-80.298 375 123 481 38 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -80.298 375 123 481 38(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 38(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 38| = 80.298 375 123 481 38


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 38.

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 38 × 2 = 0 + 0.596 750 246 962 76;
  • 2) 0.596 750 246 962 76 × 2 = 1 + 0.193 500 493 925 52;
  • 3) 0.193 500 493 925 52 × 2 = 0 + 0.387 000 987 851 04;
  • 4) 0.387 000 987 851 04 × 2 = 0 + 0.774 001 975 702 08;
  • 5) 0.774 001 975 702 08 × 2 = 1 + 0.548 003 951 404 16;
  • 6) 0.548 003 951 404 16 × 2 = 1 + 0.096 007 902 808 32;
  • 7) 0.096 007 902 808 32 × 2 = 0 + 0.192 015 805 616 64;
  • 8) 0.192 015 805 616 64 × 2 = 0 + 0.384 031 611 233 28;
  • 9) 0.384 031 611 233 28 × 2 = 0 + 0.768 063 222 466 56;
  • 10) 0.768 063 222 466 56 × 2 = 1 + 0.536 126 444 933 12;
  • 11) 0.536 126 444 933 12 × 2 = 1 + 0.072 252 889 866 24;
  • 12) 0.072 252 889 866 24 × 2 = 0 + 0.144 505 779 732 48;
  • 13) 0.144 505 779 732 48 × 2 = 0 + 0.289 011 559 464 96;
  • 14) 0.289 011 559 464 96 × 2 = 0 + 0.578 023 118 929 92;
  • 15) 0.578 023 118 929 92 × 2 = 1 + 0.156 046 237 859 84;
  • 16) 0.156 046 237 859 84 × 2 = 0 + 0.312 092 475 719 68;
  • 17) 0.312 092 475 719 68 × 2 = 0 + 0.624 184 951 439 36;
  • 18) 0.624 184 951 439 36 × 2 = 1 + 0.248 369 902 878 72;
  • 19) 0.248 369 902 878 72 × 2 = 0 + 0.496 739 805 757 44;
  • 20) 0.496 739 805 757 44 × 2 = 0 + 0.993 479 611 514 88;
  • 21) 0.993 479 611 514 88 × 2 = 1 + 0.986 959 223 029 76;
  • 22) 0.986 959 223 029 76 × 2 = 1 + 0.973 918 446 059 52;
  • 23) 0.973 918 446 059 52 × 2 = 1 + 0.947 836 892 119 04;
  • 24) 0.947 836 892 119 04 × 2 = 1 + 0.895 673 784 238 08;
  • 25) 0.895 673 784 238 08 × 2 = 1 + 0.791 347 568 476 16;
  • 26) 0.791 347 568 476 16 × 2 = 1 + 0.582 695 136 952 32;
  • 27) 0.582 695 136 952 32 × 2 = 1 + 0.165 390 273 904 64;
  • 28) 0.165 390 273 904 64 × 2 = 0 + 0.330 780 547 809 28;
  • 29) 0.330 780 547 809 28 × 2 = 0 + 0.661 561 095 618 56;
  • 30) 0.661 561 095 618 56 × 2 = 1 + 0.323 122 191 237 12;
  • 31) 0.323 122 191 237 12 × 2 = 0 + 0.646 244 382 474 24;
  • 32) 0.646 244 382 474 24 × 2 = 1 + 0.292 488 764 948 48;
  • 33) 0.292 488 764 948 48 × 2 = 0 + 0.584 977 529 896 96;
  • 34) 0.584 977 529 896 96 × 2 = 1 + 0.169 955 059 793 92;
  • 35) 0.169 955 059 793 92 × 2 = 0 + 0.339 910 119 587 84;
  • 36) 0.339 910 119 587 84 × 2 = 0 + 0.679 820 239 175 68;
  • 37) 0.679 820 239 175 68 × 2 = 1 + 0.359 640 478 351 36;
  • 38) 0.359 640 478 351 36 × 2 = 0 + 0.719 280 956 702 72;
  • 39) 0.719 280 956 702 72 × 2 = 1 + 0.438 561 913 405 44;
  • 40) 0.438 561 913 405 44 × 2 = 0 + 0.877 123 826 810 88;
  • 41) 0.877 123 826 810 88 × 2 = 1 + 0.754 247 653 621 76;
  • 42) 0.754 247 653 621 76 × 2 = 1 + 0.508 495 307 243 52;
  • 43) 0.508 495 307 243 52 × 2 = 1 + 0.016 990 614 487 04;
  • 44) 0.016 990 614 487 04 × 2 = 0 + 0.033 981 228 974 08;
  • 45) 0.033 981 228 974 08 × 2 = 0 + 0.067 962 457 948 16;
  • 46) 0.067 962 457 948 16 × 2 = 0 + 0.135 924 915 896 32;
  • 47) 0.135 924 915 896 32 × 2 = 0 + 0.271 849 831 792 64;
  • 48) 0.271 849 831 792 64 × 2 = 0 + 0.543 699 663 585 28;
  • 49) 0.543 699 663 585 28 × 2 = 1 + 0.087 399 327 170 56;
  • 50) 0.087 399 327 170 56 × 2 = 0 + 0.174 798 654 341 12;
  • 51) 0.174 798 654 341 12 × 2 = 0 + 0.349 597 308 682 24;
  • 52) 0.349 597 308 682 24 × 2 = 0 + 0.699 194 617 364 48;
  • 53) 0.699 194 617 364 48 × 2 = 1 + 0.398 389 234 728 96;

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 38(10) =


0.0100 1100 0110 0010 0100 1111 1110 0101 0100 1010 1110 0000 1000 1(2)

6. Positive number before normalization:

80.298 375 123 481 38(10) =


101 0000.0100 1100 0110 0010 0100 1111 1110 0101 0100 1010 1110 0000 1000 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 38(10) =


101 0000.0100 1100 0110 0010 0100 1111 1110 0101 0100 1010 1110 0000 1000 1(2) =


101 0000.0100 1100 0110 0010 0100 1111 1110 0101 0100 1010 1110 0000 1000 1(2) × 20 =


1.0100 0001 0011 0001 1000 1001 0011 1111 1001 0101 0010 1011 1000 0010 001(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 1000 0010 001


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 1000 001 0001 =


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


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 1000


Decimal number -80.298 375 123 481 38 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 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