654.599 999 999 999 981 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 654.599 999 999 999 981(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
654.599 999 999 999 981(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: 0.599 999 999 999 981.

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) 0.599 999 999 999 981 × 2 = 1 + 0.199 999 999 999 962;
  • 2) 0.199 999 999 999 962 × 2 = 0 + 0.399 999 999 999 924;
  • 3) 0.399 999 999 999 924 × 2 = 0 + 0.799 999 999 999 848;
  • 4) 0.799 999 999 999 848 × 2 = 1 + 0.599 999 999 999 696;
  • 5) 0.599 999 999 999 696 × 2 = 1 + 0.199 999 999 999 392;
  • 6) 0.199 999 999 999 392 × 2 = 0 + 0.399 999 999 998 784;
  • 7) 0.399 999 999 998 784 × 2 = 0 + 0.799 999 999 997 568;
  • 8) 0.799 999 999 997 568 × 2 = 1 + 0.599 999 999 995 136;
  • 9) 0.599 999 999 995 136 × 2 = 1 + 0.199 999 999 990 272;
  • 10) 0.199 999 999 990 272 × 2 = 0 + 0.399 999 999 980 544;
  • 11) 0.399 999 999 980 544 × 2 = 0 + 0.799 999 999 961 088;
  • 12) 0.799 999 999 961 088 × 2 = 1 + 0.599 999 999 922 176;
  • 13) 0.599 999 999 922 176 × 2 = 1 + 0.199 999 999 844 352;
  • 14) 0.199 999 999 844 352 × 2 = 0 + 0.399 999 999 688 704;
  • 15) 0.399 999 999 688 704 × 2 = 0 + 0.799 999 999 377 408;
  • 16) 0.799 999 999 377 408 × 2 = 1 + 0.599 999 998 754 816;
  • 17) 0.599 999 998 754 816 × 2 = 1 + 0.199 999 997 509 632;
  • 18) 0.199 999 997 509 632 × 2 = 0 + 0.399 999 995 019 264;
  • 19) 0.399 999 995 019 264 × 2 = 0 + 0.799 999 990 038 528;
  • 20) 0.799 999 990 038 528 × 2 = 1 + 0.599 999 980 077 056;
  • 21) 0.599 999 980 077 056 × 2 = 1 + 0.199 999 960 154 112;
  • 22) 0.199 999 960 154 112 × 2 = 0 + 0.399 999 920 308 224;
  • 23) 0.399 999 920 308 224 × 2 = 0 + 0.799 999 840 616 448;
  • 24) 0.799 999 840 616 448 × 2 = 1 + 0.599 999 681 232 896;
  • 25) 0.599 999 681 232 896 × 2 = 1 + 0.199 999 362 465 792;
  • 26) 0.199 999 362 465 792 × 2 = 0 + 0.399 998 724 931 584;
  • 27) 0.399 998 724 931 584 × 2 = 0 + 0.799 997 449 863 168;
  • 28) 0.799 997 449 863 168 × 2 = 1 + 0.599 994 899 726 336;
  • 29) 0.599 994 899 726 336 × 2 = 1 + 0.199 989 799 452 672;
  • 30) 0.199 989 799 452 672 × 2 = 0 + 0.399 979 598 905 344;
  • 31) 0.399 979 598 905 344 × 2 = 0 + 0.799 959 197 810 688;
  • 32) 0.799 959 197 810 688 × 2 = 1 + 0.599 918 395 621 376;
  • 33) 0.599 918 395 621 376 × 2 = 1 + 0.199 836 791 242 752;
  • 34) 0.199 836 791 242 752 × 2 = 0 + 0.399 673 582 485 504;
  • 35) 0.399 673 582 485 504 × 2 = 0 + 0.799 347 164 971 008;
  • 36) 0.799 347 164 971 008 × 2 = 1 + 0.598 694 329 942 016;
  • 37) 0.598 694 329 942 016 × 2 = 1 + 0.197 388 659 884 032;
  • 38) 0.197 388 659 884 032 × 2 = 0 + 0.394 777 319 768 064;
  • 39) 0.394 777 319 768 064 × 2 = 0 + 0.789 554 639 536 128;
  • 40) 0.789 554 639 536 128 × 2 = 1 + 0.579 109 279 072 256;
  • 41) 0.579 109 279 072 256 × 2 = 1 + 0.158 218 558 144 512;
  • 42) 0.158 218 558 144 512 × 2 = 0 + 0.316 437 116 289 024;
  • 43) 0.316 437 116 289 024 × 2 = 0 + 0.632 874 232 578 048;
  • 44) 0.632 874 232 578 048 × 2 = 1 + 0.265 748 465 156 096;
  • 45) 0.265 748 465 156 096 × 2 = 0 + 0.531 496 930 312 192;
  • 46) 0.531 496 930 312 192 × 2 = 1 + 0.062 993 860 624 384;
  • 47) 0.062 993 860 624 384 × 2 = 0 + 0.125 987 721 248 768;
  • 48) 0.125 987 721 248 768 × 2 = 0 + 0.251 975 442 497 536;
  • 49) 0.251 975 442 497 536 × 2 = 0 + 0.503 950 884 995 072;
  • 50) 0.503 950 884 995 072 × 2 = 1 + 0.007 901 769 990 144;
  • 51) 0.007 901 769 990 144 × 2 = 0 + 0.015 803 539 980 288;
  • 52) 0.015 803 539 980 288 × 2 = 0 + 0.031 607 079 960 576;
  • 53) 0.031 607 079 960 576 × 2 = 0 + 0.063 214 159 921 152;

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:


0.599 999 999 999 981(10) =


0.1001 1001 1001 1001 1001 1001 1001 1001 1001 1001 1001 0100 0100 0(2)

5. Positive number before normalization:

654.599 999 999 999 981(10) =


10 1000 1110.1001 1001 1001 1001 1001 1001 1001 1001 1001 1001 1001 0100 0100 0(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:


654.599 999 999 999 981(10) =


10 1000 1110.1001 1001 1001 1001 1001 1001 1001 1001 1001 1001 1001 0100 0100 0(2) =


10 1000 1110.1001 1001 1001 1001 1001 1001 1001 1001 1001 1001 1001 0100 0100 0(2) × 20 =


1.0100 0111 0100 1100 1100 1100 1100 1100 1100 1100 1100 1100 1100 1010 0010 00(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 1100 1010 0010 00


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 1100 10 1000 1000 =


0100 0111 0100 1100 1100 1100 1100 1100 1100 1100 1100 1100 1100


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 1100


Decimal number 654.599 999 999 999 981 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 1100


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