12 894.389 999 999 999 339 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 12 894.389 999 999 999 339(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
12 894.389 999 999 999 339(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: 12 894.
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;
  • 12 894 ÷ 2 = 6 447 + 0;
  • 6 447 ÷ 2 = 3 223 + 1;
  • 3 223 ÷ 2 = 1 611 + 1;
  • 1 611 ÷ 2 = 805 + 1;
  • 805 ÷ 2 = 402 + 1;
  • 402 ÷ 2 = 201 + 0;
  • 201 ÷ 2 = 100 + 1;
  • 100 ÷ 2 = 50 + 0;
  • 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.

12 894(10) =


11 0010 0101 1110(2)


3. Convert to binary (base 2) the fractional part: 0.389 999 999 999 339.

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) 0.389 999 999 999 339 × 2 = 0 + 0.779 999 999 998 678;
  • 2) 0.779 999 999 998 678 × 2 = 1 + 0.559 999 999 997 356;
  • 3) 0.559 999 999 997 356 × 2 = 1 + 0.119 999 999 994 712;
  • 4) 0.119 999 999 994 712 × 2 = 0 + 0.239 999 999 989 424;
  • 5) 0.239 999 999 989 424 × 2 = 0 + 0.479 999 999 978 848;
  • 6) 0.479 999 999 978 848 × 2 = 0 + 0.959 999 999 957 696;
  • 7) 0.959 999 999 957 696 × 2 = 1 + 0.919 999 999 915 392;
  • 8) 0.919 999 999 915 392 × 2 = 1 + 0.839 999 999 830 784;
  • 9) 0.839 999 999 830 784 × 2 = 1 + 0.679 999 999 661 568;
  • 10) 0.679 999 999 661 568 × 2 = 1 + 0.359 999 999 323 136;
  • 11) 0.359 999 999 323 136 × 2 = 0 + 0.719 999 998 646 272;
  • 12) 0.719 999 998 646 272 × 2 = 1 + 0.439 999 997 292 544;
  • 13) 0.439 999 997 292 544 × 2 = 0 + 0.879 999 994 585 088;
  • 14) 0.879 999 994 585 088 × 2 = 1 + 0.759 999 989 170 176;
  • 15) 0.759 999 989 170 176 × 2 = 1 + 0.519 999 978 340 352;
  • 16) 0.519 999 978 340 352 × 2 = 1 + 0.039 999 956 680 704;
  • 17) 0.039 999 956 680 704 × 2 = 0 + 0.079 999 913 361 408;
  • 18) 0.079 999 913 361 408 × 2 = 0 + 0.159 999 826 722 816;
  • 19) 0.159 999 826 722 816 × 2 = 0 + 0.319 999 653 445 632;
  • 20) 0.319 999 653 445 632 × 2 = 0 + 0.639 999 306 891 264;
  • 21) 0.639 999 306 891 264 × 2 = 1 + 0.279 998 613 782 528;
  • 22) 0.279 998 613 782 528 × 2 = 0 + 0.559 997 227 565 056;
  • 23) 0.559 997 227 565 056 × 2 = 1 + 0.119 994 455 130 112;
  • 24) 0.119 994 455 130 112 × 2 = 0 + 0.239 988 910 260 224;
  • 25) 0.239 988 910 260 224 × 2 = 0 + 0.479 977 820 520 448;
  • 26) 0.479 977 820 520 448 × 2 = 0 + 0.959 955 641 040 896;
  • 27) 0.959 955 641 040 896 × 2 = 1 + 0.919 911 282 081 792;
  • 28) 0.919 911 282 081 792 × 2 = 1 + 0.839 822 564 163 584;
  • 29) 0.839 822 564 163 584 × 2 = 1 + 0.679 645 128 327 168;
  • 30) 0.679 645 128 327 168 × 2 = 1 + 0.359 290 256 654 336;
  • 31) 0.359 290 256 654 336 × 2 = 0 + 0.718 580 513 308 672;
  • 32) 0.718 580 513 308 672 × 2 = 1 + 0.437 161 026 617 344;
  • 33) 0.437 161 026 617 344 × 2 = 0 + 0.874 322 053 234 688;
  • 34) 0.874 322 053 234 688 × 2 = 1 + 0.748 644 106 469 376;
  • 35) 0.748 644 106 469 376 × 2 = 1 + 0.497 288 212 938 752;
  • 36) 0.497 288 212 938 752 × 2 = 0 + 0.994 576 425 877 504;
  • 37) 0.994 576 425 877 504 × 2 = 1 + 0.989 152 851 755 008;
  • 38) 0.989 152 851 755 008 × 2 = 1 + 0.978 305 703 510 016;
  • 39) 0.978 305 703 510 016 × 2 = 1 + 0.956 611 407 020 032;
  • 40) 0.956 611 407 020 032 × 2 = 1 + 0.913 222 814 040 064;
  • 41) 0.913 222 814 040 064 × 2 = 1 + 0.826 445 628 080 128;
  • 42) 0.826 445 628 080 128 × 2 = 1 + 0.652 891 256 160 256;
  • 43) 0.652 891 256 160 256 × 2 = 1 + 0.305 782 512 320 512;
  • 44) 0.305 782 512 320 512 × 2 = 0 + 0.611 565 024 641 024;
  • 45) 0.611 565 024 641 024 × 2 = 1 + 0.223 130 049 282 048;
  • 46) 0.223 130 049 282 048 × 2 = 0 + 0.446 260 098 564 096;
  • 47) 0.446 260 098 564 096 × 2 = 0 + 0.892 520 197 128 192;
  • 48) 0.892 520 197 128 192 × 2 = 1 + 0.785 040 394 256 384;
  • 49) 0.785 040 394 256 384 × 2 = 1 + 0.570 080 788 512 768;
  • 50) 0.570 080 788 512 768 × 2 = 1 + 0.140 161 577 025 536;
  • 51) 0.140 161 577 025 536 × 2 = 0 + 0.280 323 154 051 072;
  • 52) 0.280 323 154 051 072 × 2 = 0 + 0.560 646 308 102 144;
  • 53) 0.560 646 308 102 144 × 2 = 1 + 0.121 292 616 204 288;

