204.120 999 999 999 980 919 7 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 204.120 999 999 999 980 919 7(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
204.120 999 999 999 980 919 7(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: 204.
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;
  • 204 ÷ 2 = 102 + 0;
  • 102 ÷ 2 = 51 + 0;
  • 51 ÷ 2 = 25 + 1;
  • 25 ÷ 2 = 12 + 1;
  • 12 ÷ 2 = 6 + 0;
  • 6 ÷ 2 = 3 + 0;
  • 3 ÷ 2 = 1 + 1;
  • 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.

204(10) =


1100 1100(2)


3. Convert to binary (base 2) the fractional part: 0.120 999 999 999 980 919 7.

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) 0.120 999 999 999 980 919 7 × 2 = 0 + 0.241 999 999 999 961 839 4;
  • 2) 0.241 999 999 999 961 839 4 × 2 = 0 + 0.483 999 999 999 923 678 8;
  • 3) 0.483 999 999 999 923 678 8 × 2 = 0 + 0.967 999 999 999 847 357 6;
  • 4) 0.967 999 999 999 847 357 6 × 2 = 1 + 0.935 999 999 999 694 715 2;
  • 5) 0.935 999 999 999 694 715 2 × 2 = 1 + 0.871 999 999 999 389 430 4;
  • 6) 0.871 999 999 999 389 430 4 × 2 = 1 + 0.743 999 999 998 778 860 8;
  • 7) 0.743 999 999 998 778 860 8 × 2 = 1 + 0.487 999 999 997 557 721 6;
  • 8) 0.487 999 999 997 557 721 6 × 2 = 0 + 0.975 999 999 995 115 443 2;
  • 9) 0.975 999 999 995 115 443 2 × 2 = 1 + 0.951 999 999 990 230 886 4;
  • 10) 0.951 999 999 990 230 886 4 × 2 = 1 + 0.903 999 999 980 461 772 8;
  • 11) 0.903 999 999 980 461 772 8 × 2 = 1 + 0.807 999 999 960 923 545 6;
  • 12) 0.807 999 999 960 923 545 6 × 2 = 1 + 0.615 999 999 921 847 091 2;
  • 13) 0.615 999 999 921 847 091 2 × 2 = 1 + 0.231 999 999 843 694 182 4;
  • 14) 0.231 999 999 843 694 182 4 × 2 = 0 + 0.463 999 999 687 388 364 8;
  • 15) 0.463 999 999 687 388 364 8 × 2 = 0 + 0.927 999 999 374 776 729 6;
  • 16) 0.927 999 999 374 776 729 6 × 2 = 1 + 0.855 999 998 749 553 459 2;
  • 17) 0.855 999 998 749 553 459 2 × 2 = 1 + 0.711 999 997 499 106 918 4;
  • 18) 0.711 999 997 499 106 918 4 × 2 = 1 + 0.423 999 994 998 213 836 8;
  • 19) 0.423 999 994 998 213 836 8 × 2 = 0 + 0.847 999 989 996 427 673 6;
  • 20) 0.847 999 989 996 427 673 6 × 2 = 1 + 0.695 999 979 992 855 347 2;
  • 21) 0.695 999 979 992 855 347 2 × 2 = 1 + 0.391 999 959 985 710 694 4;
  • 22) 0.391 999 959 985 710 694 4 × 2 = 0 + 0.783 999 919 971 421 388 8;
  • 23) 0.783 999 919 971 421 388 8 × 2 = 1 + 0.567 999 839 942 842 777 6;
  • 24) 0.567 999 839 942 842 777 6 × 2 = 1 + 0.135 999 679 885 685 555 2;
  • 25) 0.135 999 679 885 685 555 2 × 2 = 0 + 0.271 999 359 771 371 110 4;
  • 26) 0.271 999 359 771 371 110 4 × 2 = 0 + 0.543 998 719 542 742 220 8;
  • 27) 0.543 998 719 542 742 220 8 × 2 = 1 + 0.087 997 439 085 484 441 6;
  • 28) 0.087 997 439 085 484 441 6 × 2 = 0 + 0.175 994 878 170 968 883 2;
  • 29) 0.175 994 878 170 968 883 2 × 2 = 0 + 0.351 989 756 341 937 766 4;
  • 30) 0.351 989 756 341 937 766 4 × 2 = 0 + 0.703 979 512 683 875 532 8;
  • 31) 0.703 979 512 683 875 532 8 × 2 = 1 + 0.407 959 025 367 751 065 6;
  • 32) 0.407 959 025 367 751 065 6 × 2 = 0 + 0.815 918 050 735 502 131 2;
  • 33) 0.815 918 050 735 502 131 2 × 2 = 1 + 0.631 836 101 471 004 262 4;
  • 34) 0.631 836 101 471 004 262 4 × 2 = 1 + 0.263 672 202 942 008 524 8;
  • 35) 0.263 672 202 942 008 524 8 × 2 = 0 + 0.527 344 405 884 017 049 6;
  • 36) 0.527 344 405 884 017 049 6 × 2 = 1 + 0.054 688 811 768 034 099 2;
  • 37) 0.054 688 811 768 034 099 2 × 2 = 0 + 0.109 377 623 536 068 198 4;
  • 38) 0.109 377 623 536 068 198 4 × 2 = 0 + 0.218 755 247 072 136 396 8;
  • 39) 0.218 755 247 072 136 396 8 × 2 = 0 + 0.437 510 494 144 272 793 6;
  • 40) 0.437 510 494 144 272 793 6 × 2 = 0 + 0.875 020 988 288 545 587 2;
  • 41) 0.875 020 988 288 545 587 2 × 2 = 1 + 0.750 041 976 577 091 174 4;
  • 42) 0.750 041 976 577 091 174 4 × 2 = 1 + 0.500 083 953 154 182 348 8;
  • 43) 0.500 083 953 154 182 348 8 × 2 = 1 + 0.000 167 906 308 364 697 6;
  • 44) 0.000 167 906 308 364 697 6 × 2 = 0 + 0.000 335 812 616 729 395 2;
  • 45) 0.000 335 812 616 729 395 2 × 2 = 0 + 0.000 671 625 233 458 790 4;
  • 46) 0.000 671 625 233 458 790 4 × 2 = 0 + 0.001 343 250 466 917 580 8;
  • 47) 0.001 343 250 466 917 580 8 × 2 = 0 + 0.002 686 500 933 835 161 6;
  • 48) 0.002 686 500 933 835 161 6 × 2 = 0 + 0.005 373 001 867 670 323 2;
  • 49) 0.005 373 001 867 670 323 2 × 2 = 0 + 0.010 746 003 735 340 646 4;
  • 50) 0.010 746 003 735 340 646 4 × 2 = 0 + 0.021 492 007 470 681 292 8;
  • 51) 0.021 492 007 470 681 292 8 × 2 = 0 + 0.042 984 014 941 362 585 6;
  • 52) 0.042 984 014 941 362 585 6 × 2 = 0 + 0.085 968 029 882 725 171 2;
  • 53) 0.085 968 029 882 725 171 2 × 2 = 0 + 0.171 936 059 765 450 342 4;

