13 781 290.158 489 992 759 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 13 781 290.158 489 992 759(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
13 781 290.158 489 992 759(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. First, convert to binary (in base 2) the integer part: 13 781 290.
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;
  • 13 781 290 ÷ 2 = 6 890 645 + 0;
  • 6 890 645 ÷ 2 = 3 445 322 + 1;
  • 3 445 322 ÷ 2 = 1 722 661 + 0;
  • 1 722 661 ÷ 2 = 861 330 + 1;
  • 861 330 ÷ 2 = 430 665 + 0;
  • 430 665 ÷ 2 = 215 332 + 1;
  • 215 332 ÷ 2 = 107 666 + 0;
  • 107 666 ÷ 2 = 53 833 + 0;
  • 53 833 ÷ 2 = 26 916 + 1;
  • 26 916 ÷ 2 = 13 458 + 0;
  • 13 458 ÷ 2 = 6 729 + 0;
  • 6 729 ÷ 2 = 3 364 + 1;
  • 3 364 ÷ 2 = 1 682 + 0;
  • 1 682 ÷ 2 = 841 + 0;
  • 841 ÷ 2 = 420 + 1;
  • 420 ÷ 2 = 210 + 0;
  • 210 ÷ 2 = 105 + 0;
  • 105 ÷ 2 = 52 + 1;
  • 52 ÷ 2 = 26 + 0;
  • 26 ÷ 2 = 13 + 0;
  • 13 ÷ 2 = 6 + 1;
  • 6 ÷ 2 = 3 + 0;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

2. 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.

13 781 290(10) =


1101 0010 0100 1001 0010 1010(2)


3. Convert to binary (base 2) the fractional part: 0.158 489 992 759.

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) 0.158 489 992 759 × 2 = 0 + 0.316 979 985 518;
  • 2) 0.316 979 985 518 × 2 = 0 + 0.633 959 971 036;
  • 3) 0.633 959 971 036 × 2 = 1 + 0.267 919 942 072;
  • 4) 0.267 919 942 072 × 2 = 0 + 0.535 839 884 144;
  • 5) 0.535 839 884 144 × 2 = 1 + 0.071 679 768 288;
  • 6) 0.071 679 768 288 × 2 = 0 + 0.143 359 536 576;
  • 7) 0.143 359 536 576 × 2 = 0 + 0.286 719 073 152;
  • 8) 0.286 719 073 152 × 2 = 0 + 0.573 438 146 304;
  • 9) 0.573 438 146 304 × 2 = 1 + 0.146 876 292 608;
  • 10) 0.146 876 292 608 × 2 = 0 + 0.293 752 585 216;
  • 11) 0.293 752 585 216 × 2 = 0 + 0.587 505 170 432;
  • 12) 0.587 505 170 432 × 2 = 1 + 0.175 010 340 864;
  • 13) 0.175 010 340 864 × 2 = 0 + 0.350 020 681 728;
  • 14) 0.350 020 681 728 × 2 = 0 + 0.700 041 363 456;
  • 15) 0.700 041 363 456 × 2 = 1 + 0.400 082 726 912;
  • 16) 0.400 082 726 912 × 2 = 0 + 0.800 165 453 824;
  • 17) 0.800 165 453 824 × 2 = 1 + 0.600 330 907 648;
  • 18) 0.600 330 907 648 × 2 = 1 + 0.200 661 815 296;
  • 19) 0.200 661 815 296 × 2 = 0 + 0.401 323 630 592;
  • 20) 0.401 323 630 592 × 2 = 0 + 0.802 647 261 184;
  • 21) 0.802 647 261 184 × 2 = 1 + 0.605 294 522 368;
  • 22) 0.605 294 522 368 × 2 = 1 + 0.210 589 044 736;
  • 23) 0.210 589 044 736 × 2 = 0 + 0.421 178 089 472;
  • 24) 0.421 178 089 472 × 2 = 0 + 0.842 356 178 944;
  • 25) 0.842 356 178 944 × 2 = 1 + 0.684 712 357 888;
  • 26) 0.684 712 357 888 × 2 = 1 + 0.369 424 715 776;
  • 27) 0.369 424 715 776 × 2 = 0 + 0.738 849 431 552;
  • 28) 0.738 849 431 552 × 2 = 1 + 0.477 698 863 104;
  • 29) 0.477 698 863 104 × 2 = 0 + 0.955 397 726 208;
  • 30) 0.955 397 726 208 × 2 = 1 + 0.910 795 452 416;
  • 31) 0.910 795 452 416 × 2 = 1 + 0.821 590 904 832;
  • 32) 0.821 590 904 832 × 2 = 1 + 0.643 181 809 664;
  • 33) 0.643 181 809 664 × 2 = 1 + 0.286 363 619 328;
  • 34) 0.286 363 619 328 × 2 = 0 + 0.572 727 238 656;
  • 35) 0.572 727 238 656 × 2 = 1 + 0.145 454 477 312;
  • 36) 0.145 454 477 312 × 2 = 0 + 0.290 908 954 624;
  • 37) 0.290 908 954 624 × 2 = 0 + 0.581 817 909 248;
  • 38) 0.581 817 909 248 × 2 = 1 + 0.163 635 818 496;
  • 39) 0.163 635 818 496 × 2 = 0 + 0.327 271 636 992;
  • 40) 0.327 271 636 992 × 2 = 0 + 0.654 543 273 984;
  • 41) 0.654 543 273 984 × 2 = 1 + 0.309 086 547 968;
  • 42) 0.309 086 547 968 × 2 = 0 + 0.618 173 095 936;
  • 43) 0.618 173 095 936 × 2 = 1 + 0.236 346 191 872;
  • 44) 0.236 346 191 872 × 2 = 0 + 0.472 692 383 744;
  • 45) 0.472 692 383 744 × 2 = 0 + 0.945 384 767 488;
  • 46) 0.945 384 767 488 × 2 = 1 + 0.890 769 534 976;
  • 47) 0.890 769 534 976 × 2 = 1 + 0.781 539 069 952;
  • 48) 0.781 539 069 952 × 2 = 1 + 0.563 078 139 904;
  • 49) 0.563 078 139 904 × 2 = 1 + 0.126 156 279 808;
  • 50) 0.126 156 279 808 × 2 = 0 + 0.252 312 559 616;
  • 51) 0.252 312 559 616 × 2 = 0 + 0.504 625 119 232;
  • 52) 0.504 625 119 232 × 2 = 1 + 0.009 250 238 464;
  • 53) 0.009 250 238 464 × 2 = 0 + 0.018 500 476 928;

