2.236 067 977 499 789 698 57 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.236 067 977 499 789 698 57(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 57(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 57.

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 57 × 2 = 0 + 0.472 135 954 999 579 397 14;
  • 2) 0.472 135 954 999 579 397 14 × 2 = 0 + 0.944 271 909 999 158 794 28;
  • 3) 0.944 271 909 999 158 794 28 × 2 = 1 + 0.888 543 819 998 317 588 56;
  • 4) 0.888 543 819 998 317 588 56 × 2 = 1 + 0.777 087 639 996 635 177 12;
  • 5) 0.777 087 639 996 635 177 12 × 2 = 1 + 0.554 175 279 993 270 354 24;
  • 6) 0.554 175 279 993 270 354 24 × 2 = 1 + 0.108 350 559 986 540 708 48;
  • 7) 0.108 350 559 986 540 708 48 × 2 = 0 + 0.216 701 119 973 081 416 96;
  • 8) 0.216 701 119 973 081 416 96 × 2 = 0 + 0.433 402 239 946 162 833 92;
  • 9) 0.433 402 239 946 162 833 92 × 2 = 0 + 0.866 804 479 892 325 667 84;
  • 10) 0.866 804 479 892 325 667 84 × 2 = 1 + 0.733 608 959 784 651 335 68;
  • 11) 0.733 608 959 784 651 335 68 × 2 = 1 + 0.467 217 919 569 302 671 36;
  • 12) 0.467 217 919 569 302 671 36 × 2 = 0 + 0.934 435 839 138 605 342 72;
  • 13) 0.934 435 839 138 605 342 72 × 2 = 1 + 0.868 871 678 277 210 685 44;
  • 14) 0.868 871 678 277 210 685 44 × 2 = 1 + 0.737 743 356 554 421 370 88;
  • 15) 0.737 743 356 554 421 370 88 × 2 = 1 + 0.475 486 713 108 842 741 76;
  • 16) 0.475 486 713 108 842 741 76 × 2 = 0 + 0.950 973 426 217 685 483 52;
  • 17) 0.950 973 426 217 685 483 52 × 2 = 1 + 0.901 946 852 435 370 967 04;
  • 18) 0.901 946 852 435 370 967 04 × 2 = 1 + 0.803 893 704 870 741 934 08;
  • 19) 0.803 893 704 870 741 934 08 × 2 = 1 + 0.607 787 409 741 483 868 16;
  • 20) 0.607 787 409 741 483 868 16 × 2 = 1 + 0.215 574 819 482 967 736 32;
  • 21) 0.215 574 819 482 967 736 32 × 2 = 0 + 0.431 149 638 965 935 472 64;
  • 22) 0.431 149 638 965 935 472 64 × 2 = 0 + 0.862 299 277 931 870 945 28;
  • 23) 0.862 299 277 931 870 945 28 × 2 = 1 + 0.724 598 555 863 741 890 56;
  • 24) 0.724 598 555 863 741 890 56 × 2 = 1 + 0.449 197 111 727 483 781 12;
  • 25) 0.449 197 111 727 483 781 12 × 2 = 0 + 0.898 394 223 454 967 562 24;
  • 26) 0.898 394 223 454 967 562 24 × 2 = 1 + 0.796 788 446 909 935 124 48;
  • 27) 0.796 788 446 909 935 124 48 × 2 = 1 + 0.593 576 893 819 870 248 96;
  • 28) 0.593 576 893 819 870 248 96 × 2 = 1 + 0.187 153 787 639 740 497 92;
  • 29) 0.187 153 787 639 740 497 92 × 2 = 0 + 0.374 307 575 279 480 995 84;
  • 30) 0.374 307 575 279 480 995 84 × 2 = 0 + 0.748 615 150 558 961 991 68;
  • 31) 0.748 615 150 558 961 991 68 × 2 = 1 + 0.497 230 301 117 923 983 36;
  • 32) 0.497 230 301 117 923 983 36 × 2 = 0 + 0.994 460 602 235 847 966 72;
  • 33) 0.994 460 602 235 847 966 72 × 2 = 1 + 0.988 921 204 471 695 933 44;
  • 34) 0.988 921 204 471 695 933 44 × 2 = 1 + 0.977 842 408 943 391 866 88;
  • 35) 0.977 842 408 943 391 866 88 × 2 = 1 + 0.955 684 817 886 783 733 76;
  • 36) 0.955 684 817 886 783 733 76 × 2 = 1 + 0.911 369 635 773 567 467 52;
  • 37) 0.911 369 635 773 567 467 52 × 2 = 1 + 0.822 739 271 547 134 935 04;
  • 38) 0.822 739 271 547 134 935 04 × 2 = 1 + 0.645 478 543 094 269 870 08;
  • 39) 0.645 478 543 094 269 870 08 × 2 = 1 + 0.290 957 086 188 539 740 16;
  • 40) 0.290 957 086 188 539 740 16 × 2 = 0 + 0.581 914 172 377 079 480 32;
  • 41) 0.581 914 172 377 079 480 32 × 2 = 1 + 0.163 828 344 754 158 960 64;
  • 42) 0.163 828 344 754 158 960 64 × 2 = 0 + 0.327 656 689 508 317 921 28;
  • 43) 0.327 656 689 508 317 921 28 × 2 = 0 + 0.655 313 379 016 635 842 56;
  • 44) 0.655 313 379 016 635 842 56 × 2 = 1 + 0.310 626 758 033 271 685 12;
  • 45) 0.310 626 758 033 271 685 12 × 2 = 0 + 0.621 253 516 066 543 370 24;
  • 46) 0.621 253 516 066 543 370 24 × 2 = 1 + 0.242 507 032 133 086 740 48;
  • 47) 0.242 507 032 133 086 740 48 × 2 = 0 + 0.485 014 064 266 173 480 96;
  • 48) 0.485 014 064 266 173 480 96 × 2 = 0 + 0.970 028 128 532 346 961 92;
  • 49) 0.970 028 128 532 346 961 92 × 2 = 1 + 0.940 056 257 064 693 923 84;
  • 50) 0.940 056 257 064 693 923 84 × 2 = 1 + 0.880 112 514 129 387 847 68;
  • 51) 0.880 112 514 129 387 847 68 × 2 = 1 + 0.760 225 028 258 775 695 36;
  • 52) 0.760 225 028 258 775 695 36 × 2 = 1 + 0.520 450 056 517 551 390 72;
  • 53) 0.520 450 056 517 551 390 72 × 2 = 1 + 0.040 900 113 035 102 781 44;

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 57(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 57(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 57(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 57 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