Decimal to 64 Bit IEEE 754 Binary: Convert Number 2 823 704 568 289 406 756 to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From Base Ten Decimal System

Number 2 823 704 568 289 406 756(10) converted and written in 64 bit double precision IEEE 754 binary floating point representation standard (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;
  • 2 823 704 568 289 406 756 ÷ 2 = 1 411 852 284 144 703 378 + 0;
  • 1 411 852 284 144 703 378 ÷ 2 = 705 926 142 072 351 689 + 0;
  • 705 926 142 072 351 689 ÷ 2 = 352 963 071 036 175 844 + 1;
  • 352 963 071 036 175 844 ÷ 2 = 176 481 535 518 087 922 + 0;
  • 176 481 535 518 087 922 ÷ 2 = 88 240 767 759 043 961 + 0;
  • 88 240 767 759 043 961 ÷ 2 = 44 120 383 879 521 980 + 1;
  • 44 120 383 879 521 980 ÷ 2 = 22 060 191 939 760 990 + 0;
  • 22 060 191 939 760 990 ÷ 2 = 11 030 095 969 880 495 + 0;
  • 11 030 095 969 880 495 ÷ 2 = 5 515 047 984 940 247 + 1;
  • 5 515 047 984 940 247 ÷ 2 = 2 757 523 992 470 123 + 1;
  • 2 757 523 992 470 123 ÷ 2 = 1 378 761 996 235 061 + 1;
  • 1 378 761 996 235 061 ÷ 2 = 689 380 998 117 530 + 1;
  • 689 380 998 117 530 ÷ 2 = 344 690 499 058 765 + 0;
  • 344 690 499 058 765 ÷ 2 = 172 345 249 529 382 + 1;
  • 172 345 249 529 382 ÷ 2 = 86 172 624 764 691 + 0;
  • 86 172 624 764 691 ÷ 2 = 43 086 312 382 345 + 1;
  • 43 086 312 382 345 ÷ 2 = 21 543 156 191 172 + 1;
  • 21 543 156 191 172 ÷ 2 = 10 771 578 095 586 + 0;
  • 10 771 578 095 586 ÷ 2 = 5 385 789 047 793 + 0;
  • 5 385 789 047 793 ÷ 2 = 2 692 894 523 896 + 1;
  • 2 692 894 523 896 ÷ 2 = 1 346 447 261 948 + 0;
  • 1 346 447 261 948 ÷ 2 = 673 223 630 974 + 0;
  • 673 223 630 974 ÷ 2 = 336 611 815 487 + 0;
  • 336 611 815 487 ÷ 2 = 168 305 907 743 + 1;
  • 168 305 907 743 ÷ 2 = 84 152 953 871 + 1;
  • 84 152 953 871 ÷ 2 = 42 076 476 935 + 1;
  • 42 076 476 935 ÷ 2 = 21 038 238 467 + 1;
  • 21 038 238 467 ÷ 2 = 10 519 119 233 + 1;
  • 10 519 119 233 ÷ 2 = 5 259 559 616 + 1;
  • 5 259 559 616 ÷ 2 = 2 629 779 808 + 0;
  • 2 629 779 808 ÷ 2 = 1 314 889 904 + 0;
  • 1 314 889 904 ÷ 2 = 657 444 952 + 0;
  • 657 444 952 ÷ 2 = 328 722 476 + 0;
  • 328 722 476 ÷ 2 = 164 361 238 + 0;
  • 164 361 238 ÷ 2 = 82 180 619 + 0;
  • 82 180 619 ÷ 2 = 41 090 309 + 1;
  • 41 090 309 ÷ 2 = 20 545 154 + 1;
  • 20 545 154 ÷ 2 = 10 272 577 + 0;
  • 10 272 577 ÷ 2 = 5 136 288 + 1;
  • 5 136 288 ÷ 2 = 2 568 144 + 0;
  • 2 568 144 ÷ 2 = 1 284 072 + 0;
  • 1 284 072 ÷ 2 = 642 036 + 0;
  • 642 036 ÷ 2 = 321 018 + 0;
  • 321 018 ÷ 2 = 160 509 + 0;
  • 160 509 ÷ 2 = 80 254 + 1;
  • 80 254 ÷ 2 = 40 127 + 0;
  • 40 127 ÷ 2 = 20 063 + 1;
  • 20 063 ÷ 2 = 10 031 + 1;
  • 10 031 ÷ 2 = 5 015 + 1;
  • 5 015 ÷ 2 = 2 507 + 1;
  • 2 507 ÷ 2 = 1 253 + 1;
  • 1 253 ÷ 2 = 626 + 1;
  • 626 ÷ 2 = 313 + 0;
  • 313 ÷ 2 = 156 + 1;
  • 156 ÷ 2 = 78 + 0;
  • 78 ÷ 2 = 39 + 0;
  • 39 ÷ 2 = 19 + 1;
  • 19 ÷ 2 = 9 + 1;
  • 9 ÷ 2 = 4 + 1;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 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.

2 823 704 568 289 406 756(10) =


10 0111 0010 1111 1101 0000 0101 1000 0001 1111 1000 1001 1010 1111 0010 0100(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 61 positions to the left, so that only one non zero digit remains to the left of it:


2 823 704 568 289 406 756(10) =


10 0111 0010 1111 1101 0000 0101 1000 0001 1111 1000 1001 1010 1111 0010 0100(2) =


10 0111 0010 1111 1101 0000 0101 1000 0001 1111 1000 1001 1010 1111 0010 0100(2) × 20 =


1.0011 1001 0111 1110 1000 0010 1100 0000 1111 1100 0100 1101 0111 1001 0010 0(2) × 261


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): 61


Mantissa (not normalized):
1.0011 1001 0111 1110 1000 0010 1100 0000 1111 1100 0100 1101 0111 1001 0010 0


5. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


61 + 2(11-1) - 1 =


(61 + 1 023)(10) =


1 084(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;
  • 1 084 ÷ 2 = 542 + 0;
  • 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) =


1084(10) =


100 0011 1100(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. 0011 1001 0111 1110 1000 0010 1100 0000 1111 1100 0100 1101 0111 1 0010 0100 =


0011 1001 0111 1110 1000 0010 1100 0000 1111 1100 0100 1101 0111


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 1100


Mantissa (52 bits) =
0011 1001 0111 1110 1000 0010 1100 0000 1111 1100 0100 1101 0111


The base ten decimal number 2 823 704 568 289 406 756 converted and written in 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0011 1100 - 0011 1001 0111 1110 1000 0010 1100 0000 1111 1100 0100 1101 0111

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