2.236 067 977 499 789 696 68 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.236 067 977 499 789 696 68(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 68(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 68.

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 68 × 2 = 0 + 0.472 135 954 999 579 393 36;
  • 2) 0.472 135 954 999 579 393 36 × 2 = 0 + 0.944 271 909 999 158 786 72;
  • 3) 0.944 271 909 999 158 786 72 × 2 = 1 + 0.888 543 819 998 317 573 44;
  • 4) 0.888 543 819 998 317 573 44 × 2 = 1 + 0.777 087 639 996 635 146 88;
  • 5) 0.777 087 639 996 635 146 88 × 2 = 1 + 0.554 175 279 993 270 293 76;
  • 6) 0.554 175 279 993 270 293 76 × 2 = 1 + 0.108 350 559 986 540 587 52;
  • 7) 0.108 350 559 986 540 587 52 × 2 = 0 + 0.216 701 119 973 081 175 04;
  • 8) 0.216 701 119 973 081 175 04 × 2 = 0 + 0.433 402 239 946 162 350 08;
  • 9) 0.433 402 239 946 162 350 08 × 2 = 0 + 0.866 804 479 892 324 700 16;
  • 10) 0.866 804 479 892 324 700 16 × 2 = 1 + 0.733 608 959 784 649 400 32;
  • 11) 0.733 608 959 784 649 400 32 × 2 = 1 + 0.467 217 919 569 298 800 64;
  • 12) 0.467 217 919 569 298 800 64 × 2 = 0 + 0.934 435 839 138 597 601 28;
  • 13) 0.934 435 839 138 597 601 28 × 2 = 1 + 0.868 871 678 277 195 202 56;
  • 14) 0.868 871 678 277 195 202 56 × 2 = 1 + 0.737 743 356 554 390 405 12;
  • 15) 0.737 743 356 554 390 405 12 × 2 = 1 + 0.475 486 713 108 780 810 24;
  • 16) 0.475 486 713 108 780 810 24 × 2 = 0 + 0.950 973 426 217 561 620 48;
  • 17) 0.950 973 426 217 561 620 48 × 2 = 1 + 0.901 946 852 435 123 240 96;
  • 18) 0.901 946 852 435 123 240 96 × 2 = 1 + 0.803 893 704 870 246 481 92;
  • 19) 0.803 893 704 870 246 481 92 × 2 = 1 + 0.607 787 409 740 492 963 84;
  • 20) 0.607 787 409 740 492 963 84 × 2 = 1 + 0.215 574 819 480 985 927 68;
  • 21) 0.215 574 819 480 985 927 68 × 2 = 0 + 0.431 149 638 961 971 855 36;
  • 22) 0.431 149 638 961 971 855 36 × 2 = 0 + 0.862 299 277 923 943 710 72;
  • 23) 0.862 299 277 923 943 710 72 × 2 = 1 + 0.724 598 555 847 887 421 44;
  • 24) 0.724 598 555 847 887 421 44 × 2 = 1 + 0.449 197 111 695 774 842 88;
  • 25) 0.449 197 111 695 774 842 88 × 2 = 0 + 0.898 394 223 391 549 685 76;
  • 26) 0.898 394 223 391 549 685 76 × 2 = 1 + 0.796 788 446 783 099 371 52;
  • 27) 0.796 788 446 783 099 371 52 × 2 = 1 + 0.593 576 893 566 198 743 04;
  • 28) 0.593 576 893 566 198 743 04 × 2 = 1 + 0.187 153 787 132 397 486 08;
  • 29) 0.187 153 787 132 397 486 08 × 2 = 0 + 0.374 307 574 264 794 972 16;
  • 30) 0.374 307 574 264 794 972 16 × 2 = 0 + 0.748 615 148 529 589 944 32;
  • 31) 0.748 615 148 529 589 944 32 × 2 = 1 + 0.497 230 297 059 179 888 64;
  • 32) 0.497 230 297 059 179 888 64 × 2 = 0 + 0.994 460 594 118 359 777 28;
  • 33) 0.994 460 594 118 359 777 28 × 2 = 1 + 0.988 921 188 236 719 554 56;
  • 34) 0.988 921 188 236 719 554 56 × 2 = 1 + 0.977 842 376 473 439 109 12;
  • 35) 0.977 842 376 473 439 109 12 × 2 = 1 + 0.955 684 752 946 878 218 24;
  • 36) 0.955 684 752 946 878 218 24 × 2 = 1 + 0.911 369 505 893 756 436 48;
  • 37) 0.911 369 505 893 756 436 48 × 2 = 1 + 0.822 739 011 787 512 872 96;
  • 38) 0.822 739 011 787 512 872 96 × 2 = 1 + 0.645 478 023 575 025 745 92;
  • 39) 0.645 478 023 575 025 745 92 × 2 = 1 + 0.290 956 047 150 051 491 84;
  • 40) 0.290 956 047 150 051 491 84 × 2 = 0 + 0.581 912 094 300 102 983 68;
  • 41) 0.581 912 094 300 102 983 68 × 2 = 1 + 0.163 824 188 600 205 967 36;
  • 42) 0.163 824 188 600 205 967 36 × 2 = 0 + 0.327 648 377 200 411 934 72;
  • 43) 0.327 648 377 200 411 934 72 × 2 = 0 + 0.655 296 754 400 823 869 44;
  • 44) 0.655 296 754 400 823 869 44 × 2 = 1 + 0.310 593 508 801 647 738 88;
  • 45) 0.310 593 508 801 647 738 88 × 2 = 0 + 0.621 187 017 603 295 477 76;
  • 46) 0.621 187 017 603 295 477 76 × 2 = 1 + 0.242 374 035 206 590 955 52;
  • 47) 0.242 374 035 206 590 955 52 × 2 = 0 + 0.484 748 070 413 181 911 04;
  • 48) 0.484 748 070 413 181 911 04 × 2 = 0 + 0.969 496 140 826 363 822 08;
  • 49) 0.969 496 140 826 363 822 08 × 2 = 1 + 0.938 992 281 652 727 644 16;
  • 50) 0.938 992 281 652 727 644 16 × 2 = 1 + 0.877 984 563 305 455 288 32;
  • 51) 0.877 984 563 305 455 288 32 × 2 = 1 + 0.755 969 126 610 910 576 64;
  • 52) 0.755 969 126 610 910 576 64 × 2 = 1 + 0.511 938 253 221 821 153 28;
  • 53) 0.511 938 253 221 821 153 28 × 2 = 1 + 0.023 876 506 443 642 306 56;

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 68(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 68(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 68(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 68 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