2.236 067 977 499 789 697 14 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.236 067 977 499 789 697 14(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
2.236 067 977 499 789 697 14(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: 0.236 067 977 499 789 697 14.

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) 0.236 067 977 499 789 697 14 × 2 = 0 + 0.472 135 954 999 579 394 28;
  • 2) 0.472 135 954 999 579 394 28 × 2 = 0 + 0.944 271 909 999 158 788 56;
  • 3) 0.944 271 909 999 158 788 56 × 2 = 1 + 0.888 543 819 998 317 577 12;
  • 4) 0.888 543 819 998 317 577 12 × 2 = 1 + 0.777 087 639 996 635 154 24;
  • 5) 0.777 087 639 996 635 154 24 × 2 = 1 + 0.554 175 279 993 270 308 48;
  • 6) 0.554 175 279 993 270 308 48 × 2 = 1 + 0.108 350 559 986 540 616 96;
  • 7) 0.108 350 559 986 540 616 96 × 2 = 0 + 0.216 701 119 973 081 233 92;
  • 8) 0.216 701 119 973 081 233 92 × 2 = 0 + 0.433 402 239 946 162 467 84;
  • 9) 0.433 402 239 946 162 467 84 × 2 = 0 + 0.866 804 479 892 324 935 68;
  • 10) 0.866 804 479 892 324 935 68 × 2 = 1 + 0.733 608 959 784 649 871 36;
  • 11) 0.733 608 959 784 649 871 36 × 2 = 1 + 0.467 217 919 569 299 742 72;
  • 12) 0.467 217 919 569 299 742 72 × 2 = 0 + 0.934 435 839 138 599 485 44;
  • 13) 0.934 435 839 138 599 485 44 × 2 = 1 + 0.868 871 678 277 198 970 88;
  • 14) 0.868 871 678 277 198 970 88 × 2 = 1 + 0.737 743 356 554 397 941 76;
  • 15) 0.737 743 356 554 397 941 76 × 2 = 1 + 0.475 486 713 108 795 883 52;
  • 16) 0.475 486 713 108 795 883 52 × 2 = 0 + 0.950 973 426 217 591 767 04;
  • 17) 0.950 973 426 217 591 767 04 × 2 = 1 + 0.901 946 852 435 183 534 08;
  • 18) 0.901 946 852 435 183 534 08 × 2 = 1 + 0.803 893 704 870 367 068 16;
  • 19) 0.803 893 704 870 367 068 16 × 2 = 1 + 0.607 787 409 740 734 136 32;
  • 20) 0.607 787 409 740 734 136 32 × 2 = 1 + 0.215 574 819 481 468 272 64;
  • 21) 0.215 574 819 481 468 272 64 × 2 = 0 + 0.431 149 638 962 936 545 28;
  • 22) 0.431 149 638 962 936 545 28 × 2 = 0 + 0.862 299 277 925 873 090 56;
  • 23) 0.862 299 277 925 873 090 56 × 2 = 1 + 0.724 598 555 851 746 181 12;
  • 24) 0.724 598 555 851 746 181 12 × 2 = 1 + 0.449 197 111 703 492 362 24;
  • 25) 0.449 197 111 703 492 362 24 × 2 = 0 + 0.898 394 223 406 984 724 48;
  • 26) 0.898 394 223 406 984 724 48 × 2 = 1 + 0.796 788 446 813 969 448 96;
  • 27) 0.796 788 446 813 969 448 96 × 2 = 1 + 0.593 576 893 627 938 897 92;
  • 28) 0.593 576 893 627 938 897 92 × 2 = 1 + 0.187 153 787 255 877 795 84;
  • 29) 0.187 153 787 255 877 795 84 × 2 = 0 + 0.374 307 574 511 755 591 68;
  • 30) 0.374 307 574 511 755 591 68 × 2 = 0 + 0.748 615 149 023 511 183 36;
  • 31) 0.748 615 149 023 511 183 36 × 2 = 1 + 0.497 230 298 047 022 366 72;
  • 32) 0.497 230 298 047 022 366 72 × 2 = 0 + 0.994 460 596 094 044 733 44;
  • 33) 0.994 460 596 094 044 733 44 × 2 = 1 + 0.988 921 192 188 089 466 88;
  • 34) 0.988 921 192 188 089 466 88 × 2 = 1 + 0.977 842 384 376 178 933 76;
  • 35) 0.977 842 384 376 178 933 76 × 2 = 1 + 0.955 684 768 752 357 867 52;
  • 36) 0.955 684 768 752 357 867 52 × 2 = 1 + 0.911 369 537 504 715 735 04;
  • 37) 0.911 369 537 504 715 735 04 × 2 = 1 + 0.822 739 075 009 431 470 08;
  • 38) 0.822 739 075 009 431 470 08 × 2 = 1 + 0.645 478 150 018 862 940 16;
  • 39) 0.645 478 150 018 862 940 16 × 2 = 1 + 0.290 956 300 037 725 880 32;
  • 40) 0.290 956 300 037 725 880 32 × 2 = 0 + 0.581 912 600 075 451 760 64;
  • 41) 0.581 912 600 075 451 760 64 × 2 = 1 + 0.163 825 200 150 903 521 28;
  • 42) 0.163 825 200 150 903 521 28 × 2 = 0 + 0.327 650 400 301 807 042 56;
  • 43) 0.327 650 400 301 807 042 56 × 2 = 0 + 0.655 300 800 603 614 085 12;
  • 44) 0.655 300 800 603 614 085 12 × 2 = 1 + 0.310 601 601 207 228 170 24;
  • 45) 0.310 601 601 207 228 170 24 × 2 = 0 + 0.621 203 202 414 456 340 48;
  • 46) 0.621 203 202 414 456 340 48 × 2 = 1 + 0.242 406 404 828 912 680 96;
  • 47) 0.242 406 404 828 912 680 96 × 2 = 0 + 0.484 812 809 657 825 361 92;
  • 48) 0.484 812 809 657 825 361 92 × 2 = 0 + 0.969 625 619 315 650 723 84;
  • 49) 0.969 625 619 315 650 723 84 × 2 = 1 + 0.939 251 238 631 301 447 68;
  • 50) 0.939 251 238 631 301 447 68 × 2 = 1 + 0.878 502 477 262 602 895 36;
  • 51) 0.878 502 477 262 602 895 36 × 2 = 1 + 0.757 004 954 525 205 790 72;
  • 52) 0.757 004 954 525 205 790 72 × 2 = 1 + 0.514 009 909 050 411 581 44;
  • 53) 0.514 009 909 050 411 581 44 × 2 = 1 + 0.028 019 818 100 823 162 88;

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:


0.236 067 977 499 789 697 14(10) =


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

5. Positive number before normalization:

2.236 067 977 499 789 697 14(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:


2.236 067 977 499 789 697 14(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 2.236 067 977 499 789 697 14 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