1.876 544 564 654 664 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 1.876 544 564 654 664(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
1.876 544 564 654 664(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: 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;
  • 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.

1(10) =


1(2)


3. Convert to binary (base 2) the fractional part: 0.876 544 564 654 664.

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) 0.876 544 564 654 664 × 2 = 1 + 0.753 089 129 309 328;
  • 2) 0.753 089 129 309 328 × 2 = 1 + 0.506 178 258 618 656;
  • 3) 0.506 178 258 618 656 × 2 = 1 + 0.012 356 517 237 312;
  • 4) 0.012 356 517 237 312 × 2 = 0 + 0.024 713 034 474 624;
  • 5) 0.024 713 034 474 624 × 2 = 0 + 0.049 426 068 949 248;
  • 6) 0.049 426 068 949 248 × 2 = 0 + 0.098 852 137 898 496;
  • 7) 0.098 852 137 898 496 × 2 = 0 + 0.197 704 275 796 992;
  • 8) 0.197 704 275 796 992 × 2 = 0 + 0.395 408 551 593 984;
  • 9) 0.395 408 551 593 984 × 2 = 0 + 0.790 817 103 187 968;
  • 10) 0.790 817 103 187 968 × 2 = 1 + 0.581 634 206 375 936;
  • 11) 0.581 634 206 375 936 × 2 = 1 + 0.163 268 412 751 872;
  • 12) 0.163 268 412 751 872 × 2 = 0 + 0.326 536 825 503 744;
  • 13) 0.326 536 825 503 744 × 2 = 0 + 0.653 073 651 007 488;
  • 14) 0.653 073 651 007 488 × 2 = 1 + 0.306 147 302 014 976;
  • 15) 0.306 147 302 014 976 × 2 = 0 + 0.612 294 604 029 952;
  • 16) 0.612 294 604 029 952 × 2 = 1 + 0.224 589 208 059 904;
  • 17) 0.224 589 208 059 904 × 2 = 0 + 0.449 178 416 119 808;
  • 18) 0.449 178 416 119 808 × 2 = 0 + 0.898 356 832 239 616;
  • 19) 0.898 356 832 239 616 × 2 = 1 + 0.796 713 664 479 232;
  • 20) 0.796 713 664 479 232 × 2 = 1 + 0.593 427 328 958 464;
  • 21) 0.593 427 328 958 464 × 2 = 1 + 0.186 854 657 916 928;
  • 22) 0.186 854 657 916 928 × 2 = 0 + 0.373 709 315 833 856;
  • 23) 0.373 709 315 833 856 × 2 = 0 + 0.747 418 631 667 712;
  • 24) 0.747 418 631 667 712 × 2 = 1 + 0.494 837 263 335 424;
  • 25) 0.494 837 263 335 424 × 2 = 0 + 0.989 674 526 670 848;
  • 26) 0.989 674 526 670 848 × 2 = 1 + 0.979 349 053 341 696;
  • 27) 0.979 349 053 341 696 × 2 = 1 + 0.958 698 106 683 392;
  • 28) 0.958 698 106 683 392 × 2 = 1 + 0.917 396 213 366 784;
  • 29) 0.917 396 213 366 784 × 2 = 1 + 0.834 792 426 733 568;
  • 30) 0.834 792 426 733 568 × 2 = 1 + 0.669 584 853 467 136;
  • 31) 0.669 584 853 467 136 × 2 = 1 + 0.339 169 706 934 272;
  • 32) 0.339 169 706 934 272 × 2 = 0 + 0.678 339 413 868 544;
  • 33) 0.678 339 413 868 544 × 2 = 1 + 0.356 678 827 737 088;
  • 34) 0.356 678 827 737 088 × 2 = 0 + 0.713 357 655 474 176;
  • 35) 0.713 357 655 474 176 × 2 = 1 + 0.426 715 310 948 352;
  • 36) 0.426 715 310 948 352 × 2 = 0 + 0.853 430 621 896 704;
  • 37) 0.853 430 621 896 704 × 2 = 1 + 0.706 861 243 793 408;
  • 38) 0.706 861 243 793 408 × 2 = 1 + 0.413 722 487 586 816;
  • 39) 0.413 722 487 586 816 × 2 = 0 + 0.827 444 975 173 632;
  • 40) 0.827 444 975 173 632 × 2 = 1 + 0.654 889 950 347 264;
  • 41) 0.654 889 950 347 264 × 2 = 1 + 0.309 779 900 694 528;
  • 42) 0.309 779 900 694 528 × 2 = 0 + 0.619 559 801 389 056;
  • 43) 0.619 559 801 389 056 × 2 = 1 + 0.239 119 602 778 112;
  • 44) 0.239 119 602 778 112 × 2 = 0 + 0.478 239 205 556 224;
  • 45) 0.478 239 205 556 224 × 2 = 0 + 0.956 478 411 112 448;
  • 46) 0.956 478 411 112 448 × 2 = 1 + 0.912 956 822 224 896;
  • 47) 0.912 956 822 224 896 × 2 = 1 + 0.825 913 644 449 792;
  • 48) 0.825 913 644 449 792 × 2 = 1 + 0.651 827 288 899 584;
  • 49) 0.651 827 288 899 584 × 2 = 1 + 0.303 654 577 799 168;
  • 50) 0.303 654 577 799 168 × 2 = 0 + 0.607 309 155 598 336;
  • 51) 0.607 309 155 598 336 × 2 = 1 + 0.214 618 311 196 672;
  • 52) 0.214 618 311 196 672 × 2 = 0 + 0.429 236 622 393 344;
  • 53) 0.429 236 622 393 344 × 2 = 0 + 0.858 473 244 786 688;

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:


0.876 544 564 654 664(10) =


0.1110 0000 0110 0101 0011 1001 0111 1110 1010 1101 1010 0111 1010 0(2)

5. Positive number before normalization:

1.876 544 564 654 664(10) =


1.1110 0000 0110 0101 0011 1001 0111 1110 1010 1101 1010 0111 1010 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 0 positions to the left, so that only one non zero digit remains to the left of it:


1.876 544 564 654 664(10) =


1.1110 0000 0110 0101 0011 1001 0111 1110 1010 1101 1010 0111 1010 0(2) =


1.1110 0000 0110 0101 0011 1001 0111 1110 1010 1101 1010 0111 1010 0(2) × 20


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): 0


Mantissa (not normalized):
1.1110 0000 0110 0101 0011 1001 0111 1110 1010 1101 1010 0111 1010 0


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


0 + 2(11-1) - 1 =


(0 + 1 023)(10) =


1 023(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;
  • 1 023 ÷ 2 = 511 + 1;
  • 511 ÷ 2 = 255 + 1;
  • 255 ÷ 2 = 127 + 1;
  • 127 ÷ 2 = 63 + 1;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 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) =


1023(10) =


011 1111 1111(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. 1110 0000 0110 0101 0011 1001 0111 1110 1010 1101 1010 0111 1010 0 =


1110 0000 0110 0101 0011 1001 0111 1110 1010 1101 1010 0111 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) =
011 1111 1111


Mantissa (52 bits) =
1110 0000 0110 0101 0011 1001 0111 1110 1010 1101 1010 0111 1010


Decimal number 1.876 544 564 654 664 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 011 1111 1111 - 1110 0000 0110 0101 0011 1001 0111 1110 1010 1101 1010 0111 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