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).


4. 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:


0.158 489 992 759(10) =


0.0010 1000 1001 0010 1100 1100 1101 0111 1010 0100 1010 0111 1001 0(2)

5. Positive number before normalization:

13 781 290.158 489 992 759(10) =


1101 0010 0100 1001 0010 1010.0010 1000 1001 0010 1100 1100 1101 0111 1010 0100 1010 0111 1001 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 23 positions to the left, so that only one non zero digit remains to the left of it:


13 781 290.158 489 992 759(10) =


1101 0010 0100 1001 0010 1010.0010 1000 1001 0010 1100 1100 1101 0111 1010 0100 1010 0111 1001 0(2) =


1101 0010 0100 1001 0010 1010.0010 1000 1001 0010 1100 1100 1101 0111 1010 0100 1010 0111 1001 0(2) × 20 =


1.1010 0100 1001 0010 0101 0100 0101 0001 0010 0101 1001 1001 1010 1111 0100 1001 0100 1111 0010(2) × 223


7. 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 0 (a positive number)


Exponent (unadjusted): 23


Mantissa (not normalized):
1.1010 0100 1001 0010 0101 0100 0101 0001 0010 0101 1001 1001 1010 1111 0100 1001 0100 1111 0010


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


23 + 2(11-1) - 1 =


(23 + 1 023)(10) =


1 046(10)


9. 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;
  • 1 046 ÷ 2 = 523 + 0;
  • 523 ÷ 2 = 261 + 1;
  • 261 ÷ 2 = 130 + 1;
  • 130 ÷ 2 = 65 + 0;
  • 65 ÷ 2 = 32 + 1;
  • 32 ÷ 2 = 16 + 0;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

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

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


Exponent (adjusted) =


1046(10) =


100 0001 0110(2)


11. 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. 1010 0100 1001 0010 0101 0100 0101 0001 0010 0101 1001 1001 1010 1111 0100 1001 0100 1111 0010 =


1010 0100 1001 0010 0101 0100 0101 0001 0010 0101 1001 1001 1010


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

Sign (1 bit) =
0 (a positive number)


Exponent (11 bits) =
100 0001 0110


Mantissa (52 bits) =
1010 0100 1001 0010 0101 0100 0101 0001 0010 0101 1001 1001 1010


Decimal number 13 781 290.158 489 992 759 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0001 0110 - 1010 0100 1001 0010 0101 0100 0101 0001 0010 0101 1001 1001 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