-1 302.123 456 789 012 425 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -1 302.123 456 789 012 425(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
-1 302.123 456 789 012 425(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:

|-1 302.123 456 789 012 425| = 1 302.123 456 789 012 425


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: 0.123 456 789 012 425.

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) 0.123 456 789 012 425 × 2 = 0 + 0.246 913 578 024 85;
  • 2) 0.246 913 578 024 85 × 2 = 0 + 0.493 827 156 049 7;
  • 3) 0.493 827 156 049 7 × 2 = 0 + 0.987 654 312 099 4;
  • 4) 0.987 654 312 099 4 × 2 = 1 + 0.975 308 624 198 8;
  • 5) 0.975 308 624 198 8 × 2 = 1 + 0.950 617 248 397 6;
  • 6) 0.950 617 248 397 6 × 2 = 1 + 0.901 234 496 795 2;
  • 7) 0.901 234 496 795 2 × 2 = 1 + 0.802 468 993 590 4;
  • 8) 0.802 468 993 590 4 × 2 = 1 + 0.604 937 987 180 8;
  • 9) 0.604 937 987 180 8 × 2 = 1 + 0.209 875 974 361 6;
  • 10) 0.209 875 974 361 6 × 2 = 0 + 0.419 751 948 723 2;
  • 11) 0.419 751 948 723 2 × 2 = 0 + 0.839 503 897 446 4;
  • 12) 0.839 503 897 446 4 × 2 = 1 + 0.679 007 794 892 8;
  • 13) 0.679 007 794 892 8 × 2 = 1 + 0.358 015 589 785 6;
  • 14) 0.358 015 589 785 6 × 2 = 0 + 0.716 031 179 571 2;
  • 15) 0.716 031 179 571 2 × 2 = 1 + 0.432 062 359 142 4;
  • 16) 0.432 062 359 142 4 × 2 = 0 + 0.864 124 718 284 8;
  • 17) 0.864 124 718 284 8 × 2 = 1 + 0.728 249 436 569 6;
  • 18) 0.728 249 436 569 6 × 2 = 1 + 0.456 498 873 139 2;
  • 19) 0.456 498 873 139 2 × 2 = 0 + 0.912 997 746 278 4;
  • 20) 0.912 997 746 278 4 × 2 = 1 + 0.825 995 492 556 8;
  • 21) 0.825 995 492 556 8 × 2 = 1 + 0.651 990 985 113 6;
  • 22) 0.651 990 985 113 6 × 2 = 1 + 0.303 981 970 227 2;
  • 23) 0.303 981 970 227 2 × 2 = 0 + 0.607 963 940 454 4;
  • 24) 0.607 963 940 454 4 × 2 = 1 + 0.215 927 880 908 8;
  • 25) 0.215 927 880 908 8 × 2 = 0 + 0.431 855 761 817 6;
  • 26) 0.431 855 761 817 6 × 2 = 0 + 0.863 711 523 635 2;
  • 27) 0.863 711 523 635 2 × 2 = 1 + 0.727 423 047 270 4;
  • 28) 0.727 423 047 270 4 × 2 = 1 + 0.454 846 094 540 8;
  • 29) 0.454 846 094 540 8 × 2 = 0 + 0.909 692 189 081 6;
  • 30) 0.909 692 189 081 6 × 2 = 1 + 0.819 384 378 163 2;
  • 31) 0.819 384 378 163 2 × 2 = 1 + 0.638 768 756 326 4;
  • 32) 0.638 768 756 326 4 × 2 = 1 + 0.277 537 512 652 8;
  • 33) 0.277 537 512 652 8 × 2 = 0 + 0.555 075 025 305 6;
  • 34) 0.555 075 025 305 6 × 2 = 1 + 0.110 150 050 611 2;
  • 35) 0.110 150 050 611 2 × 2 = 0 + 0.220 300 101 222 4;
  • 36) 0.220 300 101 222 4 × 2 = 0 + 0.440 600 202 444 8;
  • 37) 0.440 600 202 444 8 × 2 = 0 + 0.881 200 404 889 6;
  • 38) 0.881 200 404 889 6 × 2 = 1 + 0.762 400 809 779 2;
  • 39) 0.762 400 809 779 2 × 2 = 1 + 0.524 801 619 558 4;
  • 40) 0.524 801 619 558 4 × 2 = 1 + 0.049 603 239 116 8;
  • 41) 0.049 603 239 116 8 × 2 = 0 + 0.099 206 478 233 6;
  • 42) 0.099 206 478 233 6 × 2 = 0 + 0.198 412 956 467 2;
  • 43) 0.198 412 956 467 2 × 2 = 0 + 0.396 825 912 934 4;
  • 44) 0.396 825 912 934 4 × 2 = 0 + 0.793 651 825 868 8;
  • 45) 0.793 651 825 868 8 × 2 = 1 + 0.587 303 651 737 6;
  • 46) 0.587 303 651 737 6 × 2 = 1 + 0.174 607 303 475 2;
  • 47) 0.174 607 303 475 2 × 2 = 0 + 0.349 214 606 950 4;
  • 48) 0.349 214 606 950 4 × 2 = 0 + 0.698 429 213 900 8;
  • 49) 0.698 429 213 900 8 × 2 = 1 + 0.396 858 427 801 6;
  • 50) 0.396 858 427 801 6 × 2 = 0 + 0.793 716 855 603 2;
  • 51) 0.793 716 855 603 2 × 2 = 1 + 0.587 433 711 206 4;
  • 52) 0.587 433 711 206 4 × 2 = 1 + 0.174 867 422 412 8;
  • 53) 0.174 867 422 412 8 × 2 = 0 + 0.349 734 844 825 6;

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:


0.123 456 789 012 425(10) =


0.0001 1111 1001 1010 1101 1101 0011 0111 0100 0111 0000 1100 1011 0(2)

6. Positive number before normalization:

1 302.123 456 789 012 425(10) =


101 0001 0110.0001 1111 1001 1010 1101 1101 0011 0111 0100 0111 0000 1100 1011 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:


1 302.123 456 789 012 425(10) =


101 0001 0110.0001 1111 1001 1010 1101 1101 0011 0111 0100 0111 0000 1100 1011 0(2) =


101 0001 0110.0001 1111 1001 1010 1101 1101 0011 0111 0100 0111 0000 1100 1011 0(2) × 20 =


1.0100 0101 1000 0111 1110 0110 1011 0111 0100 1101 1101 0001 1100 0011 0010 110(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 0011 0010 110


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 001 1001 0110 =


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 -1 302.123 456 789 012 425 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