2.236 067 977 499 789 698 16 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.236 067 977 499 789 698 16(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 16(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 16.

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 16 × 2 = 0 + 0.472 135 954 999 579 396 32;
  • 2) 0.472 135 954 999 579 396 32 × 2 = 0 + 0.944 271 909 999 158 792 64;
  • 3) 0.944 271 909 999 158 792 64 × 2 = 1 + 0.888 543 819 998 317 585 28;
  • 4) 0.888 543 819 998 317 585 28 × 2 = 1 + 0.777 087 639 996 635 170 56;
  • 5) 0.777 087 639 996 635 170 56 × 2 = 1 + 0.554 175 279 993 270 341 12;
  • 6) 0.554 175 279 993 270 341 12 × 2 = 1 + 0.108 350 559 986 540 682 24;
  • 7) 0.108 350 559 986 540 682 24 × 2 = 0 + 0.216 701 119 973 081 364 48;
  • 8) 0.216 701 119 973 081 364 48 × 2 = 0 + 0.433 402 239 946 162 728 96;
  • 9) 0.433 402 239 946 162 728 96 × 2 = 0 + 0.866 804 479 892 325 457 92;
  • 10) 0.866 804 479 892 325 457 92 × 2 = 1 + 0.733 608 959 784 650 915 84;
  • 11) 0.733 608 959 784 650 915 84 × 2 = 1 + 0.467 217 919 569 301 831 68;
  • 12) 0.467 217 919 569 301 831 68 × 2 = 0 + 0.934 435 839 138 603 663 36;
  • 13) 0.934 435 839 138 603 663 36 × 2 = 1 + 0.868 871 678 277 207 326 72;
  • 14) 0.868 871 678 277 207 326 72 × 2 = 1 + 0.737 743 356 554 414 653 44;
  • 15) 0.737 743 356 554 414 653 44 × 2 = 1 + 0.475 486 713 108 829 306 88;
  • 16) 0.475 486 713 108 829 306 88 × 2 = 0 + 0.950 973 426 217 658 613 76;
  • 17) 0.950 973 426 217 658 613 76 × 2 = 1 + 0.901 946 852 435 317 227 52;
  • 18) 0.901 946 852 435 317 227 52 × 2 = 1 + 0.803 893 704 870 634 455 04;
  • 19) 0.803 893 704 870 634 455 04 × 2 = 1 + 0.607 787 409 741 268 910 08;
  • 20) 0.607 787 409 741 268 910 08 × 2 = 1 + 0.215 574 819 482 537 820 16;
  • 21) 0.215 574 819 482 537 820 16 × 2 = 0 + 0.431 149 638 965 075 640 32;
  • 22) 0.431 149 638 965 075 640 32 × 2 = 0 + 0.862 299 277 930 151 280 64;
  • 23) 0.862 299 277 930 151 280 64 × 2 = 1 + 0.724 598 555 860 302 561 28;
  • 24) 0.724 598 555 860 302 561 28 × 2 = 1 + 0.449 197 111 720 605 122 56;
  • 25) 0.449 197 111 720 605 122 56 × 2 = 0 + 0.898 394 223 441 210 245 12;
  • 26) 0.898 394 223 441 210 245 12 × 2 = 1 + 0.796 788 446 882 420 490 24;
  • 27) 0.796 788 446 882 420 490 24 × 2 = 1 + 0.593 576 893 764 840 980 48;
  • 28) 0.593 576 893 764 840 980 48 × 2 = 1 + 0.187 153 787 529 681 960 96;
  • 29) 0.187 153 787 529 681 960 96 × 2 = 0 + 0.374 307 575 059 363 921 92;
  • 30) 0.374 307 575 059 363 921 92 × 2 = 0 + 0.748 615 150 118 727 843 84;
  • 31) 0.748 615 150 118 727 843 84 × 2 = 1 + 0.497 230 300 237 455 687 68;
  • 32) 0.497 230 300 237 455 687 68 × 2 = 0 + 0.994 460 600 474 911 375 36;
  • 33) 0.994 460 600 474 911 375 36 × 2 = 1 + 0.988 921 200 949 822 750 72;
  • 34) 0.988 921 200 949 822 750 72 × 2 = 1 + 0.977 842 401 899 645 501 44;
  • 35) 0.977 842 401 899 645 501 44 × 2 = 1 + 0.955 684 803 799 291 002 88;
  • 36) 0.955 684 803 799 291 002 88 × 2 = 1 + 0.911 369 607 598 582 005 76;
  • 37) 0.911 369 607 598 582 005 76 × 2 = 1 + 0.822 739 215 197 164 011 52;
  • 38) 0.822 739 215 197 164 011 52 × 2 = 1 + 0.645 478 430 394 328 023 04;
  • 39) 0.645 478 430 394 328 023 04 × 2 = 1 + 0.290 956 860 788 656 046 08;
  • 40) 0.290 956 860 788 656 046 08 × 2 = 0 + 0.581 913 721 577 312 092 16;
  • 41) 0.581 913 721 577 312 092 16 × 2 = 1 + 0.163 827 443 154 624 184 32;
  • 42) 0.163 827 443 154 624 184 32 × 2 = 0 + 0.327 654 886 309 248 368 64;
  • 43) 0.327 654 886 309 248 368 64 × 2 = 0 + 0.655 309 772 618 496 737 28;
  • 44) 0.655 309 772 618 496 737 28 × 2 = 1 + 0.310 619 545 236 993 474 56;
  • 45) 0.310 619 545 236 993 474 56 × 2 = 0 + 0.621 239 090 473 986 949 12;
  • 46) 0.621 239 090 473 986 949 12 × 2 = 1 + 0.242 478 180 947 973 898 24;
  • 47) 0.242 478 180 947 973 898 24 × 2 = 0 + 0.484 956 361 895 947 796 48;
  • 48) 0.484 956 361 895 947 796 48 × 2 = 0 + 0.969 912 723 791 895 592 96;
  • 49) 0.969 912 723 791 895 592 96 × 2 = 1 + 0.939 825 447 583 791 185 92;
  • 50) 0.939 825 447 583 791 185 92 × 2 = 1 + 0.879 650 895 167 582 371 84;
  • 51) 0.879 650 895 167 582 371 84 × 2 = 1 + 0.759 301 790 335 164 743 68;
  • 52) 0.759 301 790 335 164 743 68 × 2 = 1 + 0.518 603 580 670 329 487 36;
  • 53) 0.518 603 580 670 329 487 36 × 2 = 1 + 0.037 207 161 340 658 974 72;

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 16(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 16(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 16(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 16 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