64bit IEEE 754: Decimal ↗ Double Precision Floating Point Binary: 13 849 272 541 606 051 903 Convert the Number to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From a Base Ten Decimal System Number

Number 13 849 272 541 606 051 903(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. 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;
  • 13 849 272 541 606 051 903 ÷ 2 = 6 924 636 270 803 025 951 + 1;
  • 6 924 636 270 803 025 951 ÷ 2 = 3 462 318 135 401 512 975 + 1;
  • 3 462 318 135 401 512 975 ÷ 2 = 1 731 159 067 700 756 487 + 1;
  • 1 731 159 067 700 756 487 ÷ 2 = 865 579 533 850 378 243 + 1;
  • 865 579 533 850 378 243 ÷ 2 = 432 789 766 925 189 121 + 1;
  • 432 789 766 925 189 121 ÷ 2 = 216 394 883 462 594 560 + 1;
  • 216 394 883 462 594 560 ÷ 2 = 108 197 441 731 297 280 + 0;
  • 108 197 441 731 297 280 ÷ 2 = 54 098 720 865 648 640 + 0;
  • 54 098 720 865 648 640 ÷ 2 = 27 049 360 432 824 320 + 0;
  • 27 049 360 432 824 320 ÷ 2 = 13 524 680 216 412 160 + 0;
  • 13 524 680 216 412 160 ÷ 2 = 6 762 340 108 206 080 + 0;
  • 6 762 340 108 206 080 ÷ 2 = 3 381 170 054 103 040 + 0;
  • 3 381 170 054 103 040 ÷ 2 = 1 690 585 027 051 520 + 0;
  • 1 690 585 027 051 520 ÷ 2 = 845 292 513 525 760 + 0;
  • 845 292 513 525 760 ÷ 2 = 422 646 256 762 880 + 0;
  • 422 646 256 762 880 ÷ 2 = 211 323 128 381 440 + 0;
  • 211 323 128 381 440 ÷ 2 = 105 661 564 190 720 + 0;
  • 105 661 564 190 720 ÷ 2 = 52 830 782 095 360 + 0;
  • 52 830 782 095 360 ÷ 2 = 26 415 391 047 680 + 0;
  • 26 415 391 047 680 ÷ 2 = 13 207 695 523 840 + 0;
  • 13 207 695 523 840 ÷ 2 = 6 603 847 761 920 + 0;
  • 6 603 847 761 920 ÷ 2 = 3 301 923 880 960 + 0;
  • 3 301 923 880 960 ÷ 2 = 1 650 961 940 480 + 0;
  • 1 650 961 940 480 ÷ 2 = 825 480 970 240 + 0;
  • 825 480 970 240 ÷ 2 = 412 740 485 120 + 0;
  • 412 740 485 120 ÷ 2 = 206 370 242 560 + 0;
  • 206 370 242 560 ÷ 2 = 103 185 121 280 + 0;
  • 103 185 121 280 ÷ 2 = 51 592 560 640 + 0;
  • 51 592 560 640 ÷ 2 = 25 796 280 320 + 0;
  • 25 796 280 320 ÷ 2 = 12 898 140 160 + 0;
  • 12 898 140 160 ÷ 2 = 6 449 070 080 + 0;
  • 6 449 070 080 ÷ 2 = 3 224 535 040 + 0;
  • 3 224 535 040 ÷ 2 = 1 612 267 520 + 0;
  • 1 612 267 520 ÷ 2 = 806 133 760 + 0;
  • 806 133 760 ÷ 2 = 403 066 880 + 0;
  • 403 066 880 ÷ 2 = 201 533 440 + 0;
  • 201 533 440 ÷ 2 = 100 766 720 + 0;
  • 100 766 720 ÷ 2 = 50 383 360 + 0;
  • 50 383 360 ÷ 2 = 25 191 680 + 0;
  • 25 191 680 ÷ 2 = 12 595 840 + 0;
  • 12 595 840 ÷ 2 = 6 297 920 + 0;
  • 6 297 920 ÷ 2 = 3 148 960 + 0;
  • 3 148 960 ÷ 2 = 1 574 480 + 0;
  • 1 574 480 ÷ 2 = 787 240 + 0;
  • 787 240 ÷ 2 = 393 620 + 0;
  • 393 620 ÷ 2 = 196 810 + 0;
  • 196 810 ÷ 2 = 98 405 + 0;
  • 98 405 ÷ 2 = 49 202 + 1;
  • 49 202 ÷ 2 = 24 601 + 0;
  • 24 601 ÷ 2 = 12 300 + 1;
  • 12 300 ÷ 2 = 6 150 + 0;
  • 6 150 ÷ 2 = 3 075 + 0;
  • 3 075 ÷ 2 = 1 537 + 1;
  • 1 537 ÷ 2 = 768 + 1;
  • 768 ÷ 2 = 384 + 0;
  • 384 ÷ 2 = 192 + 0;
  • 192 ÷ 2 = 96 + 0;
  • 96 ÷ 2 = 48 + 0;
  • 48 ÷ 2 = 24 + 0;
  • 24 ÷ 2 = 12 + 0;
  • 12 ÷ 2 = 6 + 0;
  • 6 ÷ 2 = 3 + 0;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

2. Construct the base 2 representation of the positive number.

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


13 849 272 541 606 051 903(10) =


1100 0000 0011 0010 1000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0011 1111(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 63 positions to the left, so that only one non zero digit remains to the left of it:


13 849 272 541 606 051 903(10) =


1100 0000 0011 0010 1000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0011 1111(2) =


1100 0000 0011 0010 1000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0011 1111(2) × 20 =


1.1000 0000 0110 0101 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0111 111(2) × 263


4. 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): 63


Mantissa (not normalized):
1.1000 0000 0110 0101 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0111 111


5. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


63 + 2(11-1) - 1 =


(63 + 1 023)(10) =


1 086(10)


6. 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;
  • 1 086 ÷ 2 = 543 + 0;
  • 543 ÷ 2 = 271 + 1;
  • 271 ÷ 2 = 135 + 1;
  • 135 ÷ 2 = 67 + 1;
  • 67 ÷ 2 = 33 + 1;
  • 33 ÷ 2 = 16 + 1;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

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

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


Exponent (adjusted) =


1086(10) =


100 0011 1110(2)


8. 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. 1000 0000 0110 0101 0000 0000 0000 0000 0000 0000 0000 0000 0000 000 0011 1111 =


1000 0000 0110 0101 0000 0000 0000 0000 0000 0000 0000 0000 0000


9. 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 0011 1110


Mantissa (52 bits) =
1000 0000 0110 0101 0000 0000 0000 0000 0000 0000 0000 0000 0000


The base ten decimal number 13 849 272 541 606 051 903 converted and written in 64 bit double precision IEEE 754 binary floating point representation:
0 - 100 0011 1110 - 1000 0000 0110 0101 0000 0000 0000 0000 0000 0000 0000 0000 0000

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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