2.236 067 977 499 789 699 84 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.236 067 977 499 789 699 84(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
2.236 067 977 499 789 699 84(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: 0.236 067 977 499 789 699 84.

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) 0.236 067 977 499 789 699 84 × 2 = 0 + 0.472 135 954 999 579 399 68;
  • 2) 0.472 135 954 999 579 399 68 × 2 = 0 + 0.944 271 909 999 158 799 36;
  • 3) 0.944 271 909 999 158 799 36 × 2 = 1 + 0.888 543 819 998 317 598 72;
  • 4) 0.888 543 819 998 317 598 72 × 2 = 1 + 0.777 087 639 996 635 197 44;
  • 5) 0.777 087 639 996 635 197 44 × 2 = 1 + 0.554 175 279 993 270 394 88;
  • 6) 0.554 175 279 993 270 394 88 × 2 = 1 + 0.108 350 559 986 540 789 76;
  • 7) 0.108 350 559 986 540 789 76 × 2 = 0 + 0.216 701 119 973 081 579 52;
  • 8) 0.216 701 119 973 081 579 52 × 2 = 0 + 0.433 402 239 946 163 159 04;
  • 9) 0.433 402 239 946 163 159 04 × 2 = 0 + 0.866 804 479 892 326 318 08;
  • 10) 0.866 804 479 892 326 318 08 × 2 = 1 + 0.733 608 959 784 652 636 16;
  • 11) 0.733 608 959 784 652 636 16 × 2 = 1 + 0.467 217 919 569 305 272 32;
  • 12) 0.467 217 919 569 305 272 32 × 2 = 0 + 0.934 435 839 138 610 544 64;
  • 13) 0.934 435 839 138 610 544 64 × 2 = 1 + 0.868 871 678 277 221 089 28;
  • 14) 0.868 871 678 277 221 089 28 × 2 = 1 + 0.737 743 356 554 442 178 56;
  • 15) 0.737 743 356 554 442 178 56 × 2 = 1 + 0.475 486 713 108 884 357 12;
  • 16) 0.475 486 713 108 884 357 12 × 2 = 0 + 0.950 973 426 217 768 714 24;
  • 17) 0.950 973 426 217 768 714 24 × 2 = 1 + 0.901 946 852 435 537 428 48;
  • 18) 0.901 946 852 435 537 428 48 × 2 = 1 + 0.803 893 704 871 074 856 96;
  • 19) 0.803 893 704 871 074 856 96 × 2 = 1 + 0.607 787 409 742 149 713 92;
  • 20) 0.607 787 409 742 149 713 92 × 2 = 1 + 0.215 574 819 484 299 427 84;
  • 21) 0.215 574 819 484 299 427 84 × 2 = 0 + 0.431 149 638 968 598 855 68;
  • 22) 0.431 149 638 968 598 855 68 × 2 = 0 + 0.862 299 277 937 197 711 36;
  • 23) 0.862 299 277 937 197 711 36 × 2 = 1 + 0.724 598 555 874 395 422 72;
  • 24) 0.724 598 555 874 395 422 72 × 2 = 1 + 0.449 197 111 748 790 845 44;
  • 25) 0.449 197 111 748 790 845 44 × 2 = 0 + 0.898 394 223 497 581 690 88;
  • 26) 0.898 394 223 497 581 690 88 × 2 = 1 + 0.796 788 446 995 163 381 76;
  • 27) 0.796 788 446 995 163 381 76 × 2 = 1 + 0.593 576 893 990 326 763 52;
  • 28) 0.593 576 893 990 326 763 52 × 2 = 1 + 0.187 153 787 980 653 527 04;
  • 29) 0.187 153 787 980 653 527 04 × 2 = 0 + 0.374 307 575 961 307 054 08;
  • 30) 0.374 307 575 961 307 054 08 × 2 = 0 + 0.748 615 151 922 614 108 16;
  • 31) 0.748 615 151 922 614 108 16 × 2 = 1 + 0.497 230 303 845 228 216 32;
  • 32) 0.497 230 303 845 228 216 32 × 2 = 0 + 0.994 460 607 690 456 432 64;
  • 33) 0.994 460 607 690 456 432 64 × 2 = 1 + 0.988 921 215 380 912 865 28;
  • 34) 0.988 921 215 380 912 865 28 × 2 = 1 + 0.977 842 430 761 825 730 56;
  • 35) 0.977 842 430 761 825 730 56 × 2 = 1 + 0.955 684 861 523 651 461 12;
  • 36) 0.955 684 861 523 651 461 12 × 2 = 1 + 0.911 369 723 047 302 922 24;
  • 37) 0.911 369 723 047 302 922 24 × 2 = 1 + 0.822 739 446 094 605 844 48;
  • 38) 0.822 739 446 094 605 844 48 × 2 = 1 + 0.645 478 892 189 211 688 96;
  • 39) 0.645 478 892 189 211 688 96 × 2 = 1 + 0.290 957 784 378 423 377 92;
  • 40) 0.290 957 784 378 423 377 92 × 2 = 0 + 0.581 915 568 756 846 755 84;
  • 41) 0.581 915 568 756 846 755 84 × 2 = 1 + 0.163 831 137 513 693 511 68;
  • 42) 0.163 831 137 513 693 511 68 × 2 = 0 + 0.327 662 275 027 387 023 36;
  • 43) 0.327 662 275 027 387 023 36 × 2 = 0 + 0.655 324 550 054 774 046 72;
  • 44) 0.655 324 550 054 774 046 72 × 2 = 1 + 0.310 649 100 109 548 093 44;
  • 45) 0.310 649 100 109 548 093 44 × 2 = 0 + 0.621 298 200 219 096 186 88;
  • 46) 0.621 298 200 219 096 186 88 × 2 = 1 + 0.242 596 400 438 192 373 76;
  • 47) 0.242 596 400 438 192 373 76 × 2 = 0 + 0.485 192 800 876 384 747 52;
  • 48) 0.485 192 800 876 384 747 52 × 2 = 0 + 0.970 385 601 752 769 495 04;
  • 49) 0.970 385 601 752 769 495 04 × 2 = 1 + 0.940 771 203 505 538 990 08;
  • 50) 0.940 771 203 505 538 990 08 × 2 = 1 + 0.881 542 407 011 077 980 16;
  • 51) 0.881 542 407 011 077 980 16 × 2 = 1 + 0.763 084 814 022 155 960 32;
  • 52) 0.763 084 814 022 155 960 32 × 2 = 1 + 0.526 169 628 044 311 920 64;
  • 53) 0.526 169 628 044 311 920 64 × 2 = 1 + 0.052 339 256 088 623 841 28;

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:


0.236 067 977 499 789 699 84(10) =


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

5. Positive number before normalization:

2.236 067 977 499 789 699 84(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:


2.236 067 977 499 789 699 84(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 2.236 067 977 499 789 699 84 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