33.780 086 699 999 822 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 33.780 086 699 999 822(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
33.780 086 699 999 822(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: 0.780 086 699 999 822.

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) 0.780 086 699 999 822 × 2 = 1 + 0.560 173 399 999 644;
  • 2) 0.560 173 399 999 644 × 2 = 1 + 0.120 346 799 999 288;
  • 3) 0.120 346 799 999 288 × 2 = 0 + 0.240 693 599 998 576;
  • 4) 0.240 693 599 998 576 × 2 = 0 + 0.481 387 199 997 152;
  • 5) 0.481 387 199 997 152 × 2 = 0 + 0.962 774 399 994 304;
  • 6) 0.962 774 399 994 304 × 2 = 1 + 0.925 548 799 988 608;
  • 7) 0.925 548 799 988 608 × 2 = 1 + 0.851 097 599 977 216;
  • 8) 0.851 097 599 977 216 × 2 = 1 + 0.702 195 199 954 432;
  • 9) 0.702 195 199 954 432 × 2 = 1 + 0.404 390 399 908 864;
  • 10) 0.404 390 399 908 864 × 2 = 0 + 0.808 780 799 817 728;
  • 11) 0.808 780 799 817 728 × 2 = 1 + 0.617 561 599 635 456;
  • 12) 0.617 561 599 635 456 × 2 = 1 + 0.235 123 199 270 912;
  • 13) 0.235 123 199 270 912 × 2 = 0 + 0.470 246 398 541 824;
  • 14) 0.470 246 398 541 824 × 2 = 0 + 0.940 492 797 083 648;
  • 15) 0.940 492 797 083 648 × 2 = 1 + 0.880 985 594 167 296;
  • 16) 0.880 985 594 167 296 × 2 = 1 + 0.761 971 188 334 592;
  • 17) 0.761 971 188 334 592 × 2 = 1 + 0.523 942 376 669 184;
  • 18) 0.523 942 376 669 184 × 2 = 1 + 0.047 884 753 338 368;
  • 19) 0.047 884 753 338 368 × 2 = 0 + 0.095 769 506 676 736;
  • 20) 0.095 769 506 676 736 × 2 = 0 + 0.191 539 013 353 472;
  • 21) 0.191 539 013 353 472 × 2 = 0 + 0.383 078 026 706 944;
  • 22) 0.383 078 026 706 944 × 2 = 0 + 0.766 156 053 413 888;
  • 23) 0.766 156 053 413 888 × 2 = 1 + 0.532 312 106 827 776;
  • 24) 0.532 312 106 827 776 × 2 = 1 + 0.064 624 213 655 552;
  • 25) 0.064 624 213 655 552 × 2 = 0 + 0.129 248 427 311 104;
  • 26) 0.129 248 427 311 104 × 2 = 0 + 0.258 496 854 622 208;
  • 27) 0.258 496 854 622 208 × 2 = 0 + 0.516 993 709 244 416;
  • 28) 0.516 993 709 244 416 × 2 = 1 + 0.033 987 418 488 832;
  • 29) 0.033 987 418 488 832 × 2 = 0 + 0.067 974 836 977 664;
  • 30) 0.067 974 836 977 664 × 2 = 0 + 0.135 949 673 955 328;
  • 31) 0.135 949 673 955 328 × 2 = 0 + 0.271 899 347 910 656;
  • 32) 0.271 899 347 910 656 × 2 = 0 + 0.543 798 695 821 312;
  • 33) 0.543 798 695 821 312 × 2 = 1 + 0.087 597 391 642 624;
  • 34) 0.087 597 391 642 624 × 2 = 0 + 0.175 194 783 285 248;
  • 35) 0.175 194 783 285 248 × 2 = 0 + 0.350 389 566 570 496;
  • 36) 0.350 389 566 570 496 × 2 = 0 + 0.700 779 133 140 992;
  • 37) 0.700 779 133 140 992 × 2 = 1 + 0.401 558 266 281 984;
  • 38) 0.401 558 266 281 984 × 2 = 0 + 0.803 116 532 563 968;
  • 39) 0.803 116 532 563 968 × 2 = 1 + 0.606 233 065 127 936;
  • 40) 0.606 233 065 127 936 × 2 = 1 + 0.212 466 130 255 872;
  • 41) 0.212 466 130 255 872 × 2 = 0 + 0.424 932 260 511 744;
  • 42) 0.424 932 260 511 744 × 2 = 0 + 0.849 864 521 023 488;
  • 43) 0.849 864 521 023 488 × 2 = 1 + 0.699 729 042 046 976;
  • 44) 0.699 729 042 046 976 × 2 = 1 + 0.399 458 084 093 952;
  • 45) 0.399 458 084 093 952 × 2 = 0 + 0.798 916 168 187 904;
  • 46) 0.798 916 168 187 904 × 2 = 1 + 0.597 832 336 375 808;
  • 47) 0.597 832 336 375 808 × 2 = 1 + 0.195 664 672 751 616;
  • 48) 0.195 664 672 751 616 × 2 = 0 + 0.391 329 345 503 232;
  • 49) 0.391 329 345 503 232 × 2 = 0 + 0.782 658 691 006 464;
  • 50) 0.782 658 691 006 464 × 2 = 1 + 0.565 317 382 012 928;
  • 51) 0.565 317 382 012 928 × 2 = 1 + 0.130 634 764 025 856;
  • 52) 0.130 634 764 025 856 × 2 = 0 + 0.261 269 528 051 712;
  • 53) 0.261 269 528 051 712 × 2 = 0 + 0.522 539 056 103 424;

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:


0.780 086 699 999 822(10) =


0.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0011 0110 0110 0(2)

5. Positive number before normalization:

33.780 086 699 999 822(10) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0011 0110 0110 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:


33.780 086 699 999 822(10) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0011 0110 0110 0(2) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0011 0110 0110 0(2) × 20 =


1.0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1001 1011 0011 00(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 1011 0011 00


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 1011 00 1100 =


0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1001 1011


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 1011


Decimal number 33.780 086 699 999 822 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 1011


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