0.120 000 000 014 3 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.120 000 000 014 3(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
0.120 000 000 014 3(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: 0.
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;
  • 0 ÷ 2 = 0 + 0;

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.

0(10) =


0(2)


3. Convert to binary (base 2) the fractional part: 0.120 000 000 014 3.

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) 0.120 000 000 014 3 × 2 = 0 + 0.240 000 000 028 6;
  • 2) 0.240 000 000 028 6 × 2 = 0 + 0.480 000 000 057 2;
  • 3) 0.480 000 000 057 2 × 2 = 0 + 0.960 000 000 114 4;
  • 4) 0.960 000 000 114 4 × 2 = 1 + 0.920 000 000 228 8;
  • 5) 0.920 000 000 228 8 × 2 = 1 + 0.840 000 000 457 6;
  • 6) 0.840 000 000 457 6 × 2 = 1 + 0.680 000 000 915 2;
  • 7) 0.680 000 000 915 2 × 2 = 1 + 0.360 000 001 830 4;
  • 8) 0.360 000 001 830 4 × 2 = 0 + 0.720 000 003 660 8;
  • 9) 0.720 000 003 660 8 × 2 = 1 + 0.440 000 007 321 6;
  • 10) 0.440 000 007 321 6 × 2 = 0 + 0.880 000 014 643 2;
  • 11) 0.880 000 014 643 2 × 2 = 1 + 0.760 000 029 286 4;
  • 12) 0.760 000 029 286 4 × 2 = 1 + 0.520 000 058 572 8;
  • 13) 0.520 000 058 572 8 × 2 = 1 + 0.040 000 117 145 6;
  • 14) 0.040 000 117 145 6 × 2 = 0 + 0.080 000 234 291 2;
  • 15) 0.080 000 234 291 2 × 2 = 0 + 0.160 000 468 582 4;
  • 16) 0.160 000 468 582 4 × 2 = 0 + 0.320 000 937 164 8;
  • 17) 0.320 000 937 164 8 × 2 = 0 + 0.640 001 874 329 6;
  • 18) 0.640 001 874 329 6 × 2 = 1 + 0.280 003 748 659 2;
  • 19) 0.280 003 748 659 2 × 2 = 0 + 0.560 007 497 318 4;
  • 20) 0.560 007 497 318 4 × 2 = 1 + 0.120 014 994 636 8;
  • 21) 0.120 014 994 636 8 × 2 = 0 + 0.240 029 989 273 6;
  • 22) 0.240 029 989 273 6 × 2 = 0 + 0.480 059 978 547 2;
  • 23) 0.480 059 978 547 2 × 2 = 0 + 0.960 119 957 094 4;
  • 24) 0.960 119 957 094 4 × 2 = 1 + 0.920 239 914 188 8;
  • 25) 0.920 239 914 188 8 × 2 = 1 + 0.840 479 828 377 6;
  • 26) 0.840 479 828 377 6 × 2 = 1 + 0.680 959 656 755 2;
  • 27) 0.680 959 656 755 2 × 2 = 1 + 0.361 919 313 510 4;
  • 28) 0.361 919 313 510 4 × 2 = 0 + 0.723 838 627 020 8;
  • 29) 0.723 838 627 020 8 × 2 = 1 + 0.447 677 254 041 6;
  • 30) 0.447 677 254 041 6 × 2 = 0 + 0.895 354 508 083 2;
  • 31) 0.895 354 508 083 2 × 2 = 1 + 0.790 709 016 166 4;
  • 32) 0.790 709 016 166 4 × 2 = 1 + 0.581 418 032 332 8;
  • 33) 0.581 418 032 332 8 × 2 = 1 + 0.162 836 064 665 6;
  • 34) 0.162 836 064 665 6 × 2 = 0 + 0.325 672 129 331 2;
  • 35) 0.325 672 129 331 2 × 2 = 0 + 0.651 344 258 662 4;
  • 36) 0.651 344 258 662 4 × 2 = 1 + 0.302 688 517 324 8;
  • 37) 0.302 688 517 324 8 × 2 = 0 + 0.605 377 034 649 6;
  • 38) 0.605 377 034 649 6 × 2 = 1 + 0.210 754 069 299 2;
  • 39) 0.210 754 069 299 2 × 2 = 0 + 0.421 508 138 598 4;
  • 40) 0.421 508 138 598 4 × 2 = 0 + 0.843 016 277 196 8;
  • 41) 0.843 016 277 196 8 × 2 = 1 + 0.686 032 554 393 6;
  • 42) 0.686 032 554 393 6 × 2 = 1 + 0.372 065 108 787 2;
  • 43) 0.372 065 108 787 2 × 2 = 0 + 0.744 130 217 574 4;
  • 44) 0.744 130 217 574 4 × 2 = 1 + 0.488 260 435 148 8;
  • 45) 0.488 260 435 148 8 × 2 = 0 + 0.976 520 870 297 6;
  • 46) 0.976 520 870 297 6 × 2 = 1 + 0.953 041 740 595 2;
  • 47) 0.953 041 740 595 2 × 2 = 1 + 0.906 083 481 190 4;
  • 48) 0.906 083 481 190 4 × 2 = 1 + 0.812 166 962 380 8;
  • 49) 0.812 166 962 380 8 × 2 = 1 + 0.624 333 924 761 6;
  • 50) 0.624 333 924 761 6 × 2 = 1 + 0.248 667 849 523 2;
  • 51) 0.248 667 849 523 2 × 2 = 0 + 0.497 335 699 046 4;
  • 52) 0.497 335 699 046 4 × 2 = 0 + 0.994 671 398 092 8;
  • 53) 0.994 671 398 092 8 × 2 = 1 + 0.989 342 796 185 6;
  • 54) 0.989 342 796 185 6 × 2 = 1 + 0.978 685 592 371 2;
  • 55) 0.978 685 592 371 2 × 2 = 1 + 0.957 371 184 742 4;
  • 56) 0.957 371 184 742 4 × 2 = 1 + 0.914 742 369 484 8;

