33.780 086 699 999 908 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 33.780 086 699 999 908(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
33.780 086 699 999 908(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: 33.
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;
  • 33 ÷ 2 = 16 + 1;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 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.

33(10) =


10 0001(2)


3. Convert to binary (base 2) the fractional part: 0.780 086 699 999 908.

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) 0.780 086 699 999 908 × 2 = 1 + 0.560 173 399 999 816;
  • 2) 0.560 173 399 999 816 × 2 = 1 + 0.120 346 799 999 632;
  • 3) 0.120 346 799 999 632 × 2 = 0 + 0.240 693 599 999 264;
  • 4) 0.240 693 599 999 264 × 2 = 0 + 0.481 387 199 998 528;
  • 5) 0.481 387 199 998 528 × 2 = 0 + 0.962 774 399 997 056;
  • 6) 0.962 774 399 997 056 × 2 = 1 + 0.925 548 799 994 112;
  • 7) 0.925 548 799 994 112 × 2 = 1 + 0.851 097 599 988 224;
  • 8) 0.851 097 599 988 224 × 2 = 1 + 0.702 195 199 976 448;
  • 9) 0.702 195 199 976 448 × 2 = 1 + 0.404 390 399 952 896;
  • 10) 0.404 390 399 952 896 × 2 = 0 + 0.808 780 799 905 792;
  • 11) 0.808 780 799 905 792 × 2 = 1 + 0.617 561 599 811 584;
  • 12) 0.617 561 599 811 584 × 2 = 1 + 0.235 123 199 623 168;
  • 13) 0.235 123 199 623 168 × 2 = 0 + 0.470 246 399 246 336;
  • 14) 0.470 246 399 246 336 × 2 = 0 + 0.940 492 798 492 672;
  • 15) 0.940 492 798 492 672 × 2 = 1 + 0.880 985 596 985 344;
  • 16) 0.880 985 596 985 344 × 2 = 1 + 0.761 971 193 970 688;
  • 17) 0.761 971 193 970 688 × 2 = 1 + 0.523 942 387 941 376;
  • 18) 0.523 942 387 941 376 × 2 = 1 + 0.047 884 775 882 752;
  • 19) 0.047 884 775 882 752 × 2 = 0 + 0.095 769 551 765 504;
  • 20) 0.095 769 551 765 504 × 2 = 0 + 0.191 539 103 531 008;
  • 21) 0.191 539 103 531 008 × 2 = 0 + 0.383 078 207 062 016;
  • 22) 0.383 078 207 062 016 × 2 = 0 + 0.766 156 414 124 032;
  • 23) 0.766 156 414 124 032 × 2 = 1 + 0.532 312 828 248 064;
  • 24) 0.532 312 828 248 064 × 2 = 1 + 0.064 625 656 496 128;
  • 25) 0.064 625 656 496 128 × 2 = 0 + 0.129 251 312 992 256;
  • 26) 0.129 251 312 992 256 × 2 = 0 + 0.258 502 625 984 512;
  • 27) 0.258 502 625 984 512 × 2 = 0 + 0.517 005 251 969 024;
  • 28) 0.517 005 251 969 024 × 2 = 1 + 0.034 010 503 938 048;
  • 29) 0.034 010 503 938 048 × 2 = 0 + 0.068 021 007 876 096;
  • 30) 0.068 021 007 876 096 × 2 = 0 + 0.136 042 015 752 192;
  • 31) 0.136 042 015 752 192 × 2 = 0 + 0.272 084 031 504 384;
  • 32) 0.272 084 031 504 384 × 2 = 0 + 0.544 168 063 008 768;
  • 33) 0.544 168 063 008 768 × 2 = 1 + 0.088 336 126 017 536;
  • 34) 0.088 336 126 017 536 × 2 = 0 + 0.176 672 252 035 072;
  • 35) 0.176 672 252 035 072 × 2 = 0 + 0.353 344 504 070 144;
  • 36) 0.353 344 504 070 144 × 2 = 0 + 0.706 689 008 140 288;
  • 37) 0.706 689 008 140 288 × 2 = 1 + 0.413 378 016 280 576;
  • 38) 0.413 378 016 280 576 × 2 = 0 + 0.826 756 032 561 152;
  • 39) 0.826 756 032 561 152 × 2 = 1 + 0.653 512 065 122 304;
  • 40) 0.653 512 065 122 304 × 2 = 1 + 0.307 024 130 244 608;
  • 41) 0.307 024 130 244 608 × 2 = 0 + 0.614 048 260 489 216;
  • 42) 0.614 048 260 489 216 × 2 = 1 + 0.228 096 520 978 432;
  • 43) 0.228 096 520 978 432 × 2 = 0 + 0.456 193 041 956 864;
  • 44) 0.456 193 041 956 864 × 2 = 0 + 0.912 386 083 913 728;
  • 45) 0.912 386 083 913 728 × 2 = 1 + 0.824 772 167 827 456;
  • 46) 0.824 772 167 827 456 × 2 = 1 + 0.649 544 335 654 912;
  • 47) 0.649 544 335 654 912 × 2 = 1 + 0.299 088 671 309 824;
  • 48) 0.299 088 671 309 824 × 2 = 0 + 0.598 177 342 619 648;
  • 49) 0.598 177 342 619 648 × 2 = 1 + 0.196 354 685 239 296;
  • 50) 0.196 354 685 239 296 × 2 = 0 + 0.392 709 370 478 592;
  • 51) 0.392 709 370 478 592 × 2 = 0 + 0.785 418 740 957 184;
  • 52) 0.785 418 740 957 184 × 2 = 1 + 0.570 837 481 914 368;
  • 53) 0.570 837 481 914 368 × 2 = 1 + 0.141 674 963 828 736;

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:


0.780 086 699 999 908(10) =


0.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0100 1110 1001 1(2)

5. Positive number before normalization:

33.780 086 699 999 908(10) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0100 1110 1001 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 5 positions to the left, so that only one non zero digit remains to the left of it:


33.780 086 699 999 908(10) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0100 1110 1001 1(2) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0100 1110 1001 1(2) × 20 =


1.0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1010 0111 0100 11(2) × 25


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): 5


Mantissa (not normalized):
1.0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1010 0111 0100 11


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


5 + 2(11-1) - 1 =


(5 + 1 023)(10) =


1 028(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;
  • 1 028 ÷ 2 = 514 + 0;
  • 514 ÷ 2 = 257 + 0;
  • 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) =


1028(10) =


100 0000 0100(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. 0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1010 0111 01 0011 =


0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 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 0100


Mantissa (52 bits) =
0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1010 0111


Decimal number 33.780 086 699 999 908 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0100 - 0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 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