654.599 999 999 999 776 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 654.599 999 999 999 776(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
654.599 999 999 999 776(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: 654.
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;
  • 654 ÷ 2 = 327 + 0;
  • 327 ÷ 2 = 163 + 1;
  • 163 ÷ 2 = 81 + 1;
  • 81 ÷ 2 = 40 + 1;
  • 40 ÷ 2 = 20 + 0;
  • 20 ÷ 2 = 10 + 0;
  • 10 ÷ 2 = 5 + 0;
  • 5 ÷ 2 = 2 + 1;
  • 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.

654(10) =


10 1000 1110(2)


3. Convert to binary (base 2) the fractional part: 0.599 999 999 999 776.

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) 0.599 999 999 999 776 × 2 = 1 + 0.199 999 999 999 552;
  • 2) 0.199 999 999 999 552 × 2 = 0 + 0.399 999 999 999 104;
  • 3) 0.399 999 999 999 104 × 2 = 0 + 0.799 999 999 998 208;
  • 4) 0.799 999 999 998 208 × 2 = 1 + 0.599 999 999 996 416;
  • 5) 0.599 999 999 996 416 × 2 = 1 + 0.199 999 999 992 832;
  • 6) 0.199 999 999 992 832 × 2 = 0 + 0.399 999 999 985 664;
  • 7) 0.399 999 999 985 664 × 2 = 0 + 0.799 999 999 971 328;
  • 8) 0.799 999 999 971 328 × 2 = 1 + 0.599 999 999 942 656;
  • 9) 0.599 999 999 942 656 × 2 = 1 + 0.199 999 999 885 312;
  • 10) 0.199 999 999 885 312 × 2 = 0 + 0.399 999 999 770 624;
  • 11) 0.399 999 999 770 624 × 2 = 0 + 0.799 999 999 541 248;
  • 12) 0.799 999 999 541 248 × 2 = 1 + 0.599 999 999 082 496;
  • 13) 0.599 999 999 082 496 × 2 = 1 + 0.199 999 998 164 992;
  • 14) 0.199 999 998 164 992 × 2 = 0 + 0.399 999 996 329 984;
  • 15) 0.399 999 996 329 984 × 2 = 0 + 0.799 999 992 659 968;
  • 16) 0.799 999 992 659 968 × 2 = 1 + 0.599 999 985 319 936;
  • 17) 0.599 999 985 319 936 × 2 = 1 + 0.199 999 970 639 872;
  • 18) 0.199 999 970 639 872 × 2 = 0 + 0.399 999 941 279 744;
  • 19) 0.399 999 941 279 744 × 2 = 0 + 0.799 999 882 559 488;
  • 20) 0.799 999 882 559 488 × 2 = 1 + 0.599 999 765 118 976;
  • 21) 0.599 999 765 118 976 × 2 = 1 + 0.199 999 530 237 952;
  • 22) 0.199 999 530 237 952 × 2 = 0 + 0.399 999 060 475 904;
  • 23) 0.399 999 060 475 904 × 2 = 0 + 0.799 998 120 951 808;
  • 24) 0.799 998 120 951 808 × 2 = 1 + 0.599 996 241 903 616;
  • 25) 0.599 996 241 903 616 × 2 = 1 + 0.199 992 483 807 232;
  • 26) 0.199 992 483 807 232 × 2 = 0 + 0.399 984 967 614 464;
  • 27) 0.399 984 967 614 464 × 2 = 0 + 0.799 969 935 228 928;
  • 28) 0.799 969 935 228 928 × 2 = 1 + 0.599 939 870 457 856;
  • 29) 0.599 939 870 457 856 × 2 = 1 + 0.199 879 740 915 712;
  • 30) 0.199 879 740 915 712 × 2 = 0 + 0.399 759 481 831 424;
  • 31) 0.399 759 481 831 424 × 2 = 0 + 0.799 518 963 662 848;
  • 32) 0.799 518 963 662 848 × 2 = 1 + 0.599 037 927 325 696;
  • 33) 0.599 037 927 325 696 × 2 = 1 + 0.198 075 854 651 392;
  • 34) 0.198 075 854 651 392 × 2 = 0 + 0.396 151 709 302 784;
  • 35) 0.396 151 709 302 784 × 2 = 0 + 0.792 303 418 605 568;
  • 36) 0.792 303 418 605 568 × 2 = 1 + 0.584 606 837 211 136;
  • 37) 0.584 606 837 211 136 × 2 = 1 + 0.169 213 674 422 272;
  • 38) 0.169 213 674 422 272 × 2 = 0 + 0.338 427 348 844 544;
  • 39) 0.338 427 348 844 544 × 2 = 0 + 0.676 854 697 689 088;
  • 40) 0.676 854 697 689 088 × 2 = 1 + 0.353 709 395 378 176;
  • 41) 0.353 709 395 378 176 × 2 = 0 + 0.707 418 790 756 352;
  • 42) 0.707 418 790 756 352 × 2 = 1 + 0.414 837 581 512 704;
  • 43) 0.414 837 581 512 704 × 2 = 0 + 0.829 675 163 025 408;
  • 44) 0.829 675 163 025 408 × 2 = 1 + 0.659 350 326 050 816;
  • 45) 0.659 350 326 050 816 × 2 = 1 + 0.318 700 652 101 632;
  • 46) 0.318 700 652 101 632 × 2 = 0 + 0.637 401 304 203 264;
  • 47) 0.637 401 304 203 264 × 2 = 1 + 0.274 802 608 406 528;
  • 48) 0.274 802 608 406 528 × 2 = 0 + 0.549 605 216 813 056;
  • 49) 0.549 605 216 813 056 × 2 = 1 + 0.099 210 433 626 112;
  • 50) 0.099 210 433 626 112 × 2 = 0 + 0.198 420 867 252 224;
  • 51) 0.198 420 867 252 224 × 2 = 0 + 0.396 841 734 504 448;
  • 52) 0.396 841 734 504 448 × 2 = 0 + 0.793 683 469 008 896;
  • 53) 0.793 683 469 008 896 × 2 = 1 + 0.587 366 938 017 792;

