2.236 067 977 499 789 698 81 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.236 067 977 499 789 698 81(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
2.236 067 977 499 789 698 81(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: 0.236 067 977 499 789 698 81.

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) 0.236 067 977 499 789 698 81 × 2 = 0 + 0.472 135 954 999 579 397 62;
  • 2) 0.472 135 954 999 579 397 62 × 2 = 0 + 0.944 271 909 999 158 795 24;
  • 3) 0.944 271 909 999 158 795 24 × 2 = 1 + 0.888 543 819 998 317 590 48;
  • 4) 0.888 543 819 998 317 590 48 × 2 = 1 + 0.777 087 639 996 635 180 96;
  • 5) 0.777 087 639 996 635 180 96 × 2 = 1 + 0.554 175 279 993 270 361 92;
  • 6) 0.554 175 279 993 270 361 92 × 2 = 1 + 0.108 350 559 986 540 723 84;
  • 7) 0.108 350 559 986 540 723 84 × 2 = 0 + 0.216 701 119 973 081 447 68;
  • 8) 0.216 701 119 973 081 447 68 × 2 = 0 + 0.433 402 239 946 162 895 36;
  • 9) 0.433 402 239 946 162 895 36 × 2 = 0 + 0.866 804 479 892 325 790 72;
  • 10) 0.866 804 479 892 325 790 72 × 2 = 1 + 0.733 608 959 784 651 581 44;
  • 11) 0.733 608 959 784 651 581 44 × 2 = 1 + 0.467 217 919 569 303 162 88;
  • 12) 0.467 217 919 569 303 162 88 × 2 = 0 + 0.934 435 839 138 606 325 76;
  • 13) 0.934 435 839 138 606 325 76 × 2 = 1 + 0.868 871 678 277 212 651 52;
  • 14) 0.868 871 678 277 212 651 52 × 2 = 1 + 0.737 743 356 554 425 303 04;
  • 15) 0.737 743 356 554 425 303 04 × 2 = 1 + 0.475 486 713 108 850 606 08;
  • 16) 0.475 486 713 108 850 606 08 × 2 = 0 + 0.950 973 426 217 701 212 16;
  • 17) 0.950 973 426 217 701 212 16 × 2 = 1 + 0.901 946 852 435 402 424 32;
  • 18) 0.901 946 852 435 402 424 32 × 2 = 1 + 0.803 893 704 870 804 848 64;
  • 19) 0.803 893 704 870 804 848 64 × 2 = 1 + 0.607 787 409 741 609 697 28;
  • 20) 0.607 787 409 741 609 697 28 × 2 = 1 + 0.215 574 819 483 219 394 56;
  • 21) 0.215 574 819 483 219 394 56 × 2 = 0 + 0.431 149 638 966 438 789 12;
  • 22) 0.431 149 638 966 438 789 12 × 2 = 0 + 0.862 299 277 932 877 578 24;
  • 23) 0.862 299 277 932 877 578 24 × 2 = 1 + 0.724 598 555 865 755 156 48;
  • 24) 0.724 598 555 865 755 156 48 × 2 = 1 + 0.449 197 111 731 510 312 96;
  • 25) 0.449 197 111 731 510 312 96 × 2 = 0 + 0.898 394 223 463 020 625 92;
  • 26) 0.898 394 223 463 020 625 92 × 2 = 1 + 0.796 788 446 926 041 251 84;
  • 27) 0.796 788 446 926 041 251 84 × 2 = 1 + 0.593 576 893 852 082 503 68;
  • 28) 0.593 576 893 852 082 503 68 × 2 = 1 + 0.187 153 787 704 165 007 36;
  • 29) 0.187 153 787 704 165 007 36 × 2 = 0 + 0.374 307 575 408 330 014 72;
  • 30) 0.374 307 575 408 330 014 72 × 2 = 0 + 0.748 615 150 816 660 029 44;
  • 31) 0.748 615 150 816 660 029 44 × 2 = 1 + 0.497 230 301 633 320 058 88;
  • 32) 0.497 230 301 633 320 058 88 × 2 = 0 + 0.994 460 603 266 640 117 76;
  • 33) 0.994 460 603 266 640 117 76 × 2 = 1 + 0.988 921 206 533 280 235 52;
  • 34) 0.988 921 206 533 280 235 52 × 2 = 1 + 0.977 842 413 066 560 471 04;
  • 35) 0.977 842 413 066 560 471 04 × 2 = 1 + 0.955 684 826 133 120 942 08;
  • 36) 0.955 684 826 133 120 942 08 × 2 = 1 + 0.911 369 652 266 241 884 16;
  • 37) 0.911 369 652 266 241 884 16 × 2 = 1 + 0.822 739 304 532 483 768 32;
  • 38) 0.822 739 304 532 483 768 32 × 2 = 1 + 0.645 478 609 064 967 536 64;
  • 39) 0.645 478 609 064 967 536 64 × 2 = 1 + 0.290 957 218 129 935 073 28;
  • 40) 0.290 957 218 129 935 073 28 × 2 = 0 + 0.581 914 436 259 870 146 56;
  • 41) 0.581 914 436 259 870 146 56 × 2 = 1 + 0.163 828 872 519 740 293 12;
  • 42) 0.163 828 872 519 740 293 12 × 2 = 0 + 0.327 657 745 039 480 586 24;
  • 43) 0.327 657 745 039 480 586 24 × 2 = 0 + 0.655 315 490 078 961 172 48;
  • 44) 0.655 315 490 078 961 172 48 × 2 = 1 + 0.310 630 980 157 922 344 96;
  • 45) 0.310 630 980 157 922 344 96 × 2 = 0 + 0.621 261 960 315 844 689 92;
  • 46) 0.621 261 960 315 844 689 92 × 2 = 1 + 0.242 523 920 631 689 379 84;
  • 47) 0.242 523 920 631 689 379 84 × 2 = 0 + 0.485 047 841 263 378 759 68;
  • 48) 0.485 047 841 263 378 759 68 × 2 = 0 + 0.970 095 682 526 757 519 36;
  • 49) 0.970 095 682 526 757 519 36 × 2 = 1 + 0.940 191 365 053 515 038 72;
  • 50) 0.940 191 365 053 515 038 72 × 2 = 1 + 0.880 382 730 107 030 077 44;
  • 51) 0.880 382 730 107 030 077 44 × 2 = 1 + 0.760 765 460 214 060 154 88;
  • 52) 0.760 765 460 214 060 154 88 × 2 = 1 + 0.521 530 920 428 120 309 76;
  • 53) 0.521 530 920 428 120 309 76 × 2 = 1 + 0.043 061 840 856 240 619 52;

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:


0.236 067 977 499 789 698 81(10) =


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

5. Positive number before normalization:

2.236 067 977 499 789 698 81(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:


2.236 067 977 499 789 698 81(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 2.236 067 977 499 789 698 81 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