4 693 217 858 908 898 103 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 4 693 217 858 908 898 103(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
4 693 217 858 908 898 103(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. 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;
  • 4 693 217 858 908 898 103 ÷ 2 = 2 346 608 929 454 449 051 + 1;
  • 2 346 608 929 454 449 051 ÷ 2 = 1 173 304 464 727 224 525 + 1;
  • 1 173 304 464 727 224 525 ÷ 2 = 586 652 232 363 612 262 + 1;
  • 586 652 232 363 612 262 ÷ 2 = 293 326 116 181 806 131 + 0;
  • 293 326 116 181 806 131 ÷ 2 = 146 663 058 090 903 065 + 1;
  • 146 663 058 090 903 065 ÷ 2 = 73 331 529 045 451 532 + 1;
  • 73 331 529 045 451 532 ÷ 2 = 36 665 764 522 725 766 + 0;
  • 36 665 764 522 725 766 ÷ 2 = 18 332 882 261 362 883 + 0;
  • 18 332 882 261 362 883 ÷ 2 = 9 166 441 130 681 441 + 1;
  • 9 166 441 130 681 441 ÷ 2 = 4 583 220 565 340 720 + 1;
  • 4 583 220 565 340 720 ÷ 2 = 2 291 610 282 670 360 + 0;
  • 2 291 610 282 670 360 ÷ 2 = 1 145 805 141 335 180 + 0;
  • 1 145 805 141 335 180 ÷ 2 = 572 902 570 667 590 + 0;
  • 572 902 570 667 590 ÷ 2 = 286 451 285 333 795 + 0;
  • 286 451 285 333 795 ÷ 2 = 143 225 642 666 897 + 1;
  • 143 225 642 666 897 ÷ 2 = 71 612 821 333 448 + 1;
  • 71 612 821 333 448 ÷ 2 = 35 806 410 666 724 + 0;
  • 35 806 410 666 724 ÷ 2 = 17 903 205 333 362 + 0;
  • 17 903 205 333 362 ÷ 2 = 8 951 602 666 681 + 0;
  • 8 951 602 666 681 ÷ 2 = 4 475 801 333 340 + 1;
  • 4 475 801 333 340 ÷ 2 = 2 237 900 666 670 + 0;
  • 2 237 900 666 670 ÷ 2 = 1 118 950 333 335 + 0;
  • 1 118 950 333 335 ÷ 2 = 559 475 166 667 + 1;
  • 559 475 166 667 ÷ 2 = 279 737 583 333 + 1;
  • 279 737 583 333 ÷ 2 = 139 868 791 666 + 1;
  • 139 868 791 666 ÷ 2 = 69 934 395 833 + 0;
  • 69 934 395 833 ÷ 2 = 34 967 197 916 + 1;
  • 34 967 197 916 ÷ 2 = 17 483 598 958 + 0;
  • 17 483 598 958 ÷ 2 = 8 741 799 479 + 0;
  • 8 741 799 479 ÷ 2 = 4 370 899 739 + 1;
  • 4 370 899 739 ÷ 2 = 2 185 449 869 + 1;
  • 2 185 449 869 ÷ 2 = 1 092 724 934 + 1;
  • 1 092 724 934 ÷ 2 = 546 362 467 + 0;
  • 546 362 467 ÷ 2 = 273 181 233 + 1;
  • 273 181 233 ÷ 2 = 136 590 616 + 1;
  • 136 590 616 ÷ 2 = 68 295 308 + 0;
  • 68 295 308 ÷ 2 = 34 147 654 + 0;
  • 34 147 654 ÷ 2 = 17 073 827 + 0;
  • 17 073 827 ÷ 2 = 8 536 913 + 1;
  • 8 536 913 ÷ 2 = 4 268 456 + 1;
  • 4 268 456 ÷ 2 = 2 134 228 + 0;
  • 2 134 228 ÷ 2 = 1 067 114 + 0;
  • 1 067 114 ÷ 2 = 533 557 + 0;
  • 533 557 ÷ 2 = 266 778 + 1;
  • 266 778 ÷ 2 = 133 389 + 0;
  • 133 389 ÷ 2 = 66 694 + 1;
  • 66 694 ÷ 2 = 33 347 + 0;
  • 33 347 ÷ 2 = 16 673 + 1;
  • 16 673 ÷ 2 = 8 336 + 1;
  • 8 336 ÷ 2 = 4 168 + 0;
  • 4 168 ÷ 2 = 2 084 + 0;
  • 2 084 ÷ 2 = 1 042 + 0;
  • 1 042 ÷ 2 = 521 + 0;
  • 521 ÷ 2 = 260 + 1;
  • 260 ÷ 2 = 130 + 0;
  • 130 ÷ 2 = 65 + 0;
  • 65 ÷ 2 = 32 + 1;
  • 32 ÷ 2 = 16 + 0;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 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.

4 693 217 858 908 898 103(10) =


100 0001 0010 0001 1010 1000 1100 0110 1110 0101 1100 1000 1100 0011 0011 0111(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 62 positions to the left, so that only one non zero digit remains to the left of it:


4 693 217 858 908 898 103(10) =


100 0001 0010 0001 1010 1000 1100 0110 1110 0101 1100 1000 1100 0011 0011 0111(2) =


100 0001 0010 0001 1010 1000 1100 0110 1110 0101 1100 1000 1100 0011 0011 0111(2) × 20 =


1.0000 0100 1000 0110 1010 0011 0001 1011 1001 0111 0010 0011 0000 1100 1101 11(2) × 262


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): 62


Mantissa (not normalized):
1.0000 0100 1000 0110 1010 0011 0001 1011 1001 0111 0010 0011 0000 1100 1101 11


5. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


62 + 2(11-1) - 1 =


(62 + 1 023)(10) =


1 085(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;
  • 1 085 ÷ 2 = 542 + 1;
  • 542 ÷ 2 = 271 + 0;
  • 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) =


1085(10) =


100 0011 1101(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. 0000 0100 1000 0110 1010 0011 0001 1011 1001 0111 0010 0011 0000 11 0011 0111 =


0000 0100 1000 0110 1010 0011 0001 1011 1001 0111 0010 0011 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 1101


Mantissa (52 bits) =
0000 0100 1000 0110 1010 0011 0001 1011 1001 0111 0010 0011 0000


Decimal number 4 693 217 858 908 898 103 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0011 1101 - 0000 0100 1000 0110 1010 0011 0001 1011 1001 0111 0010 0011 0000


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