64bit IEEE 754: Decimal ↗ Double Precision Floating Point Binary: -2 001.230 014 923 101 16 Convert the Number to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From a Base Ten Decimal System Number

Number -2 001.230 014 923 101 16(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. Start with the positive version of the number:

|-2 001.230 014 923 101 16| = 2 001.230 014 923 101 16

2. First, convert to binary (in base 2) the integer part: 2 001.
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;
  • 2 001 ÷ 2 = 1 000 + 1;
  • 1 000 ÷ 2 = 500 + 0;
  • 500 ÷ 2 = 250 + 0;
  • 250 ÷ 2 = 125 + 0;
  • 125 ÷ 2 = 62 + 1;
  • 62 ÷ 2 = 31 + 0;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

3. 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.


2 001(10) =


111 1101 0001(2)


4. Convert to binary (base 2) the fractional part: 0.230 014 923 101 16.

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) 0.230 014 923 101 16 × 2 = 0 + 0.460 029 846 202 32;
  • 2) 0.460 029 846 202 32 × 2 = 0 + 0.920 059 692 404 64;
  • 3) 0.920 059 692 404 64 × 2 = 1 + 0.840 119 384 809 28;
  • 4) 0.840 119 384 809 28 × 2 = 1 + 0.680 238 769 618 56;
  • 5) 0.680 238 769 618 56 × 2 = 1 + 0.360 477 539 237 12;
  • 6) 0.360 477 539 237 12 × 2 = 0 + 0.720 955 078 474 24;
  • 7) 0.720 955 078 474 24 × 2 = 1 + 0.441 910 156 948 48;
  • 8) 0.441 910 156 948 48 × 2 = 0 + 0.883 820 313 896 96;
  • 9) 0.883 820 313 896 96 × 2 = 1 + 0.767 640 627 793 92;
  • 10) 0.767 640 627 793 92 × 2 = 1 + 0.535 281 255 587 84;
  • 11) 0.535 281 255 587 84 × 2 = 1 + 0.070 562 511 175 68;
  • 12) 0.070 562 511 175 68 × 2 = 0 + 0.141 125 022 351 36;
  • 13) 0.141 125 022 351 36 × 2 = 0 + 0.282 250 044 702 72;
  • 14) 0.282 250 044 702 72 × 2 = 0 + 0.564 500 089 405 44;
  • 15) 0.564 500 089 405 44 × 2 = 1 + 0.129 000 178 810 88;
  • 16) 0.129 000 178 810 88 × 2 = 0 + 0.258 000 357 621 76;
  • 17) 0.258 000 357 621 76 × 2 = 0 + 0.516 000 715 243 52;
  • 18) 0.516 000 715 243 52 × 2 = 1 + 0.032 001 430 487 04;
  • 19) 0.032 001 430 487 04 × 2 = 0 + 0.064 002 860 974 08;
  • 20) 0.064 002 860 974 08 × 2 = 0 + 0.128 005 721 948 16;
  • 21) 0.128 005 721 948 16 × 2 = 0 + 0.256 011 443 896 32;
  • 22) 0.256 011 443 896 32 × 2 = 0 + 0.512 022 887 792 64;
  • 23) 0.512 022 887 792 64 × 2 = 1 + 0.024 045 775 585 28;
  • 24) 0.024 045 775 585 28 × 2 = 0 + 0.048 091 551 170 56;
  • 25) 0.048 091 551 170 56 × 2 = 0 + 0.096 183 102 341 12;
  • 26) 0.096 183 102 341 12 × 2 = 0 + 0.192 366 204 682 24;
  • 27) 0.192 366 204 682 24 × 2 = 0 + 0.384 732 409 364 48;
  • 28) 0.384 732 409 364 48 × 2 = 0 + 0.769 464 818 728 96;
  • 29) 0.769 464 818 728 96 × 2 = 1 + 0.538 929 637 457 92;
  • 30) 0.538 929 637 457 92 × 2 = 1 + 0.077 859 274 915 84;
  • 31) 0.077 859 274 915 84 × 2 = 0 + 0.155 718 549 831 68;
  • 32) 0.155 718 549 831 68 × 2 = 0 + 0.311 437 099 663 36;
  • 33) 0.311 437 099 663 36 × 2 = 0 + 0.622 874 199 326 72;
  • 34) 0.622 874 199 326 72 × 2 = 1 + 0.245 748 398 653 44;
  • 35) 0.245 748 398 653 44 × 2 = 0 + 0.491 496 797 306 88;
  • 36) 0.491 496 797 306 88 × 2 = 0 + 0.982 993 594 613 76;
  • 37) 0.982 993 594 613 76 × 2 = 1 + 0.965 987 189 227 52;
  • 38) 0.965 987 189 227 52 × 2 = 1 + 0.931 974 378 455 04;
  • 39) 0.931 974 378 455 04 × 2 = 1 + 0.863 948 756 910 08;
  • 40) 0.863 948 756 910 08 × 2 = 1 + 0.727 897 513 820 16;
  • 41) 0.727 897 513 820 16 × 2 = 1 + 0.455 795 027 640 32;
  • 42) 0.455 795 027 640 32 × 2 = 0 + 0.911 590 055 280 64;
  • 43) 0.911 590 055 280 64 × 2 = 1 + 0.823 180 110 561 28;
  • 44) 0.823 180 110 561 28 × 2 = 1 + 0.646 360 221 122 56;
  • 45) 0.646 360 221 122 56 × 2 = 1 + 0.292 720 442 245 12;
  • 46) 0.292 720 442 245 12 × 2 = 0 + 0.585 440 884 490 24;
  • 47) 0.585 440 884 490 24 × 2 = 1 + 0.170 881 768 980 48;
  • 48) 0.170 881 768 980 48 × 2 = 0 + 0.341 763 537 960 96;
  • 49) 0.341 763 537 960 96 × 2 = 0 + 0.683 527 075 921 92;
  • 50) 0.683 527 075 921 92 × 2 = 1 + 0.367 054 151 843 84;
  • 51) 0.367 054 151 843 84 × 2 = 0 + 0.734 108 303 687 68;
  • 52) 0.734 108 303 687 68 × 2 = 1 + 0.468 216 607 375 36;
  • 53) 0.468 216 607 375 36 × 2 = 0 + 0.936 433 214 750 72;

