9 876 543 210 009 876.009 234 568 8 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 9 876 543 210 009 876.009 234 568 8(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
9 876 543 210 009 876.009 234 568 8(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: 9 876 543 210 009 876.
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;
  • 9 876 543 210 009 876 ÷ 2 = 4 938 271 605 004 938 + 0;
  • 4 938 271 605 004 938 ÷ 2 = 2 469 135 802 502 469 + 0;
  • 2 469 135 802 502 469 ÷ 2 = 1 234 567 901 251 234 + 1;
  • 1 234 567 901 251 234 ÷ 2 = 617 283 950 625 617 + 0;
  • 617 283 950 625 617 ÷ 2 = 308 641 975 312 808 + 1;
  • 308 641 975 312 808 ÷ 2 = 154 320 987 656 404 + 0;
  • 154 320 987 656 404 ÷ 2 = 77 160 493 828 202 + 0;
  • 77 160 493 828 202 ÷ 2 = 38 580 246 914 101 + 0;
  • 38 580 246 914 101 ÷ 2 = 19 290 123 457 050 + 1;
  • 19 290 123 457 050 ÷ 2 = 9 645 061 728 525 + 0;
  • 9 645 061 728 525 ÷ 2 = 4 822 530 864 262 + 1;
  • 4 822 530 864 262 ÷ 2 = 2 411 265 432 131 + 0;
  • 2 411 265 432 131 ÷ 2 = 1 205 632 716 065 + 1;
  • 1 205 632 716 065 ÷ 2 = 602 816 358 032 + 1;
  • 602 816 358 032 ÷ 2 = 301 408 179 016 + 0;
  • 301 408 179 016 ÷ 2 = 150 704 089 508 + 0;
  • 150 704 089 508 ÷ 2 = 75 352 044 754 + 0;
  • 75 352 044 754 ÷ 2 = 37 676 022 377 + 0;
  • 37 676 022 377 ÷ 2 = 18 838 011 188 + 1;
  • 18 838 011 188 ÷ 2 = 9 419 005 594 + 0;
  • 9 419 005 594 ÷ 2 = 4 709 502 797 + 0;
  • 4 709 502 797 ÷ 2 = 2 354 751 398 + 1;
  • 2 354 751 398 ÷ 2 = 1 177 375 699 + 0;
  • 1 177 375 699 ÷ 2 = 588 687 849 + 1;
  • 588 687 849 ÷ 2 = 294 343 924 + 1;
  • 294 343 924 ÷ 2 = 147 171 962 + 0;
  • 147 171 962 ÷ 2 = 73 585 981 + 0;
  • 73 585 981 ÷ 2 = 36 792 990 + 1;
  • 36 792 990 ÷ 2 = 18 396 495 + 0;
  • 18 396 495 ÷ 2 = 9 198 247 + 1;
  • 9 198 247 ÷ 2 = 4 599 123 + 1;
  • 4 599 123 ÷ 2 = 2 299 561 + 1;
  • 2 299 561 ÷ 2 = 1 149 780 + 1;
  • 1 149 780 ÷ 2 = 574 890 + 0;
  • 574 890 ÷ 2 = 287 445 + 0;
  • 287 445 ÷ 2 = 143 722 + 1;
  • 143 722 ÷ 2 = 71 861 + 0;
  • 71 861 ÷ 2 = 35 930 + 1;
  • 35 930 ÷ 2 = 17 965 + 0;
  • 17 965 ÷ 2 = 8 982 + 1;
  • 8 982 ÷ 2 = 4 491 + 0;
  • 4 491 ÷ 2 = 2 245 + 1;
  • 2 245 ÷ 2 = 1 122 + 1;
  • 1 122 ÷ 2 = 561 + 0;
  • 561 ÷ 2 = 280 + 1;
  • 280 ÷ 2 = 140 + 0;
  • 140 ÷ 2 = 70 + 0;
  • 70 ÷ 2 = 35 + 0;
  • 35 ÷ 2 = 17 + 1;
  • 17 ÷ 2 = 8 + 1;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 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.

