64bit IEEE 754: Decimal ↗ Double Precision Floating Point Binary: 50.141 359 Convert the Number to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From a Base Ten Decimal System Number

Number 50.141 359(10) converted and written in 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: 50.
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;
  • 50 ÷ 2 = 25 + 0;
  • 25 ÷ 2 = 12 + 1;
  • 12 ÷ 2 = 6 + 0;
  • 6 ÷ 2 = 3 + 0;
  • 3 ÷ 2 = 1 + 1;
  • 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.


50(10) =


11 0010(2)


3. Convert to binary (base 2) the fractional part: 0.141 359.

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) 0.141 359 × 2 = 0 + 0.282 718;
  • 2) 0.282 718 × 2 = 0 + 0.565 436;
  • 3) 0.565 436 × 2 = 1 + 0.130 872;
  • 4) 0.130 872 × 2 = 0 + 0.261 744;
  • 5) 0.261 744 × 2 = 0 + 0.523 488;
  • 6) 0.523 488 × 2 = 1 + 0.046 976;
  • 7) 0.046 976 × 2 = 0 + 0.093 952;
  • 8) 0.093 952 × 2 = 0 + 0.187 904;
  • 9) 0.187 904 × 2 = 0 + 0.375 808;
  • 10) 0.375 808 × 2 = 0 + 0.751 616;
  • 11) 0.751 616 × 2 = 1 + 0.503 232;
  • 12) 0.503 232 × 2 = 1 + 0.006 464;
  • 13) 0.006 464 × 2 = 0 + 0.012 928;
  • 14) 0.012 928 × 2 = 0 + 0.025 856;
  • 15) 0.025 856 × 2 = 0 + 0.051 712;
  • 16) 0.051 712 × 2 = 0 + 0.103 424;
  • 17) 0.103 424 × 2 = 0 + 0.206 848;
  • 18) 0.206 848 × 2 = 0 + 0.413 696;
  • 19) 0.413 696 × 2 = 0 + 0.827 392;
  • 20) 0.827 392 × 2 = 1 + 0.654 784;
  • 21) 0.654 784 × 2 = 1 + 0.309 568;
  • 22) 0.309 568 × 2 = 0 + 0.619 136;
  • 23) 0.619 136 × 2 = 1 + 0.238 272;
  • 24) 0.238 272 × 2 = 0 + 0.476 544;
  • 25) 0.476 544 × 2 = 0 + 0.953 088;
  • 26) 0.953 088 × 2 = 1 + 0.906 176;
  • 27) 0.906 176 × 2 = 1 + 0.812 352;
  • 28) 0.812 352 × 2 = 1 + 0.624 704;
  • 29) 0.624 704 × 2 = 1 + 0.249 408;
  • 30) 0.249 408 × 2 = 0 + 0.498 816;
  • 31) 0.498 816 × 2 = 0 + 0.997 632;
  • 32) 0.997 632 × 2 = 1 + 0.995 264;
  • 33) 0.995 264 × 2 = 1 + 0.990 528;
  • 34) 0.990 528 × 2 = 1 + 0.981 056;
  • 35) 0.981 056 × 2 = 1 + 0.962 112;
  • 36) 0.962 112 × 2 = 1 + 0.924 224;
  • 37) 0.924 224 × 2 = 1 + 0.848 448;
  • 38) 0.848 448 × 2 = 1 + 0.696 896;
  • 39) 0.696 896 × 2 = 1 + 0.393 792;
  • 40) 0.393 792 × 2 = 0 + 0.787 584;
  • 41) 0.787 584 × 2 = 1 + 0.575 168;
  • 42) 0.575 168 × 2 = 1 + 0.150 336;
  • 43) 0.150 336 × 2 = 0 + 0.300 672;
  • 44) 0.300 672 × 2 = 0 + 0.601 344;
  • 45) 0.601 344 × 2 = 1 + 0.202 688;
  • 46) 0.202 688 × 2 = 0 + 0.405 376;
  • 47) 0.405 376 × 2 = 0 + 0.810 752;
  • 48) 0.810 752 × 2 = 1 + 0.621 504;
  • 49) 0.621 504 × 2 = 1 + 0.243 008;
  • 50) 0.243 008 × 2 = 0 + 0.486 016;
  • 51) 0.486 016 × 2 = 0 + 0.972 032;
  • 52) 0.972 032 × 2 = 1 + 0.944 064;
  • 53) 0.944 064 × 2 = 1 + 0.888 128;

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...)


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:


0.141 359(10) =


0.0010 0100 0011 0000 0001 1010 0111 1001 1111 1110 1100 1001 1001 1(2)


5. Positive number before normalization:

50.141 359(10) =


11 0010.0010 0100 0011 0000 0001 1010 0111 1001 1111 1110 1100 1001 1001 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:


50.141 359(10) =


11 0010.0010 0100 0011 0000 0001 1010 0111 1001 1111 1110 1100 1001 1001 1(2) =


11 0010.0010 0100 0011 0000 0001 1010 0111 1001 1111 1110 1100 1001 1001 1(2) × 20 =


1.1001 0001 0010 0001 1000 0000 1101 0011 1100 1111 1111 0110 0100 1100 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):
1.1001 0001 0010 0001 1000 0000 1101 0011 1100 1111 1111 0110 0100 1100 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. 1001 0001 0010 0001 1000 0000 1101 0011 1100 1111 1111 0110 0100 11 0011 =


1001 0001 0010 0001 1000 0000 1101 0011 1100 1111 1111 0110 0100


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) =
1001 0001 0010 0001 1000 0000 1101 0011 1100 1111 1111 0110 0100


The base ten decimal number 50.141 359 converted and written in 64 bit double precision IEEE 754 binary floating point representation:
0 - 100 0000 0100 - 1001 0001 0010 0001 1000 0000 1101 0011 1100 1111 1111 0110 0100

The latest decimal numbers converted from base ten to 64 bit double precision IEEE 754 floating point binary standard representation

Number 95.62 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard Apr 27 15:17 UTC (GMT)
Number 8 978 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard Apr 27 15:17 UTC (GMT)
Number 0.083 333 333 333 33 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard Apr 27 15:17 UTC (GMT)
Number 0.428 571 428 5 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard Apr 27 15:17 UTC (GMT)
Number 639 951 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard Apr 27 15:17 UTC (GMT)
Number -45.562 4 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard Apr 27 15:16 UTC (GMT)
Number 25 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard Apr 27 15:16 UTC (GMT)
Number 9 223 372 036 854 774 735 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard Apr 27 15:16 UTC (GMT)
Number -19.981 999 999 5 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard Apr 27 15:16 UTC (GMT)
Number 1 947 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard Apr 27 15:16 UTC (GMT)
All base ten decimal numbers converted to 64 bit double precision IEEE 754 binary floating point

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