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...)


5. 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:


0.230 014 923 101 16(10) =


0.0011 1010 1110 0010 0100 0010 0000 1100 0100 1111 1011 1010 0101 0(2)


6. Positive number before normalization:

2 001.230 014 923 101 16(10) =


111 1101 0001.0011 1010 1110 0010 0100 0010 0000 1100 0100 1111 1011 1010 0101 0(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 10 positions to the left, so that only one non zero digit remains to the left of it:


2 001.230 014 923 101 16(10) =


111 1101 0001.0011 1010 1110 0010 0100 0010 0000 1100 0100 1111 1011 1010 0101 0(2) =


111 1101 0001.0011 1010 1110 0010 0100 0010 0000 1100 0100 1111 1011 1010 0101 0(2) × 20 =


1.1111 0100 0100 1110 1011 1000 1001 0000 1000 0011 0001 0011 1110 1110 1001 010(2) × 210


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): 10


Mantissa (not normalized):
1.1111 0100 0100 1110 1011 1000 1001 0000 1000 0011 0001 0011 1110 1110 1001 010


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


10 + 2(11-1) - 1 =


(10 + 1 023)(10) =


1 033(10)


10. 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;
  • 1 033 ÷ 2 = 516 + 1;
  • 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;

11. Construct the base 2 representation of the adjusted exponent.

Take all the remainders starting from the bottom of the list constructed above.


Exponent (adjusted) =


1033(10) =


100 0000 1001(2)


12. 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. 1111 0100 0100 1110 1011 1000 1001 0000 1000 0011 0001 0011 1110 111 0100 1010 =


1111 0100 0100 1110 1011 1000 1001 0000 1000 0011 0001 0011 1110


13. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

Sign (1 bit) =
1 (a negative number)


Exponent (11 bits) =
100 0000 1001


Mantissa (52 bits) =
1111 0100 0100 1110 1011 1000 1001 0000 1000 0011 0001 0011 1110


The base ten decimal number -2 001.230 014 923 101 16 converted and written in 64 bit double precision IEEE 754 binary floating point representation:
1 - 100 0000 1001 - 1111 0100 0100 1110 1011 1000 1001 0000 1000 0011 0001 0011 1110

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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