-1 302.123 456 789 012 395 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -1 302.123 456 789 012 395(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
-1 302.123 456 789 012 395(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:

|-1 302.123 456 789 012 395| = 1 302.123 456 789 012 395


2. First, convert to binary (in base 2) the integer part: 1 302.
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;
  • 1 302 ÷ 2 = 651 + 0;
  • 651 ÷ 2 = 325 + 1;
  • 325 ÷ 2 = 162 + 1;
  • 162 ÷ 2 = 81 + 0;
  • 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;

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.

1 302(10) =


101 0001 0110(2)


4. Convert to binary (base 2) the fractional part: 0.123 456 789 012 395.

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) 0.123 456 789 012 395 × 2 = 0 + 0.246 913 578 024 79;
  • 2) 0.246 913 578 024 79 × 2 = 0 + 0.493 827 156 049 58;
  • 3) 0.493 827 156 049 58 × 2 = 0 + 0.987 654 312 099 16;
  • 4) 0.987 654 312 099 16 × 2 = 1 + 0.975 308 624 198 32;
  • 5) 0.975 308 624 198 32 × 2 = 1 + 0.950 617 248 396 64;
  • 6) 0.950 617 248 396 64 × 2 = 1 + 0.901 234 496 793 28;
  • 7) 0.901 234 496 793 28 × 2 = 1 + 0.802 468 993 586 56;
  • 8) 0.802 468 993 586 56 × 2 = 1 + 0.604 937 987 173 12;
  • 9) 0.604 937 987 173 12 × 2 = 1 + 0.209 875 974 346 24;
  • 10) 0.209 875 974 346 24 × 2 = 0 + 0.419 751 948 692 48;
  • 11) 0.419 751 948 692 48 × 2 = 0 + 0.839 503 897 384 96;
  • 12) 0.839 503 897 384 96 × 2 = 1 + 0.679 007 794 769 92;
  • 13) 0.679 007 794 769 92 × 2 = 1 + 0.358 015 589 539 84;
  • 14) 0.358 015 589 539 84 × 2 = 0 + 0.716 031 179 079 68;
  • 15) 0.716 031 179 079 68 × 2 = 1 + 0.432 062 358 159 36;
  • 16) 0.432 062 358 159 36 × 2 = 0 + 0.864 124 716 318 72;
  • 17) 0.864 124 716 318 72 × 2 = 1 + 0.728 249 432 637 44;
  • 18) 0.728 249 432 637 44 × 2 = 1 + 0.456 498 865 274 88;
  • 19) 0.456 498 865 274 88 × 2 = 0 + 0.912 997 730 549 76;
  • 20) 0.912 997 730 549 76 × 2 = 1 + 0.825 995 461 099 52;
  • 21) 0.825 995 461 099 52 × 2 = 1 + 0.651 990 922 199 04;
  • 22) 0.651 990 922 199 04 × 2 = 1 + 0.303 981 844 398 08;
  • 23) 0.303 981 844 398 08 × 2 = 0 + 0.607 963 688 796 16;
  • 24) 0.607 963 688 796 16 × 2 = 1 + 0.215 927 377 592 32;
  • 25) 0.215 927 377 592 32 × 2 = 0 + 0.431 854 755 184 64;
  • 26) 0.431 854 755 184 64 × 2 = 0 + 0.863 709 510 369 28;
  • 27) 0.863 709 510 369 28 × 2 = 1 + 0.727 419 020 738 56;
  • 28) 0.727 419 020 738 56 × 2 = 1 + 0.454 838 041 477 12;
  • 29) 0.454 838 041 477 12 × 2 = 0 + 0.909 676 082 954 24;
  • 30) 0.909 676 082 954 24 × 2 = 1 + 0.819 352 165 908 48;
  • 31) 0.819 352 165 908 48 × 2 = 1 + 0.638 704 331 816 96;
  • 32) 0.638 704 331 816 96 × 2 = 1 + 0.277 408 663 633 92;
  • 33) 0.277 408 663 633 92 × 2 = 0 + 0.554 817 327 267 84;
  • 34) 0.554 817 327 267 84 × 2 = 1 + 0.109 634 654 535 68;
  • 35) 0.109 634 654 535 68 × 2 = 0 + 0.219 269 309 071 36;
  • 36) 0.219 269 309 071 36 × 2 = 0 + 0.438 538 618 142 72;
  • 37) 0.438 538 618 142 72 × 2 = 0 + 0.877 077 236 285 44;
  • 38) 0.877 077 236 285 44 × 2 = 1 + 0.754 154 472 570 88;
  • 39) 0.754 154 472 570 88 × 2 = 1 + 0.508 308 945 141 76;
  • 40) 0.508 308 945 141 76 × 2 = 1 + 0.016 617 890 283 52;
  • 41) 0.016 617 890 283 52 × 2 = 0 + 0.033 235 780 567 04;
  • 42) 0.033 235 780 567 04 × 2 = 0 + 0.066 471 561 134 08;
  • 43) 0.066 471 561 134 08 × 2 = 0 + 0.132 943 122 268 16;
  • 44) 0.132 943 122 268 16 × 2 = 0 + 0.265 886 244 536 32;
  • 45) 0.265 886 244 536 32 × 2 = 0 + 0.531 772 489 072 64;
  • 46) 0.531 772 489 072 64 × 2 = 1 + 0.063 544 978 145 28;
  • 47) 0.063 544 978 145 28 × 2 = 0 + 0.127 089 956 290 56;
  • 48) 0.127 089 956 290 56 × 2 = 0 + 0.254 179 912 581 12;
  • 49) 0.254 179 912 581 12 × 2 = 0 + 0.508 359 825 162 24;
  • 50) 0.508 359 825 162 24 × 2 = 1 + 0.016 719 650 324 48;
  • 51) 0.016 719 650 324 48 × 2 = 0 + 0.033 439 300 648 96;
  • 52) 0.033 439 300 648 96 × 2 = 0 + 0.066 878 601 297 92;
  • 53) 0.066 878 601 297 92 × 2 = 0 + 0.133 757 202 595 84;

