33.780 086 699 999 857 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 33.780 086 699 999 857(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
33.780 086 699 999 857(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: 0.780 086 699 999 857.

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) 0.780 086 699 999 857 × 2 = 1 + 0.560 173 399 999 714;
  • 2) 0.560 173 399 999 714 × 2 = 1 + 0.120 346 799 999 428;
  • 3) 0.120 346 799 999 428 × 2 = 0 + 0.240 693 599 998 856;
  • 4) 0.240 693 599 998 856 × 2 = 0 + 0.481 387 199 997 712;
  • 5) 0.481 387 199 997 712 × 2 = 0 + 0.962 774 399 995 424;
  • 6) 0.962 774 399 995 424 × 2 = 1 + 0.925 548 799 990 848;
  • 7) 0.925 548 799 990 848 × 2 = 1 + 0.851 097 599 981 696;
  • 8) 0.851 097 599 981 696 × 2 = 1 + 0.702 195 199 963 392;
  • 9) 0.702 195 199 963 392 × 2 = 1 + 0.404 390 399 926 784;
  • 10) 0.404 390 399 926 784 × 2 = 0 + 0.808 780 799 853 568;
  • 11) 0.808 780 799 853 568 × 2 = 1 + 0.617 561 599 707 136;
  • 12) 0.617 561 599 707 136 × 2 = 1 + 0.235 123 199 414 272;
  • 13) 0.235 123 199 414 272 × 2 = 0 + 0.470 246 398 828 544;
  • 14) 0.470 246 398 828 544 × 2 = 0 + 0.940 492 797 657 088;
  • 15) 0.940 492 797 657 088 × 2 = 1 + 0.880 985 595 314 176;
  • 16) 0.880 985 595 314 176 × 2 = 1 + 0.761 971 190 628 352;
  • 17) 0.761 971 190 628 352 × 2 = 1 + 0.523 942 381 256 704;
  • 18) 0.523 942 381 256 704 × 2 = 1 + 0.047 884 762 513 408;
  • 19) 0.047 884 762 513 408 × 2 = 0 + 0.095 769 525 026 816;
  • 20) 0.095 769 525 026 816 × 2 = 0 + 0.191 539 050 053 632;
  • 21) 0.191 539 050 053 632 × 2 = 0 + 0.383 078 100 107 264;
  • 22) 0.383 078 100 107 264 × 2 = 0 + 0.766 156 200 214 528;
  • 23) 0.766 156 200 214 528 × 2 = 1 + 0.532 312 400 429 056;
  • 24) 0.532 312 400 429 056 × 2 = 1 + 0.064 624 800 858 112;
  • 25) 0.064 624 800 858 112 × 2 = 0 + 0.129 249 601 716 224;
  • 26) 0.129 249 601 716 224 × 2 = 0 + 0.258 499 203 432 448;
  • 27) 0.258 499 203 432 448 × 2 = 0 + 0.516 998 406 864 896;
  • 28) 0.516 998 406 864 896 × 2 = 1 + 0.033 996 813 729 792;
  • 29) 0.033 996 813 729 792 × 2 = 0 + 0.067 993 627 459 584;
  • 30) 0.067 993 627 459 584 × 2 = 0 + 0.135 987 254 919 168;
  • 31) 0.135 987 254 919 168 × 2 = 0 + 0.271 974 509 838 336;
  • 32) 0.271 974 509 838 336 × 2 = 0 + 0.543 949 019 676 672;
  • 33) 0.543 949 019 676 672 × 2 = 1 + 0.087 898 039 353 344;
  • 34) 0.087 898 039 353 344 × 2 = 0 + 0.175 796 078 706 688;
  • 35) 0.175 796 078 706 688 × 2 = 0 + 0.351 592 157 413 376;
  • 36) 0.351 592 157 413 376 × 2 = 0 + 0.703 184 314 826 752;
  • 37) 0.703 184 314 826 752 × 2 = 1 + 0.406 368 629 653 504;
  • 38) 0.406 368 629 653 504 × 2 = 0 + 0.812 737 259 307 008;
  • 39) 0.812 737 259 307 008 × 2 = 1 + 0.625 474 518 614 016;
  • 40) 0.625 474 518 614 016 × 2 = 1 + 0.250 949 037 228 032;
  • 41) 0.250 949 037 228 032 × 2 = 0 + 0.501 898 074 456 064;
  • 42) 0.501 898 074 456 064 × 2 = 1 + 0.003 796 148 912 128;
  • 43) 0.003 796 148 912 128 × 2 = 0 + 0.007 592 297 824 256;
  • 44) 0.007 592 297 824 256 × 2 = 0 + 0.015 184 595 648 512;
  • 45) 0.015 184 595 648 512 × 2 = 0 + 0.030 369 191 297 024;
  • 46) 0.030 369 191 297 024 × 2 = 0 + 0.060 738 382 594 048;
  • 47) 0.060 738 382 594 048 × 2 = 0 + 0.121 476 765 188 096;
  • 48) 0.121 476 765 188 096 × 2 = 0 + 0.242 953 530 376 192;
  • 49) 0.242 953 530 376 192 × 2 = 0 + 0.485 907 060 752 384;
  • 50) 0.485 907 060 752 384 × 2 = 0 + 0.971 814 121 504 768;
  • 51) 0.971 814 121 504 768 × 2 = 1 + 0.943 628 243 009 536;
  • 52) 0.943 628 243 009 536 × 2 = 1 + 0.887 256 486 019 072;
  • 53) 0.887 256 486 019 072 × 2 = 1 + 0.774 512 972 038 144;

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:


0.780 086 699 999 857(10) =


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

5. Positive number before normalization:

33.780 086 699 999 857(10) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0100 0000 0011 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:


33.780 086 699 999 857(10) =


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


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


1.0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1010 0000 0001 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 0000 0001 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 0000 00 0111 =


0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1010 0000


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 0000


Decimal number 33.780 086 699 999 857 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 0000


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