9 876 543 210 009 876.009 234 567 8 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 9 876 543 210 009 876.009 234 567 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
9 876 543 210 009 876.009 234 567 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: 0.009 234 567 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) 0.009 234 567 8 × 2 = 0 + 0.018 469 135 6;
  • 2) 0.018 469 135 6 × 2 = 0 + 0.036 938 271 2;
  • 3) 0.036 938 271 2 × 2 = 0 + 0.073 876 542 4;
  • 4) 0.073 876 542 4 × 2 = 0 + 0.147 753 084 8;
  • 5) 0.147 753 084 8 × 2 = 0 + 0.295 506 169 6;
  • 6) 0.295 506 169 6 × 2 = 0 + 0.591 012 339 2;
  • 7) 0.591 012 339 2 × 2 = 1 + 0.182 024 678 4;
  • 8) 0.182 024 678 4 × 2 = 0 + 0.364 049 356 8;
  • 9) 0.364 049 356 8 × 2 = 0 + 0.728 098 713 6;
  • 10) 0.728 098 713 6 × 2 = 1 + 0.456 197 427 2;
  • 11) 0.456 197 427 2 × 2 = 0 + 0.912 394 854 4;
  • 12) 0.912 394 854 4 × 2 = 1 + 0.824 789 708 8;
  • 13) 0.824 789 708 8 × 2 = 1 + 0.649 579 417 6;
  • 14) 0.649 579 417 6 × 2 = 1 + 0.299 158 835 2;
  • 15) 0.299 158 835 2 × 2 = 0 + 0.598 317 670 4;
  • 16) 0.598 317 670 4 × 2 = 1 + 0.196 635 340 8;
  • 17) 0.196 635 340 8 × 2 = 0 + 0.393 270 681 6;
  • 18) 0.393 270 681 6 × 2 = 0 + 0.786 541 363 2;
  • 19) 0.786 541 363 2 × 2 = 1 + 0.573 082 726 4;
  • 20) 0.573 082 726 4 × 2 = 1 + 0.146 165 452 8;
  • 21) 0.146 165 452 8 × 2 = 0 + 0.292 330 905 6;
  • 22) 0.292 330 905 6 × 2 = 0 + 0.584 661 811 2;
  • 23) 0.584 661 811 2 × 2 = 1 + 0.169 323 622 4;
  • 24) 0.169 323 622 4 × 2 = 0 + 0.338 647 244 8;
  • 25) 0.338 647 244 8 × 2 = 0 + 0.677 294 489 6;
  • 26) 0.677 294 489 6 × 2 = 1 + 0.354 588 979 2;
  • 27) 0.354 588 979 2 × 2 = 0 + 0.709 177 958 4;
  • 28) 0.709 177 958 4 × 2 = 1 + 0.418 355 916 8;
  • 29) 0.418 355 916 8 × 2 = 0 + 0.836 711 833 6;
  • 30) 0.836 711 833 6 × 2 = 1 + 0.673 423 667 2;
  • 31) 0.673 423 667 2 × 2 = 1 + 0.346 847 334 4;
  • 32) 0.346 847 334 4 × 2 = 0 + 0.693 694 668 8;
  • 33) 0.693 694 668 8 × 2 = 1 + 0.387 389 337 6;
  • 34) 0.387 389 337 6 × 2 = 0 + 0.774 778 675 2;
  • 35) 0.774 778 675 2 × 2 = 1 + 0.549 557 350 4;
  • 36) 0.549 557 350 4 × 2 = 1 + 0.099 114 700 8;
  • 37) 0.099 114 700 8 × 2 = 0 + 0.198 229 401 6;
  • 38) 0.198 229 401 6 × 2 = 0 + 0.396 458 803 2;
  • 39) 0.396 458 803 2 × 2 = 0 + 0.792 917 606 4;
  • 40) 0.792 917 606 4 × 2 = 1 + 0.585 835 212 8;
  • 41) 0.585 835 212 8 × 2 = 1 + 0.171 670 425 6;
  • 42) 0.171 670 425 6 × 2 = 0 + 0.343 340 851 2;
  • 43) 0.343 340 851 2 × 2 = 0 + 0.686 681 702 4;
  • 44) 0.686 681 702 4 × 2 = 1 + 0.373 363 404 8;
  • 45) 0.373 363 404 8 × 2 = 0 + 0.746 726 809 6;
  • 46) 0.746 726 809 6 × 2 = 1 + 0.493 453 619 2;
  • 47) 0.493 453 619 2 × 2 = 0 + 0.986 907 238 4;
  • 48) 0.986 907 238 4 × 2 = 1 + 0.973 814 476 8;
  • 49) 0.973 814 476 8 × 2 = 1 + 0.947 628 953 6;
  • 50) 0.947 628 953 6 × 2 = 1 + 0.895 257 907 2;
  • 51) 0.895 257 907 2 × 2 = 1 + 0.790 515 814 4;
  • 52) 0.790 515 814 4 × 2 = 1 + 0.581 031 628 8;
  • 53) 0.581 031 628 8 × 2 = 1 + 0.162 063 257 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:


0.009 234 567 8(10) =


0.0000 0010 0101 1101 0011 0010 0101 0110 1011 0001 1001 0101 1111 1(2)

5. Positive number before normalization:

9 876 543 210 009 876.009 234 567 8(10) =


10 0011 0001 0110 1010 1001 1110 1001 1010 0100 0011 0101 0001 0100.0000 0010 0101 1101 0011 0010 0101 0110 1011 0001 1001 0101 1111 1(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:


9 876 543 210 009 876.009 234 567 8(10) =


10 0011 0001 0110 1010 1001 1110 1001 1010 0100 0011 0101 0001 0100.0000 0010 0101 1101 0011 0010 0101 0110 1011 0001 1001 0101 1111 1(2) =


10 0011 0001 0110 1010 1001 1110 1001 1010 0100 0011 0101 0001 0100.0000 0010 0101 1101 0011 0010 0101 0110 1011 0001 1001 0101 1111 1(2) × 20 =


1.0001 1000 1011 0101 0100 1111 0100 1101 0010 0001 1010 1000 1010 0000 0001 0010 1110 1001 1001 0010 1011 0101 1000 1100 1010 1111 11(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 1011 0101 1000 1100 1010 1111 11


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 1010 1101 0110 0011 0010 1011 1111 =


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 9 876 543 210 009 876.009 234 567 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