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:


0.599 999 999 999 776(10) =


0.1001 1001 1001 1001 1001 1001 1001 1001 1001 1001 0101 1010 1000 1(2)

5. Positive number before normalization:

654.599 999 999 999 776(10) =


10 1000 1110.1001 1001 1001 1001 1001 1001 1001 1001 1001 1001 0101 1010 1000 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 9 positions to the left, so that only one non zero digit remains to the left of it:


654.599 999 999 999 776(10) =


10 1000 1110.1001 1001 1001 1001 1001 1001 1001 1001 1001 1001 0101 1010 1000 1(2) =


10 1000 1110.1001 1001 1001 1001 1001 1001 1001 1001 1001 1001 0101 1010 1000 1(2) × 20 =


1.0100 0111 0100 1100 1100 1100 1100 1100 1100 1100 1100 1100 1010 1101 0100 01(2) × 29


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): 9


Mantissa (not normalized):
1.0100 0111 0100 1100 1100 1100 1100 1100 1100 1100 1100 1100 1010 1101 0100 01


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


9 + 2(11-1) - 1 =


(9 + 1 023)(10) =


1 032(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;
  • 1 032 ÷ 2 = 516 + 0;
  • 516 ÷ 2 = 258 + 0;
  • 258 ÷ 2 = 129 + 0;
  • 129 ÷ 2 = 64 + 1;
  • 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) =


1032(10) =


100 0000 1000(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. 0100 0111 0100 1100 1100 1100 1100 1100 1100 1100 1100 1100 1010 11 0101 0001 =


0100 0111 0100 1100 1100 1100 1100 1100 1100 1100 1100 1100 1010


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 1000


Mantissa (52 bits) =
0100 0111 0100 1100 1100 1100 1100 1100 1100 1100 1100 1100 1010


Decimal number 654.599 999 999 999 776 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 1000 - 0100 0111 0100 1100 1100 1100 1100 1100 1100 1100 1100 1100 1010


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