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:


0.389 999 999 999 339(10) =


0.0110 0011 1101 0111 0000 1010 0011 1101 0110 1111 1110 1001 1100 1(2)

5. Positive number before normalization:

12 894.389 999 999 999 339(10) =


11 0010 0101 1110.0110 0011 1101 0111 0000 1010 0011 1101 0110 1111 1110 1001 1100 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 13 positions to the left, so that only one non zero digit remains to the left of it:


12 894.389 999 999 999 339(10) =


11 0010 0101 1110.0110 0011 1101 0111 0000 1010 0011 1101 0110 1111 1110 1001 1100 1(2) =


11 0010 0101 1110.0110 0011 1101 0111 0000 1010 0011 1101 0110 1111 1110 1001 1100 1(2) × 20 =


1.1001 0010 1111 0011 0001 1110 1011 1000 0101 0001 1110 1011 0111 1111 0100 1110 01(2) × 213


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): 13


Mantissa (not normalized):
1.1001 0010 1111 0011 0001 1110 1011 1000 0101 0001 1110 1011 0111 1111 0100 1110 01


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


13 + 2(11-1) - 1 =


(13 + 1 023)(10) =


1 036(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;
  • 1 036 ÷ 2 = 518 + 0;
  • 518 ÷ 2 = 259 + 0;
  • 259 ÷ 2 = 129 + 1;
  • 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) =


1036(10) =


100 0000 1100(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 0010 1111 0011 0001 1110 1011 1000 0101 0001 1110 1011 0111 11 1101 0011 1001 =


1001 0010 1111 0011 0001 1110 1011 1000 0101 0001 1110 1011 0111


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 1100


Mantissa (52 bits) =
1001 0010 1111 0011 0001 1110 1011 1000 0101 0001 1110 1011 0111


Decimal number 12 894.389 999 999 999 339 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 1100 - 1001 0010 1111 0011 0001 1110 1011 1000 0101 0001 1110 1011 0111


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