2.236 067 977 499 789 696 46 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.236 067 977 499 789 696 46(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
2.236 067 977 499 789 696 46(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: 2.
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 ÷ 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.

2(10) =


10(2)


3. Convert to binary (base 2) the fractional part: 0.236 067 977 499 789 696 46.

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) 0.236 067 977 499 789 696 46 × 2 = 0 + 0.472 135 954 999 579 392 92;
  • 2) 0.472 135 954 999 579 392 92 × 2 = 0 + 0.944 271 909 999 158 785 84;
  • 3) 0.944 271 909 999 158 785 84 × 2 = 1 + 0.888 543 819 998 317 571 68;
  • 4) 0.888 543 819 998 317 571 68 × 2 = 1 + 0.777 087 639 996 635 143 36;
  • 5) 0.777 087 639 996 635 143 36 × 2 = 1 + 0.554 175 279 993 270 286 72;
  • 6) 0.554 175 279 993 270 286 72 × 2 = 1 + 0.108 350 559 986 540 573 44;
  • 7) 0.108 350 559 986 540 573 44 × 2 = 0 + 0.216 701 119 973 081 146 88;
  • 8) 0.216 701 119 973 081 146 88 × 2 = 0 + 0.433 402 239 946 162 293 76;
  • 9) 0.433 402 239 946 162 293 76 × 2 = 0 + 0.866 804 479 892 324 587 52;
  • 10) 0.866 804 479 892 324 587 52 × 2 = 1 + 0.733 608 959 784 649 175 04;
  • 11) 0.733 608 959 784 649 175 04 × 2 = 1 + 0.467 217 919 569 298 350 08;
  • 12) 0.467 217 919 569 298 350 08 × 2 = 0 + 0.934 435 839 138 596 700 16;
  • 13) 0.934 435 839 138 596 700 16 × 2 = 1 + 0.868 871 678 277 193 400 32;
  • 14) 0.868 871 678 277 193 400 32 × 2 = 1 + 0.737 743 356 554 386 800 64;
  • 15) 0.737 743 356 554 386 800 64 × 2 = 1 + 0.475 486 713 108 773 601 28;
  • 16) 0.475 486 713 108 773 601 28 × 2 = 0 + 0.950 973 426 217 547 202 56;
  • 17) 0.950 973 426 217 547 202 56 × 2 = 1 + 0.901 946 852 435 094 405 12;
  • 18) 0.901 946 852 435 094 405 12 × 2 = 1 + 0.803 893 704 870 188 810 24;
  • 19) 0.803 893 704 870 188 810 24 × 2 = 1 + 0.607 787 409 740 377 620 48;
  • 20) 0.607 787 409 740 377 620 48 × 2 = 1 + 0.215 574 819 480 755 240 96;
  • 21) 0.215 574 819 480 755 240 96 × 2 = 0 + 0.431 149 638 961 510 481 92;
  • 22) 0.431 149 638 961 510 481 92 × 2 = 0 + 0.862 299 277 923 020 963 84;
  • 23) 0.862 299 277 923 020 963 84 × 2 = 1 + 0.724 598 555 846 041 927 68;
  • 24) 0.724 598 555 846 041 927 68 × 2 = 1 + 0.449 197 111 692 083 855 36;
  • 25) 0.449 197 111 692 083 855 36 × 2 = 0 + 0.898 394 223 384 167 710 72;
  • 26) 0.898 394 223 384 167 710 72 × 2 = 1 + 0.796 788 446 768 335 421 44;
  • 27) 0.796 788 446 768 335 421 44 × 2 = 1 + 0.593 576 893 536 670 842 88;
  • 28) 0.593 576 893 536 670 842 88 × 2 = 1 + 0.187 153 787 073 341 685 76;
  • 29) 0.187 153 787 073 341 685 76 × 2 = 0 + 0.374 307 574 146 683 371 52;
  • 30) 0.374 307 574 146 683 371 52 × 2 = 0 + 0.748 615 148 293 366 743 04;
  • 31) 0.748 615 148 293 366 743 04 × 2 = 1 + 0.497 230 296 586 733 486 08;
  • 32) 0.497 230 296 586 733 486 08 × 2 = 0 + 0.994 460 593 173 466 972 16;
  • 33) 0.994 460 593 173 466 972 16 × 2 = 1 + 0.988 921 186 346 933 944 32;
  • 34) 0.988 921 186 346 933 944 32 × 2 = 1 + 0.977 842 372 693 867 888 64;
  • 35) 0.977 842 372 693 867 888 64 × 2 = 1 + 0.955 684 745 387 735 777 28;
  • 36) 0.955 684 745 387 735 777 28 × 2 = 1 + 0.911 369 490 775 471 554 56;
  • 37) 0.911 369 490 775 471 554 56 × 2 = 1 + 0.822 738 981 550 943 109 12;
  • 38) 0.822 738 981 550 943 109 12 × 2 = 1 + 0.645 477 963 101 886 218 24;
  • 39) 0.645 477 963 101 886 218 24 × 2 = 1 + 0.290 955 926 203 772 436 48;
  • 40) 0.290 955 926 203 772 436 48 × 2 = 0 + 0.581 911 852 407 544 872 96;
  • 41) 0.581 911 852 407 544 872 96 × 2 = 1 + 0.163 823 704 815 089 745 92;
  • 42) 0.163 823 704 815 089 745 92 × 2 = 0 + 0.327 647 409 630 179 491 84;
  • 43) 0.327 647 409 630 179 491 84 × 2 = 0 + 0.655 294 819 260 358 983 68;
  • 44) 0.655 294 819 260 358 983 68 × 2 = 1 + 0.310 589 638 520 717 967 36;
  • 45) 0.310 589 638 520 717 967 36 × 2 = 0 + 0.621 179 277 041 435 934 72;
  • 46) 0.621 179 277 041 435 934 72 × 2 = 1 + 0.242 358 554 082 871 869 44;
  • 47) 0.242 358 554 082 871 869 44 × 2 = 0 + 0.484 717 108 165 743 738 88;
  • 48) 0.484 717 108 165 743 738 88 × 2 = 0 + 0.969 434 216 331 487 477 76;
  • 49) 0.969 434 216 331 487 477 76 × 2 = 1 + 0.938 868 432 662 974 955 52;
  • 50) 0.938 868 432 662 974 955 52 × 2 = 1 + 0.877 736 865 325 949 911 04;
  • 51) 0.877 736 865 325 949 911 04 × 2 = 1 + 0.755 473 730 651 899 822 08;
  • 52) 0.755 473 730 651 899 822 08 × 2 = 1 + 0.510 947 461 303 799 644 16;
  • 53) 0.510 947 461 303 799 644 16 × 2 = 1 + 0.021 894 922 607 599 288 32;

