10.000 000 000 000 001 93 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 10.000 000 000 000 001 93(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
10.000 000 000 000 001 93(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: 10.
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;
  • 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.

10(10) =


1010(2)


3. Convert to binary (base 2) the fractional part: 0.000 000 000 000 001 93.

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) 0.000 000 000 000 001 93 × 2 = 0 + 0.000 000 000 000 003 86;
  • 2) 0.000 000 000 000 003 86 × 2 = 0 + 0.000 000 000 000 007 72;
  • 3) 0.000 000 000 000 007 72 × 2 = 0 + 0.000 000 000 000 015 44;
  • 4) 0.000 000 000 000 015 44 × 2 = 0 + 0.000 000 000 000 030 88;
  • 5) 0.000 000 000 000 030 88 × 2 = 0 + 0.000 000 000 000 061 76;
  • 6) 0.000 000 000 000 061 76 × 2 = 0 + 0.000 000 000 000 123 52;
  • 7) 0.000 000 000 000 123 52 × 2 = 0 + 0.000 000 000 000 247 04;
  • 8) 0.000 000 000 000 247 04 × 2 = 0 + 0.000 000 000 000 494 08;
  • 9) 0.000 000 000 000 494 08 × 2 = 0 + 0.000 000 000 000 988 16;
  • 10) 0.000 000 000 000 988 16 × 2 = 0 + 0.000 000 000 001 976 32;
  • 11) 0.000 000 000 001 976 32 × 2 = 0 + 0.000 000 000 003 952 64;
  • 12) 0.000 000 000 003 952 64 × 2 = 0 + 0.000 000 000 007 905 28;
  • 13) 0.000 000 000 007 905 28 × 2 = 0 + 0.000 000 000 015 810 56;
  • 14) 0.000 000 000 015 810 56 × 2 = 0 + 0.000 000 000 031 621 12;
  • 15) 0.000 000 000 031 621 12 × 2 = 0 + 0.000 000 000 063 242 24;
  • 16) 0.000 000 000 063 242 24 × 2 = 0 + 0.000 000 000 126 484 48;
  • 17) 0.000 000 000 126 484 48 × 2 = 0 + 0.000 000 000 252 968 96;
  • 18) 0.000 000 000 252 968 96 × 2 = 0 + 0.000 000 000 505 937 92;
  • 19) 0.000 000 000 505 937 92 × 2 = 0 + 0.000 000 001 011 875 84;
  • 20) 0.000 000 001 011 875 84 × 2 = 0 + 0.000 000 002 023 751 68;
  • 21) 0.000 000 002 023 751 68 × 2 = 0 + 0.000 000 004 047 503 36;
  • 22) 0.000 000 004 047 503 36 × 2 = 0 + 0.000 000 008 095 006 72;
  • 23) 0.000 000 008 095 006 72 × 2 = 0 + 0.000 000 016 190 013 44;
  • 24) 0.000 000 016 190 013 44 × 2 = 0 + 0.000 000 032 380 026 88;
  • 25) 0.000 000 032 380 026 88 × 2 = 0 + 0.000 000 064 760 053 76;
  • 26) 0.000 000 064 760 053 76 × 2 = 0 + 0.000 000 129 520 107 52;
  • 27) 0.000 000 129 520 107 52 × 2 = 0 + 0.000 000 259 040 215 04;
  • 28) 0.000 000 259 040 215 04 × 2 = 0 + 0.000 000 518 080 430 08;
  • 29) 0.000 000 518 080 430 08 × 2 = 0 + 0.000 001 036 160 860 16;
  • 30) 0.000 001 036 160 860 16 × 2 = 0 + 0.000 002 072 321 720 32;
  • 31) 0.000 002 072 321 720 32 × 2 = 0 + 0.000 004 144 643 440 64;
  • 32) 0.000 004 144 643 440 64 × 2 = 0 + 0.000 008 289 286 881 28;
  • 33) 0.000 008 289 286 881 28 × 2 = 0 + 0.000 016 578 573 762 56;
  • 34) 0.000 016 578 573 762 56 × 2 = 0 + 0.000 033 157 147 525 12;
  • 35) 0.000 033 157 147 525 12 × 2 = 0 + 0.000 066 314 295 050 24;
  • 36) 0.000 066 314 295 050 24 × 2 = 0 + 0.000 132 628 590 100 48;
  • 37) 0.000 132 628 590 100 48 × 2 = 0 + 0.000 265 257 180 200 96;
  • 38) 0.000 265 257 180 200 96 × 2 = 0 + 0.000 530 514 360 401 92;
  • 39) 0.000 530 514 360 401 92 × 2 = 0 + 0.001 061 028 720 803 84;
  • 40) 0.001 061 028 720 803 84 × 2 = 0 + 0.002 122 057 441 607 68;
  • 41) 0.002 122 057 441 607 68 × 2 = 0 + 0.004 244 114 883 215 36;
  • 42) 0.004 244 114 883 215 36 × 2 = 0 + 0.008 488 229 766 430 72;
  • 43) 0.008 488 229 766 430 72 × 2 = 0 + 0.016 976 459 532 861 44;
  • 44) 0.016 976 459 532 861 44 × 2 = 0 + 0.033 952 919 065 722 88;
  • 45) 0.033 952 919 065 722 88 × 2 = 0 + 0.067 905 838 131 445 76;
  • 46) 0.067 905 838 131 445 76 × 2 = 0 + 0.135 811 676 262 891 52;
  • 47) 0.135 811 676 262 891 52 × 2 = 0 + 0.271 623 352 525 783 04;
  • 48) 0.271 623 352 525 783 04 × 2 = 0 + 0.543 246 705 051 566 08;
  • 49) 0.543 246 705 051 566 08 × 2 = 1 + 0.086 493 410 103 132 16;
  • 50) 0.086 493 410 103 132 16 × 2 = 0 + 0.172 986 820 206 264 32;
  • 51) 0.172 986 820 206 264 32 × 2 = 0 + 0.345 973 640 412 528 64;
  • 52) 0.345 973 640 412 528 64 × 2 = 0 + 0.691 947 280 825 057 28;
  • 53) 0.691 947 280 825 057 28 × 2 = 1 + 0.383 894 561 650 114 56;

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:


0.000 000 000 000 001 93(10) =


0.0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 1000 1(2)

5. Positive number before normalization:

10.000 000 000 000 001 93(10) =


1010.0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 1000 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 3 positions to the left, so that only one non zero digit remains to the left of it:


10.000 000 000 000 001 93(10) =


1010.0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 1000 1(2) =


1010.0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 1000 1(2) × 20 =


1.0100 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0001 0001(2) × 23


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): 3


Mantissa (not normalized):
1.0100 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0001 0001


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


3 + 2(11-1) - 1 =


(3 + 1 023)(10) =


1 026(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;
  • 1 026 ÷ 2 = 513 + 0;
  • 513 ÷ 2 = 256 + 1;
  • 256 ÷ 2 = 128 + 0;
  • 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) =


1026(10) =


100 0000 0010(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 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0001 0001 =


0100 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0001


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 0010


Mantissa (52 bits) =
0100 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0001


Decimal number 10.000 000 000 000 001 93 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0010 - 0100 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0001

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