 2 = 0 + 0.681 881 823 477 76;
  • 37) 0.681 881 823 477 76 × 2 = 1 + 0.363 763 646 955 52;
  • 38) 0.363 763 646 955 52 × 2 = 0 + 0.727 527 293 911 04;
  • 39) 0.727 527 293 911 04 × 2 = 1 + 0.455 054 587 822 08;
  • 40) 0.455 054 587 822 08 × 2 = 0 + 0.910 109 175 644 16;
  • 41) 0.910 109 175 644 16 × 2 = 1 + 0.820 218 351 288 32;
  • 42) 0.820 218 351 288 32 × 2 = 1 + 0.640 436 702 576 64;
  • 43) 0.640 436 702 576 64 × 2 = 1 + 0.280 873 405 153 28;
  • 44) 0.280 873 405 153 28 × 2 = 0 + 0.561 746 810 306 56;
  • 45) 0.561 746 810 306 56 × 2 = 1 + 0.123 493 620 613 12;
  • 46) 0.123 493 620 613 12 × 2 = 0 + 0.246 987 241 226 24;
  • 47) 0.246 987 241 226 24 × 2 = 0 + 0.493 974 482 452 48;
  • 48) 0.493 974 482 452 48 × 2 = 0 + 0.987 948 964 904 96;
  • 49) 0.987 948 964 904 96 × 2 = 1 + 0.975 897 929 809 92;
  • 50) 0.975 897 929 809 92 × 2 = 1 + 0.951 795 859 619 84;
  • 51) 0.951 795 859 619 84 × 2 = 1 + 0.903 591 719 239 68;
  • 52) 0.903 591 719 239 68 × 2 = 1 + 0.807 183 438 479 36;
  • 53) 0.807 183 438 479 36 × 2 = 1 + 0.614 366 876 958 72;

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).


5. 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:


0.298 375 123 481 41(10) =


0.0100 1100 0110 0010 0100 1111 1110 0101 0100 1010 1110 1000 1111 1(2)

6. Positive number before normalization:

80.298 375 123 481 41(10) =


101 0000.0100 1100 0110 0010 0100 1111 1110 0101 0100 1010 1110 1000 1111 1(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 6 positions to the left, so that only one non zero digit remains to the left of it:


80.298 375 123 481 41(10) =


101 0000.0100 1100 0110 0010 0100 1111 1110 0101 0100 1010 1110 1000 1111 1(2) =


101 0000.0100 1100 0110 0010 0100 1111 1110 0101 0100 1010 1110 1000 1111 1(2) × 20 =


1.0100 0001 0011 0001 1000 1001 0011 1111 1001 0101 0010 1011 1010 0011 111(2) × 26


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): 6


Mantissa (not normalized):
1.0100 0001 0011 0001 1000 1001 0011 1111 1001 0101 0010 1011 1010 0011 111


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


6 + 2(11-1) - 1 =


(6 + 1 023)(10) =


1 029(10)


10. 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;
  • 1 029 ÷ 2 = 514 + 1;
  • 514 ÷ 2 = 257 + 0;
  • 257 ÷ 2 = 128 + 1;
  • 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;

11. Construct the base 2 representation of the adjusted exponent.

Take all the remainders starting from the bottom of the list constructed above.


Exponent (adjusted) =


1029(10) =


100 0000 0101(2)


12. 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 0001 0011 0001 1000 1001 0011 1111 1001 0101 0010 1011 1010 001 1111 =


0100 0001 0011 0001 1000 1001 0011 1111 1001 0101 0010 1011 1010


13. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

Sign (1 bit) =
1 (a negative number)


Exponent (11 bits) =
100 0000 0101


Mantissa (52 bits) =
0100 0001 0011 0001 1000 1001 0011 1111 1001 0101 0010 1011 1010


Decimal number -80.298 375 123 481 41 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 100 0000 0101 - 0100 0001 0011 0001 1000 1001 0011 1111 1001 0101 0010 1011 1010

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