64bit IEEE 754: Decimal ↗ Double Precision Floating Point Binary: 8 108 783 922 821 464 053 Convert the Number to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From a Base Ten Decimal System Number

Number 8 108 783 922 821 464 053(10) converted and written in 64 bit double precision IEEE 754 binary floating point representation (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

1. 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;
  • 8 108 783 922 821 464 053 ÷ 2 = 4 054 391 961 410 732 026 + 1;
  • 4 054 391 961 410 732 026 ÷ 2 = 2 027 195 980 705 366 013 + 0;
  • 2 027 195 980 705 366 013 ÷ 2 = 1 013 597 990 352 683 006 + 1;
  • 1 013 597 990 352 683 006 ÷ 2 = 506 798 995 176 341 503 + 0;
  • 506 798 995 176 341 503 ÷ 2 = 253 399 497 588 170 751 + 1;
  • 253 399 497 588 170 751 ÷ 2 = 126 699 748 794 085 375 + 1;
  • 126 699 748 794 085 375 ÷ 2 = 63 349 874 397 042 687 + 1;
  • 63 349 874 397 042 687 ÷ 2 = 31 674 937 198 521 343 + 1;
  • 31 674 937 198 521 343 ÷ 2 = 15 837 468 599 260 671 + 1;
  • 15 837 468 599 260 671 ÷ 2 = 7 918 734 299 630 335 + 1;
  • 7 918 734 299 630 335 ÷ 2 = 3 959 367 149 815 167 + 1;
  • 3 959 367 149 815 167 ÷ 2 = 1 979 683 574 907 583 + 1;
  • 1 979 683 574 907 583 ÷ 2 = 989 841 787 453 791 + 1;
  • 989 841 787 453 791 ÷ 2 = 494 920 893 726 895 + 1;
  • 494 920 893 726 895 ÷ 2 = 247 460 446 863 447 + 1;
  • 247 460 446 863 447 ÷ 2 = 123 730 223 431 723 + 1;
  • 123 730 223 431 723 ÷ 2 = 61 865 111 715 861 + 1;
  • 61 865 111 715 861 ÷ 2 = 30 932 555 857 930 + 1;
  • 30 932 555 857 930 ÷ 2 = 15 466 277 928 965 + 0;
  • 15 466 277 928 965 ÷ 2 = 7 733 138 964 482 + 1;
  • 7 733 138 964 482 ÷ 2 = 3 866 569 482 241 + 0;
  • 3 866 569 482 241 ÷ 2 = 1 933 284 741 120 + 1;
  • 1 933 284 741 120 ÷ 2 = 966 642 370 560 + 0;
  • 966 642 370 560 ÷ 2 = 483 321 185 280 + 0;
  • 483 321 185 280 ÷ 2 = 241 660 592 640 + 0;
  • 241 660 592 640 ÷ 2 = 120 830 296 320 + 0;
  • 120 830 296 320 ÷ 2 = 60 415 148 160 + 0;
  • 60 415 148 160 ÷ 2 = 30 207 574 080 + 0;
  • 30 207 574 080 ÷ 2 = 15 103 787 040 + 0;
  • 15 103 787 040 ÷ 2 = 7 551 893 520 + 0;
  • 7 551 893 520 ÷ 2 = 3 775 946 760 + 0;
  • 3 775 946 760 ÷ 2 = 1 887 973 380 + 0;
  • 1 887 973 380 ÷ 2 = 943 986 690 + 0;
  • 943 986 690 ÷ 2 = 471 993 345 + 0;
  • 471 993 345 ÷ 2 = 235 996 672 + 1;
  • 235 996 672 ÷ 2 = 117 998 336 + 0;
  • 117 998 336 ÷ 2 = 58 999 168 + 0;
  • 58 999 168 ÷ 2 = 29 499 584 + 0;
  • 29 499 584 ÷ 2 = 14 749 792 + 0;
  • 14 749 792 ÷ 2 = 7 374 896 + 0;
  • 7 374 896 ÷ 2 = 3 687 448 + 0;
  • 3 687 448 ÷ 2 = 1 843 724 + 0;
  • 1 843 724 ÷ 2 = 921 862 + 0;
  • 921 862 ÷ 2 = 460 931 + 0;
  • 460 931 ÷ 2 = 230 465 + 1;
  • 230 465 ÷ 2 = 115 232 + 1;
  • 115 232 ÷ 2 = 57 616 + 0;
  • 57 616 ÷ 2 = 28 808 + 0;
  • 28 808 ÷ 2 = 14 404 + 0;
  • 14 404 ÷ 2 = 7 202 + 0;
  • 7 202 ÷ 2 = 3 601 + 0;
  • 3 601 ÷ 2 = 1 800 + 1;
  • 1 800 ÷ 2 = 900 + 0;
  • 900 ÷ 2 = 450 + 0;
  • 450 ÷ 2 = 225 + 0;
  • 225 ÷ 2 = 112 + 1;
  • 112 ÷ 2 = 56 + 0;
  • 56 ÷ 2 = 28 + 0;
  • 28 ÷ 2 = 14 + 0;
  • 14 ÷ 2 = 7 + 0;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

2. Construct the base 2 representation of the positive number.

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


8 108 783 922 821 464 053(10) =


111 0000 1000 1000 0011 0000 0000 0100 0000 0000 0010 1011 1111 1111 1111 0101(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 62 positions to the left, so that only one non zero digit remains to the left of it:


8 108 783 922 821 464 053(10) =


111 0000 1000 1000 0011 0000 0000 0100 0000 0000 0010 1011 1111 1111 1111 0101(2) =


111 0000 1000 1000 0011 0000 0000 0100 0000 0000 0010 1011 1111 1111 1111 0101(2) × 20 =


1.1100 0010 0010 0000 1100 0000 0001 0000 0000 0000 1010 1111 1111 1111 1101 01(2) × 262


4. 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): 62


Mantissa (not normalized):
1.1100 0010 0010 0000 1100 0000 0001 0000 0000 0000 1010 1111 1111 1111 1101 01


5. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


62 + 2(11-1) - 1 =


(62 + 1 023)(10) =


1 085(10)


6. 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;
  • 1 085 ÷ 2 = 542 + 1;
  • 542 ÷ 2 = 271 + 0;
  • 271 ÷ 2 = 135 + 1;
  • 135 ÷ 2 = 67 + 1;
  • 67 ÷ 2 = 33 + 1;
  • 33 ÷ 2 = 16 + 1;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

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

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


Exponent (adjusted) =


1085(10) =


100 0011 1101(2)


8. 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. 1100 0010 0010 0000 1100 0000 0001 0000 0000 0000 1010 1111 1111 11 1111 0101 =


1100 0010 0010 0000 1100 0000 0001 0000 0000 0000 1010 1111 1111


9. 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 0011 1101


Mantissa (52 bits) =
1100 0010 0010 0000 1100 0000 0001 0000 0000 0000 1010 1111 1111


The base ten decimal number 8 108 783 922 821 464 053 converted and written in 64 bit double precision IEEE 754 binary floating point representation:
0 - 100 0011 1101 - 1100 0010 0010 0000 1100 0000 0001 0000 0000 0000 1010 1111 1111

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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