654.599 999 999 999 824 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 654.599 999 999 999 824(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
654.599 999 999 999 824(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: 0.599 999 999 999 824.

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) 0.599 999 999 999 824 × 2 = 1 + 0.199 999 999 999 648;
  • 2) 0.199 999 999 999 648 × 2 = 0 + 0.399 999 999 999 296;
  • 3) 0.399 999 999 999 296 × 2 = 0 + 0.799 999 999 998 592;
  • 4) 0.799 999 999 998 592 × 2 = 1 + 0.599 999 999 997 184;
  • 5) 0.599 999 999 997 184 × 2 = 1 + 0.199 999 999 994 368;
  • 6) 0.199 999 999 994 368 × 2 = 0 + 0.399 999 999 988 736;
  • 7) 0.399 999 999 988 736 × 2 = 0 + 0.799 999 999 977 472;
  • 8) 0.799 999 999 977 472 × 2 = 1 + 0.599 999 999 954 944;
  • 9) 0.599 999 999 954 944 × 2 = 1 + 0.199 999 999 909 888;
  • 10) 0.199 999 999 909 888 × 2 = 0 + 0.399 999 999 819 776;
  • 11) 0.399 999 999 819 776 × 2 = 0 + 0.799 999 999 639 552;
  • 12) 0.799 999 999 639 552 × 2 = 1 + 0.599 999 999 279 104;
  • 13) 0.599 999 999 279 104 × 2 = 1 + 0.199 999 998 558 208;
  • 14) 0.199 999 998 558 208 × 2 = 0 + 0.399 999 997 116 416;
  • 15) 0.399 999 997 116 416 × 2 = 0 + 0.799 999 994 232 832;
  • 16) 0.799 999 994 232 832 × 2 = 1 + 0.599 999 988 465 664;
  • 17) 0.599 999 988 465 664 × 2 = 1 + 0.199 999 976 931 328;
  • 18) 0.199 999 976 931 328 × 2 = 0 + 0.399 999 953 862 656;
  • 19) 0.399 999 953 862 656 × 2 = 0 + 0.799 999 907 725 312;
  • 20) 0.799 999 907 725 312 × 2 = 1 + 0.599 999 815 450 624;
  • 21) 0.599 999 815 450 624 × 2 = 1 + 0.199 999 630 901 248;
  • 22) 0.199 999 630 901 248 × 2 = 0 + 0.399 999 261 802 496;
  • 23) 0.399 999 261 802 496 × 2 = 0 + 0.799 998 523 604 992;
  • 24) 0.799 998 523 604 992 × 2 = 1 + 0.599 997 047 209 984;
  • 25) 0.599 997 047 209 984 × 2 = 1 + 0.199 994 094 419 968;
  • 26) 0.199 994 094 419 968 × 2 = 0 + 0.399 988 188 839 936;
  • 27) 0.399 988 188 839 936 × 2 = 0 + 0.799 976 377 679 872;
  • 28) 0.799 976 377 679 872 × 2 = 1 + 0.599 952 755 359 744;
  • 29) 0.599 952 755 359 744 × 2 = 1 + 0.199 905 510 719 488;
  • 30) 0.199 905 510 719 488 × 2 = 0 + 0.399 811 021 438 976;
  • 31) 0.399 811 021 438 976 × 2 = 0 + 0.799 622 042 877 952;
  • 32) 0.799 622 042 877 952 × 2 = 1 + 0.599 244 085 755 904;
  • 33) 0.599 244 085 755 904 × 2 = 1 + 0.198 488 171 511 808;
  • 34) 0.198 488 171 511 808 × 2 = 0 + 0.396 976 343 023 616;
  • 35) 0.396 976 343 023 616 × 2 = 0 + 0.793 952 686 047 232;
  • 36) 0.793 952 686 047 232 × 2 = 1 + 0.587 905 372 094 464;
  • 37) 0.587 905 372 094 464 × 2 = 1 + 0.175 810 744 188 928;
  • 38) 0.175 810 744 188 928 × 2 = 0 + 0.351 621 488 377 856;
  • 39) 0.351 621 488 377 856 × 2 = 0 + 0.703 242 976 755 712;
  • 40) 0.703 242 976 755 712 × 2 = 1 + 0.406 485 953 511 424;
  • 41) 0.406 485 953 511 424 × 2 = 0 + 0.812 971 907 022 848;
  • 42) 0.812 971 907 022 848 × 2 = 1 + 0.625 943 814 045 696;
  • 43) 0.625 943 814 045 696 × 2 = 1 + 0.251 887 628 091 392;
  • 44) 0.251 887 628 091 392 × 2 = 0 + 0.503 775 256 182 784;
  • 45) 0.503 775 256 182 784 × 2 = 1 + 0.007 550 512 365 568;
  • 46) 0.007 550 512 365 568 × 2 = 0 + 0.015 101 024 731 136;
  • 47) 0.015 101 024 731 136 × 2 = 0 + 0.030 202 049 462 272;
  • 48) 0.030 202 049 462 272 × 2 = 0 + 0.060 404 098 924 544;
  • 49) 0.060 404 098 924 544 × 2 = 0 + 0.120 808 197 849 088;
  • 50) 0.120 808 197 849 088 × 2 = 0 + 0.241 616 395 698 176;
  • 51) 0.241 616 395 698 176 × 2 = 0 + 0.483 232 791 396 352;
  • 52) 0.483 232 791 396 352 × 2 = 0 + 0.966 465 582 792 704;
  • 53) 0.966 465 582 792 704 × 2 = 1 + 0.932 931 165 585 408;

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:


0.599 999 999 999 824(10) =


0.1001 1001 1001 1001 1001 1001 1001 1001 1001 1001 0110 1000 0000 1(2)

5. Positive number before normalization:

654.599 999 999 999 824(10) =


10 1000 1110.1001 1001 1001 1001 1001 1001 1001 1001 1001 1001 0110 1000 0000 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:


654.599 999 999 999 824(10) =


10 1000 1110.1001 1001 1001 1001 1001 1001 1001 1001 1001 1001 0110 1000 0000 1(2) =


10 1000 1110.1001 1001 1001 1001 1001 1001 1001 1001 1001 1001 0110 1000 0000 1(2) × 20 =


1.0100 0111 0100 1100 1100 1100 1100 1100 1100 1100 1100 1100 1011 0100 0000 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 1011 0100 0000 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 1011 01 0000 0001 =


0100 0111 0100 1100 1100 1100 1100 1100 1100 1100 1100 1100 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 1000


Mantissa (52 bits) =
0100 0111 0100 1100 1100 1100 1100 1100 1100 1100 1100 1100 1011


Decimal number 654.599 999 999 999 824 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 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