2.236 067 977 499 789 697 57 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.236 067 977 499 789 697 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
2.236 067 977 499 789 697 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: 0.236 067 977 499 789 697 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) 0.236 067 977 499 789 697 57 × 2 = 0 + 0.472 135 954 999 579 395 14;
  • 2) 0.472 135 954 999 579 395 14 × 2 = 0 + 0.944 271 909 999 158 790 28;
  • 3) 0.944 271 909 999 158 790 28 × 2 = 1 + 0.888 543 819 998 317 580 56;
  • 4) 0.888 543 819 998 317 580 56 × 2 = 1 + 0.777 087 639 996 635 161 12;
  • 5) 0.777 087 639 996 635 161 12 × 2 = 1 + 0.554 175 279 993 270 322 24;
  • 6) 0.554 175 279 993 270 322 24 × 2 = 1 + 0.108 350 559 986 540 644 48;
  • 7) 0.108 350 559 986 540 644 48 × 2 = 0 + 0.216 701 119 973 081 288 96;
  • 8) 0.216 701 119 973 081 288 96 × 2 = 0 + 0.433 402 239 946 162 577 92;
  • 9) 0.433 402 239 946 162 577 92 × 2 = 0 + 0.866 804 479 892 325 155 84;
  • 10) 0.866 804 479 892 325 155 84 × 2 = 1 + 0.733 608 959 784 650 311 68;
  • 11) 0.733 608 959 784 650 311 68 × 2 = 1 + 0.467 217 919 569 300 623 36;
  • 12) 0.467 217 919 569 300 623 36 × 2 = 0 + 0.934 435 839 138 601 246 72;
  • 13) 0.934 435 839 138 601 246 72 × 2 = 1 + 0.868 871 678 277 202 493 44;
  • 14) 0.868 871 678 277 202 493 44 × 2 = 1 + 0.737 743 356 554 404 986 88;
  • 15) 0.737 743 356 554 404 986 88 × 2 = 1 + 0.475 486 713 108 809 973 76;
  • 16) 0.475 486 713 108 809 973 76 × 2 = 0 + 0.950 973 426 217 619 947 52;
  • 17) 0.950 973 426 217 619 947 52 × 2 = 1 + 0.901 946 852 435 239 895 04;
  • 18) 0.901 946 852 435 239 895 04 × 2 = 1 + 0.803 893 704 870 479 790 08;
  • 19) 0.803 893 704 870 479 790 08 × 2 = 1 + 0.607 787 409 740 959 580 16;
  • 20) 0.607 787 409 740 959 580 16 × 2 = 1 + 0.215 574 819 481 919 160 32;
  • 21) 0.215 574 819 481 919 160 32 × 2 = 0 + 0.431 149 638 963 838 320 64;
  • 22) 0.431 149 638 963 838 320 64 × 2 = 0 + 0.862 299 277 927 676 641 28;
  • 23) 0.862 299 277 927 676 641 28 × 2 = 1 + 0.724 598 555 855 353 282 56;
  • 24) 0.724 598 555 855 353 282 56 × 2 = 1 + 0.449 197 111 710 706 565 12;
  • 25) 0.449 197 111 710 706 565 12 × 2 = 0 + 0.898 394 223 421 413 130 24;
  • 26) 0.898 394 223 421 413 130 24 × 2 = 1 + 0.796 788 446 842 826 260 48;
  • 27) 0.796 788 446 842 826 260 48 × 2 = 1 + 0.593 576 893 685 652 520 96;
  • 28) 0.593 576 893 685 652 520 96 × 2 = 1 + 0.187 153 787 371 305 041 92;
  • 29) 0.187 153 787 371 305 041 92 × 2 = 0 + 0.374 307 574 742 610 083 84;
  • 30) 0.374 307 574 742 610 083 84 × 2 = 0 + 0.748 615 149 485 220 167 68;
  • 31) 0.748 615 149 485 220 167 68 × 2 = 1 + 0.497 230 298 970 440 335 36;
  • 32) 0.497 230 298 970 440 335 36 × 2 = 0 + 0.994 460 597 940 880 670 72;
  • 33) 0.994 460 597 940 880 670 72 × 2 = 1 + 0.988 921 195 881 761 341 44;
  • 34) 0.988 921 195 881 761 341 44 × 2 = 1 + 0.977 842 391 763 522 682 88;
  • 35) 0.977 842 391 763 522 682 88 × 2 = 1 + 0.955 684 783 527 045 365 76;
  • 36) 0.955 684 783 527 045 365 76 × 2 = 1 + 0.911 369 567 054 090 731 52;
  • 37) 0.911 369 567 054 090 731 52 × 2 = 1 + 0.822 739 134 108 181 463 04;
  • 38) 0.822 739 134 108 181 463 04 × 2 = 1 + 0.645 478 268 216 362 926 08;
  • 39) 0.645 478 268 216 362 926 08 × 2 = 1 + 0.290 956 536 432 725 852 16;
  • 40) 0.290 956 536 432 725 852 16 × 2 = 0 + 0.581 913 072 865 451 704 32;
  • 41) 0.581 913 072 865 451 704 32 × 2 = 1 + 0.163 826 145 730 903 408 64;
  • 42) 0.163 826 145 730 903 408 64 × 2 = 0 + 0.327 652 291 461 806 817 28;
  • 43) 0.327 652 291 461 806 817 28 × 2 = 0 + 0.655 304 582 923 613 634 56;
  • 44) 0.655 304 582 923 613 634 56 × 2 = 1 + 0.310 609 165 847 227 269 12;
  • 45) 0.310 609 165 847 227 269 12 × 2 = 0 + 0.621 218 331 694 454 538 24;
  • 46) 0.621 218 331 694 454 538 24 × 2 = 1 + 0.242 436 663 388 909 076 48;
  • 47) 0.242 436 663 388 909 076 48 × 2 = 0 + 0.484 873 326 777 818 152 96;
  • 48) 0.484 873 326 777 818 152 96 × 2 = 0 + 0.969 746 653 555 636 305 92;
  • 49) 0.969 746 653 555 636 305 92 × 2 = 1 + 0.939 493 307 111 272 611 84;
  • 50) 0.939 493 307 111 272 611 84 × 2 = 1 + 0.878 986 614 222 545 223 68;
  • 51) 0.878 986 614 222 545 223 68 × 2 = 1 + 0.757 973 228 445 090 447 36;
  • 52) 0.757 973 228 445 090 447 36 × 2 = 1 + 0.515 946 456 890 180 894 72;
  • 53) 0.515 946 456 890 180 894 72 × 2 = 1 + 0.031 892 913 780 361 789 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:


0.236 067 977 499 789 697 57(10) =


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

5. Positive number before normalization:

2.236 067 977 499 789 697 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:


2.236 067 977 499 789 697 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 2.236 067 977 499 789 697 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