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:


0.120 999 999 999 980 919 7(10) =


0.0001 1110 1111 1001 1101 1011 0010 0010 1101 0000 1110 0000 0000 0(2)

5. Positive number before normalization:

204.120 999 999 999 980 919 7(10) =


1100 1100.0001 1110 1111 1001 1101 1011 0010 0010 1101 0000 1110 0000 0000 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 7 positions to the left, so that only one non zero digit remains to the left of it:


204.120 999 999 999 980 919 7(10) =


1100 1100.0001 1110 1111 1001 1101 1011 0010 0010 1101 0000 1110 0000 0000 0(2) =


1100 1100.0001 1110 1111 1001 1101 1011 0010 0010 1101 0000 1110 0000 0000 0(2) × 20 =


1.1001 1000 0011 1101 1111 0011 1011 0110 0100 0101 1010 0001 1100 0000 0000(2) × 27


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): 7


Mantissa (not normalized):
1.1001 1000 0011 1101 1111 0011 1011 0110 0100 0101 1010 0001 1100 0000 0000


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(11-1) - 1 =


7 + 2(11-1) - 1 =


(7 + 1 023)(10) =


1 030(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;
  • 1 030 ÷ 2 = 515 + 0;
  • 515 ÷ 2 = 257 + 1;
  • 257 ÷ 2 = 128 + 1;
  • 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) =


1030(10) =


100 0000 0110(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. 1001 1000 0011 1101 1111 0011 1011 0110 0100 0101 1010 0001 1100 0000 0000 =


1001 1000 0011 1101 1111 0011 1011 0110 0100 0101 1010 0001 1100


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 0110


Mantissa (52 bits) =
1001 1000 0011 1101 1111 0011 1011 0110 0100 0101 1010 0001 1100


Decimal number 204.120 999 999 999 980 919 7 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0110 - 1001 1000 0011 1101 1111 0011 1011 0110 0100 0101 1010 0001 1100


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