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:


0.120 000 000 014 3(10) =


0.0001 1110 1011 1000 0101 0001 1110 1011 1001 0100 1101 0111 1100 1111(2)

5. Positive number before normalization:

0.120 000 000 014 3(10) =


0.0001 1110 1011 1000 0101 0001 1110 1011 1001 0100 1101 0111 1100 1111(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 4 positions to the right, so that only one non zero digit remains to the left of it:


0.120 000 000 014 3(10) =


0.0001 1110 1011 1000 0101 0001 1110 1011 1001 0100 1101 0111 1100 1111(2) =


0.0001 1110 1011 1000 0101 0001 1110 1011 1001 0100 1101 0111 1100 1111(2) × 20 =


1.1110 1011 1000 0101 0001 1110 1011 1001 0100 1101 0111 1100 1111(2) × 2-4


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): -4


Mantissa (not normalized):
1.1110 1011 1000 0101 0001 1110 1011 1001 0100 1101 0111 1100 1111


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


-4 + 2(11-1) - 1 =


(-4 + 1 023)(10) =


1 019(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;
  • 1 019 ÷ 2 = 509 + 1;
  • 509 ÷ 2 = 254 + 1;
  • 254 ÷ 2 = 127 + 0;
  • 127 ÷ 2 = 63 + 1;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 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) =


1019(10) =


011 1111 1011(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, only if necessary (not the case here).


Mantissa (normalized) =


1. 1110 1011 1000 0101 0001 1110 1011 1001 0100 1101 0111 1100 1111 =


1110 1011 1000 0101 0001 1110 1011 1001 0100 1101 0111 1100 1111


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) =
011 1111 1011


Mantissa (52 bits) =
1110 1011 1000 0101 0001 1110 1011 1001 0100 1101 0111 1100 1111


Decimal number 0.120 000 000 014 3 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 011 1111 1011 - 1110 1011 1000 0101 0001 1110 1011 1001 0100 1101 0111 1100 1111


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