9 876 543 210 009 876(10) =


10 0011 0001 0110 1010 1001 1110 1001 1010 0100 0011 0101 0001 0100(2)


3. Convert to binary (base 2) the fractional part: 0.009 234 568 8.

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) 0.009 234 568 8 × 2 = 0 + 0.018 469 137 6;
  • 2) 0.018 469 137 6 × 2 = 0 + 0.036 938 275 2;
  • 3) 0.036 938 275 2 × 2 = 0 + 0.073 876 550 4;
  • 4) 0.073 876 550 4 × 2 = 0 + 0.147 753 100 8;
  • 5) 0.147 753 100 8 × 2 = 0 + 0.295 506 201 6;
  • 6) 0.295 506 201 6 × 2 = 0 + 0.591 012 403 2;
  • 7) 0.591 012 403 2 × 2 = 1 + 0.182 024 806 4;
  • 8) 0.182 024 806 4 × 2 = 0 + 0.364 049 612 8;
  • 9) 0.364 049 612 8 × 2 = 0 + 0.728 099 225 6;
  • 10) 0.728 099 225 6 × 2 = 1 + 0.456 198 451 2;
  • 11) 0.456 198 451 2 × 2 = 0 + 0.912 396 902 4;
  • 12) 0.912 396 902 4 × 2 = 1 + 0.824 793 804 8;
  • 13) 0.824 793 804 8 × 2 = 1 + 0.649 587 609 6;
  • 14) 0.649 587 609 6 × 2 = 1 + 0.299 175 219 2;
  • 15) 0.299 175 219 2 × 2 = 0 + 0.598 350 438 4;
  • 16) 0.598 350 438 4 × 2 = 1 + 0.196 700 876 8;
  • 17) 0.196 700 876 8 × 2 = 0 + 0.393 401 753 6;
  • 18) 0.393 401 753 6 × 2 = 0 + 0.786 803 507 2;
  • 19) 0.786 803 507 2 × 2 = 1 + 0.573 607 014 4;
  • 20) 0.573 607 014 4 × 2 = 1 + 0.147 214 028 8;
  • 21) 0.147 214 028 8 × 2 = 0 + 0.294 428 057 6;
  • 22) 0.294 428 057 6 × 2 = 0 + 0.588 856 115 2;
  • 23) 0.588 856 115 2 × 2 = 1 + 0.177 712 230 4;
  • 24) 0.177 712 230 4 × 2 = 0 + 0.355 424 460 8;
  • 25) 0.355 424 460 8 × 2 = 0 + 0.710 848 921 6;
  • 26) 0.710 848 921 6 × 2 = 1 + 0.421 697 843 2;
  • 27) 0.421 697 843 2 × 2 = 0 + 0.843 395 686 4;
  • 28) 0.843 395 686 4 × 2 = 1 + 0.686 791 372 8;
  • 29) 0.686 791 372 8 × 2 = 1 + 0.373 582 745 6;
  • 30) 0.373 582 745 6 × 2 = 0 + 0.747 165 491 2;
  • 31) 0.747 165 491 2 × 2 = 1 + 0.494 330 982 4;
  • 32) 0.494 330 982 4 × 2 = 0 + 0.988 661 964 8;
  • 33) 0.988 661 964 8 × 2 = 1 + 0.977 323 929 6;
  • 34) 0.977 323 929 6 × 2 = 1 + 0.954 647 859 2;
  • 35) 0.954 647 859 2 × 2 = 1 + 0.909 295 718 4;
  • 36) 0.909 295 718 4 × 2 = 1 + 0.818 591 436 8;
  • 37) 0.818 591 436 8 × 2 = 1 + 0.637 182 873 6;
  • 38) 0.637 182 873 6 × 2 = 1 + 0.274 365 747 2;
  • 39) 0.274 365 747 2 × 2 = 0 + 0.548 731 494 4;
  • 40) 0.548 731 494 4 × 2 = 1 + 0.097 462 988 8;
  • 41) 0.097 462 988 8 × 2 = 0 + 0.194 925 977 6;
  • 42) 0.194 925 977 6 × 2 = 0 + 0.389 851 955 2;
  • 43) 0.389 851 955 2 × 2 = 0 + 0.779 703 910 4;
  • 44) 0.779 703 910 4 × 2 = 1 + 0.559 407 820 8;
  • 45) 0.559 407 820 8 × 2 = 1 + 0.118 815 641 6;
  • 46) 0.118 815 641 6 × 2 = 0 + 0.237 631 283 2;
  • 47) 0.237 631 283 2 × 2 = 0 + 0.475 262 566 4;
  • 48) 0.475 262 566 4 × 2 = 0 + 0.950 525 132 8;
  • 49) 0.950 525 132 8 × 2 = 1 + 0.901 050 265 6;
  • 50) 0.901 050 265 6 × 2 = 1 + 0.802 100 531 2;
  • 51) 0.802 100 531 2 × 2 = 1 + 0.604 201 062 4;
  • 52) 0.604 201 062 4 × 2 = 1 + 0.208 402 124 8;
  • 53) 0.208 402 124 8 × 2 = 0 + 0.416 804 249 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).


