-1 302.123 456 789 012 343 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -1 302.123 456 789 012 343(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
-1 302.123 456 789 012 343(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:

|-1 302.123 456 789 012 343| = 1 302.123 456 789 012 343


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: 0.123 456 789 012 343.

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) 0.123 456 789 012 343 × 2 = 0 + 0.246 913 578 024 686;
  • 2) 0.246 913 578 024 686 × 2 = 0 + 0.493 827 156 049 372;
  • 3) 0.493 827 156 049 372 × 2 = 0 + 0.987 654 312 098 744;
  • 4) 0.987 654 312 098 744 × 2 = 1 + 0.975 308 624 197 488;
  • 5) 0.975 308 624 197 488 × 2 = 1 + 0.950 617 248 394 976;
  • 6) 0.950 617 248 394 976 × 2 = 1 + 0.901 234 496 789 952;
  • 7) 0.901 234 496 789 952 × 2 = 1 + 0.802 468 993 579 904;
  • 8) 0.802 468 993 579 904 × 2 = 1 + 0.604 937 987 159 808;
  • 9) 0.604 937 987 159 808 × 2 = 1 + 0.209 875 974 319 616;
  • 10) 0.209 875 974 319 616 × 2 = 0 + 0.419 751 948 639 232;
  • 11) 0.419 751 948 639 232 × 2 = 0 + 0.839 503 897 278 464;
  • 12) 0.839 503 897 278 464 × 2 = 1 + 0.679 007 794 556 928;
  • 13) 0.679 007 794 556 928 × 2 = 1 + 0.358 015 589 113 856;
  • 14) 0.358 015 589 113 856 × 2 = 0 + 0.716 031 178 227 712;
  • 15) 0.716 031 178 227 712 × 2 = 1 + 0.432 062 356 455 424;
  • 16) 0.432 062 356 455 424 × 2 = 0 + 0.864 124 712 910 848;
  • 17) 0.864 124 712 910 848 × 2 = 1 + 0.728 249 425 821 696;
  • 18) 0.728 249 425 821 696 × 2 = 1 + 0.456 498 851 643 392;
  • 19) 0.456 498 851 643 392 × 2 = 0 + 0.912 997 703 286 784;
  • 20) 0.912 997 703 286 784 × 2 = 1 + 0.825 995 406 573 568;
  • 21) 0.825 995 406 573 568 × 2 = 1 + 0.651 990 813 147 136;
  • 22) 0.651 990 813 147 136 × 2 = 1 + 0.303 981 626 294 272;
  • 23) 0.303 981 626 294 272 × 2 = 0 + 0.607 963 252 588 544;
  • 24) 0.607 963 252 588 544 × 2 = 1 + 0.215 926 505 177 088;
  • 25) 0.215 926 505 177 088 × 2 = 0 + 0.431 853 010 354 176;
  • 26) 0.431 853 010 354 176 × 2 = 0 + 0.863 706 020 708 352;
  • 27) 0.863 706 020 708 352 × 2 = 1 + 0.727 412 041 416 704;
  • 28) 0.727 412 041 416 704 × 2 = 1 + 0.454 824 082 833 408;
  • 29) 0.454 824 082 833 408 × 2 = 0 + 0.909 648 165 666 816;
  • 30) 0.909 648 165 666 816 × 2 = 1 + 0.819 296 331 333 632;
  • 31) 0.819 296 331 333 632 × 2 = 1 + 0.638 592 662 667 264;
  • 32) 0.638 592 662 667 264 × 2 = 1 + 0.277 185 325 334 528;
  • 33) 0.277 185 325 334 528 × 2 = 0 + 0.554 370 650 669 056;
  • 34) 0.554 370 650 669 056 × 2 = 1 + 0.108 741 301 338 112;
  • 35) 0.108 741 301 338 112 × 2 = 0 + 0.217 482 602 676 224;
  • 36) 0.217 482 602 676 224 × 2 = 0 + 0.434 965 205 352 448;
  • 37) 0.434 965 205 352 448 × 2 = 0 + 0.869 930 410 704 896;
  • 38) 0.869 930 410 704 896 × 2 = 1 + 0.739 860 821 409 792;
  • 39) 0.739 860 821 409 792 × 2 = 1 + 0.479 721 642 819 584;
  • 40) 0.479 721 642 819 584 × 2 = 0 + 0.959 443 285 639 168;
  • 41) 0.959 443 285 639 168 × 2 = 1 + 0.918 886 571 278 336;
  • 42) 0.918 886 571 278 336 × 2 = 1 + 0.837 773 142 556 672;
  • 43) 0.837 773 142 556 672 × 2 = 1 + 0.675 546 285 113 344;
  • 44) 0.675 546 285 113 344 × 2 = 1 + 0.351 092 570 226 688;
  • 45) 0.351 092 570 226 688 × 2 = 0 + 0.702 185 140 453 376;
  • 46) 0.702 185 140 453 376 × 2 = 1 + 0.404 370 280 906 752;
  • 47) 0.404 370 280 906 752 × 2 = 0 + 0.808 740 561 813 504;
  • 48) 0.808 740 561 813 504 × 2 = 1 + 0.617 481 123 627 008;
  • 49) 0.617 481 123 627 008 × 2 = 1 + 0.234 962 247 254 016;
  • 50) 0.234 962 247 254 016 × 2 = 0 + 0.469 924 494 508 032;
  • 51) 0.469 924 494 508 032 × 2 = 0 + 0.939 848 989 016 064;
  • 52) 0.939 848 989 016 064 × 2 = 1 + 0.879 697 978 032 128;
  • 53) 0.879 697 978 032 128 × 2 = 1 + 0.759 395 956 064 256;

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:


0.123 456 789 012 343(10) =


0.0001 1111 1001 1010 1101 1101 0011 0111 0100 0110 1111 0101 1001 1(2)

6. Positive number before normalization:

1 302.123 456 789 012 343(10) =


101 0001 0110.0001 1111 1001 1010 1101 1101 0011 0111 0100 0110 1111 0101 1001 1(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:


1 302.123 456 789 012 343(10) =


101 0001 0110.0001 1111 1001 1010 1101 1101 0011 0111 0100 0110 1111 0101 1001 1(2) =


101 0001 0110.0001 1111 1001 1010 1101 1101 0011 0111 0100 0110 1111 0101 1001 1(2) × 20 =


1.0100 0101 1000 0111 1110 0110 1011 0111 0100 1101 1101 0001 1011 1101 0110 011(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 1011 1101 0110 011


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 1011 110 1011 0011 =


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


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 1011


Decimal number -1 302.123 456 789 012 343 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 1011


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