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:


0.123 456 789 012 395(10) =


0.0001 1111 1001 1010 1101 1101 0011 0111 0100 0111 0000 0100 0100 0(2)

6. Positive number before normalization:

1 302.123 456 789 012 395(10) =


101 0001 0110.0001 1111 1001 1010 1101 1101 0011 0111 0100 0111 0000 0100 0100 0(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 10 positions to the left, so that only one non zero digit remains to the left of it:


1 302.123 456 789 012 395(10) =


101 0001 0110.0001 1111 1001 1010 1101 1101 0011 0111 0100 0111 0000 0100 0100 0(2) =


101 0001 0110.0001 1111 1001 1010 1101 1101 0011 0111 0100 0111 0000 0100 0100 0(2) × 20 =


1.0100 0101 1000 0111 1110 0110 1011 0111 0100 1101 1101 0001 1100 0001 0001 000(2) × 210


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): 10


Mantissa (not normalized):
1.0100 0101 1000 0111 1110 0110 1011 0111 0100 1101 1101 0001 1100 0001 0001 000


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


10 + 2(11-1) - 1 =


(10 + 1 023)(10) =


1 033(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;
  • 1 033 ÷ 2 = 516 + 1;
  • 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;

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) =


1033(10) =


100 0000 1001(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 0101 1000 0111 1110 0110 1011 0111 0100 1101 1101 0001 1100 000 1000 1000 =


0100 0101 1000 0111 1110 0110 1011 0111 0100 1101 1101 0001 1100


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 1001


Mantissa (52 bits) =
0100 0101 1000 0111 1110 0110 1011 0111 0100 1101 1101 0001 1100


Decimal number -1 302.123 456 789 012 395 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 100 0000 1001 - 0100 0101 1000 0111 1110 0110 1011 0111 0100 1101 1101 0001 1100


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