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:


0.009 234 568 8(10) =


0.0000 0010 0101 1101 0011 0010 0101 1010 1111 1101 0001 1000 1111 0(2)

5. Positive number before normalization:

9 876 543 210 009 876.009 234 568 8(10) =


10 0011 0001 0110 1010 1001 1110 1001 1010 0100 0011 0101 0001 0100.0000 0010 0101 1101 0011 0010 0101 1010 1111 1101 0001 1000 1111 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 53 positions to the left, so that only one non zero digit remains to the left of it:


9 876 543 210 009 876.009 234 568 8(10) =


10 0011 0001 0110 1010 1001 1110 1001 1010 0100 0011 0101 0001 0100.0000 0010 0101 1101 0011 0010 0101 1010 1111 1101 0001 1000 1111 0(2) =


10 0011 0001 0110 1010 1001 1110 1001 1010 0100 0011 0101 0001 0100.0000 0010 0101 1101 0011 0010 0101 1010 1111 1101 0001 1000 1111 0(2) × 20 =


1.0001 1000 1011 0101 0100 1111 0100 1101 0010 0001 1010 1000 1010 0000 0001 0010 1110 1001 1001 0010 1101 0111 1110 1000 1100 0111 10(2) × 253


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): 53


Mantissa (not normalized):
1.0001 1000 1011 0101 0100 1111 0100 1101 0010 0001 1010 1000 1010 0000 0001 0010 1110 1001 1001 0010 1101 0111 1110 1000 1100 0111 10


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


53 + 2(11-1) - 1 =


(53 + 1 023)(10) =


1 076(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;
  • 1 076 ÷ 2 = 538 + 0;
  • 538 ÷ 2 = 269 + 0;
  • 269 ÷ 2 = 134 + 1;
  • 134 ÷ 2 = 67 + 0;
  • 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;

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) =


1076(10) =


100 0011 0100(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. 0001 1000 1011 0101 0100 1111 0100 1101 0010 0001 1010 1000 1010 00 0000 0100 1011 1010 0110 0100 1011 0101 1111 1010 0011 0001 1110 =


0001 1000 1011 0101 0100 1111 0100 1101 0010 0001 1010 1000 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 0011 0100


Mantissa (52 bits) =
0001 1000 1011 0101 0100 1111 0100 1101 0010 0001 1010 1000 1010


Decimal number 9 876 543 210 009 876.009 234 568 8 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0011 0100 - 0001 1000 1011 0101 0100 1111 0100 1101 0010 0001 1010 1000 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