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:


0.236 067 977 499 789 696 46(10) =


0.0011 1100 0110 1110 1111 0011 0111 0010 1111 1110 1001 0100 1111 1(2)

5. Positive number before normalization:

2.236 067 977 499 789 696 46(10) =


10.0011 1100 0110 1110 1111 0011 0111 0010 1111 1110 1001 0100 1111 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 1 positions to the left, so that only one non zero digit remains to the left of it:


2.236 067 977 499 789 696 46(10) =


10.0011 1100 0110 1110 1111 0011 0111 0010 1111 1110 1001 0100 1111 1(2) =


10.0011 1100 0110 1110 1111 0011 0111 0010 1111 1110 1001 0100 1111 1(2) × 20 =


1.0001 1110 0011 0111 0111 1001 1011 1001 0111 1111 0100 1010 0111 11(2) × 21


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): 1


Mantissa (not normalized):
1.0001 1110 0011 0111 0111 1001 1011 1001 0111 1111 0100 1010 0111 11


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


1 + 2(11-1) - 1 =


(1 + 1 023)(10) =


1 024(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;
  • 1 024 ÷ 2 = 512 + 0;
  • 512 ÷ 2 = 256 + 0;
  • 256 ÷ 2 = 128 + 0;
  • 128 ÷ 2 = 64 + 0;
  • 64 ÷ 2 = 32 + 0;
  • 32 ÷ 2 = 16 + 0;
  • 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) =


1024(10) =


100 0000 0000(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 1110 0011 0111 0111 1001 1011 1001 0111 1111 0100 1010 0111 11 =


0001 1110 0011 0111 0111 1001 1011 1001 0111 1111 0100 1010 0111


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 0000 0000


Mantissa (52 bits) =
0001 1110 0011 0111 0111 1001 1011 1001 0111 1111 0100 1010 0111


Decimal number 2.236 067 977 499 789 696 46 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0000 - 0001 1110 0011 0111 0111 1001 1011 1001 0111 1111 0100 1010 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