33.780 086 699 999 792 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 33.780 086 699 999 792(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
33.780 086 699 999 792(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: 0.780 086 699 999 792.

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) 0.780 086 699 999 792 × 2 = 1 + 0.560 173 399 999 584;
  • 2) 0.560 173 399 999 584 × 2 = 1 + 0.120 346 799 999 168;
  • 3) 0.120 346 799 999 168 × 2 = 0 + 0.240 693 599 998 336;
  • 4) 0.240 693 599 998 336 × 2 = 0 + 0.481 387 199 996 672;
  • 5) 0.481 387 199 996 672 × 2 = 0 + 0.962 774 399 993 344;
  • 6) 0.962 774 399 993 344 × 2 = 1 + 0.925 548 799 986 688;
  • 7) 0.925 548 799 986 688 × 2 = 1 + 0.851 097 599 973 376;
  • 8) 0.851 097 599 973 376 × 2 = 1 + 0.702 195 199 946 752;
  • 9) 0.702 195 199 946 752 × 2 = 1 + 0.404 390 399 893 504;
  • 10) 0.404 390 399 893 504 × 2 = 0 + 0.808 780 799 787 008;
  • 11) 0.808 780 799 787 008 × 2 = 1 + 0.617 561 599 574 016;
  • 12) 0.617 561 599 574 016 × 2 = 1 + 0.235 123 199 148 032;
  • 13) 0.235 123 199 148 032 × 2 = 0 + 0.470 246 398 296 064;
  • 14) 0.470 246 398 296 064 × 2 = 0 + 0.940 492 796 592 128;
  • 15) 0.940 492 796 592 128 × 2 = 1 + 0.880 985 593 184 256;
  • 16) 0.880 985 593 184 256 × 2 = 1 + 0.761 971 186 368 512;
  • 17) 0.761 971 186 368 512 × 2 = 1 + 0.523 942 372 737 024;
  • 18) 0.523 942 372 737 024 × 2 = 1 + 0.047 884 745 474 048;
  • 19) 0.047 884 745 474 048 × 2 = 0 + 0.095 769 490 948 096;
  • 20) 0.095 769 490 948 096 × 2 = 0 + 0.191 538 981 896 192;
  • 21) 0.191 538 981 896 192 × 2 = 0 + 0.383 077 963 792 384;
  • 22) 0.383 077 963 792 384 × 2 = 0 + 0.766 155 927 584 768;
  • 23) 0.766 155 927 584 768 × 2 = 1 + 0.532 311 855 169 536;
  • 24) 0.532 311 855 169 536 × 2 = 1 + 0.064 623 710 339 072;
  • 25) 0.064 623 710 339 072 × 2 = 0 + 0.129 247 420 678 144;
  • 26) 0.129 247 420 678 144 × 2 = 0 + 0.258 494 841 356 288;
  • 27) 0.258 494 841 356 288 × 2 = 0 + 0.516 989 682 712 576;
  • 28) 0.516 989 682 712 576 × 2 = 1 + 0.033 979 365 425 152;
  • 29) 0.033 979 365 425 152 × 2 = 0 + 0.067 958 730 850 304;
  • 30) 0.067 958 730 850 304 × 2 = 0 + 0.135 917 461 700 608;
  • 31) 0.135 917 461 700 608 × 2 = 0 + 0.271 834 923 401 216;
  • 32) 0.271 834 923 401 216 × 2 = 0 + 0.543 669 846 802 432;
  • 33) 0.543 669 846 802 432 × 2 = 1 + 0.087 339 693 604 864;
  • 34) 0.087 339 693 604 864 × 2 = 0 + 0.174 679 387 209 728;
  • 35) 0.174 679 387 209 728 × 2 = 0 + 0.349 358 774 419 456;
  • 36) 0.349 358 774 419 456 × 2 = 0 + 0.698 717 548 838 912;
  • 37) 0.698 717 548 838 912 × 2 = 1 + 0.397 435 097 677 824;
  • 38) 0.397 435 097 677 824 × 2 = 0 + 0.794 870 195 355 648;
  • 39) 0.794 870 195 355 648 × 2 = 1 + 0.589 740 390 711 296;
  • 40) 0.589 740 390 711 296 × 2 = 1 + 0.179 480 781 422 592;
  • 41) 0.179 480 781 422 592 × 2 = 0 + 0.358 961 562 845 184;
  • 42) 0.358 961 562 845 184 × 2 = 0 + 0.717 923 125 690 368;
  • 43) 0.717 923 125 690 368 × 2 = 1 + 0.435 846 251 380 736;
  • 44) 0.435 846 251 380 736 × 2 = 0 + 0.871 692 502 761 472;
  • 45) 0.871 692 502 761 472 × 2 = 1 + 0.743 385 005 522 944;
  • 46) 0.743 385 005 522 944 × 2 = 1 + 0.486 770 011 045 888;
  • 47) 0.486 770 011 045 888 × 2 = 0 + 0.973 540 022 091 776;
  • 48) 0.973 540 022 091 776 × 2 = 1 + 0.947 080 044 183 552;
  • 49) 0.947 080 044 183 552 × 2 = 1 + 0.894 160 088 367 104;
  • 50) 0.894 160 088 367 104 × 2 = 1 + 0.788 320 176 734 208;
  • 51) 0.788 320 176 734 208 × 2 = 1 + 0.576 640 353 468 416;
  • 52) 0.576 640 353 468 416 × 2 = 1 + 0.153 280 706 936 832;
  • 53) 0.153 280 706 936 832 × 2 = 0 + 0.306 561 413 873 664;

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:


0.780 086 699 999 792(10) =


0.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0010 1101 1111 0(2)

5. Positive number before normalization:

33.780 086 699 999 792(10) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0010 1101 1111 0(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:


33.780 086 699 999 792(10) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0010 1101 1111 0(2) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0010 1101 1111 0(2) × 20 =


1.0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1001 0110 1111 10(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 1001 0110 1111 10


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 1001 0110 11 1110 =


0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1001 0110


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 1001 0110


Decimal number 33.780 086 699 999 792 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 1001 0110


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