2 048.098 120 958 253 3 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2 048.098 120 958 253 3(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
2 048.098 120 958 253 3(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: 2 048.
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;
  • 2 048 ÷ 2 = 1 024 + 0;
  • 1 024 ÷ 2 = 512 + 0;
  • 512 ÷ 2 = 256 + 0;
  • 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;

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.

2 048(10) =


1000 0000 0000(2)


3. Convert to binary (base 2) the fractional part: 0.098 120 958 253 3.

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) 0.098 120 958 253 3 × 2 = 0 + 0.196 241 916 506 6;
  • 2) 0.196 241 916 506 6 × 2 = 0 + 0.392 483 833 013 2;
  • 3) 0.392 483 833 013 2 × 2 = 0 + 0.784 967 666 026 4;
  • 4) 0.784 967 666 026 4 × 2 = 1 + 0.569 935 332 052 8;
  • 5) 0.569 935 332 052 8 × 2 = 1 + 0.139 870 664 105 6;
  • 6) 0.139 870 664 105 6 × 2 = 0 + 0.279 741 328 211 2;
  • 7) 0.279 741 328 211 2 × 2 = 0 + 0.559 482 656 422 4;
  • 8) 0.559 482 656 422 4 × 2 = 1 + 0.118 965 312 844 8;
  • 9) 0.118 965 312 844 8 × 2 = 0 + 0.237 930 625 689 6;
  • 10) 0.237 930 625 689 6 × 2 = 0 + 0.475 861 251 379 2;
  • 11) 0.475 861 251 379 2 × 2 = 0 + 0.951 722 502 758 4;
  • 12) 0.951 722 502 758 4 × 2 = 1 + 0.903 445 005 516 8;
  • 13) 0.903 445 005 516 8 × 2 = 1 + 0.806 890 011 033 6;
  • 14) 0.806 890 011 033 6 × 2 = 1 + 0.613 780 022 067 2;
  • 15) 0.613 780 022 067 2 × 2 = 1 + 0.227 560 044 134 4;
  • 16) 0.227 560 044 134 4 × 2 = 0 + 0.455 120 088 268 8;
  • 17) 0.455 120 088 268 8 × 2 = 0 + 0.910 240 176 537 6;
  • 18) 0.910 240 176 537 6 × 2 = 1 + 0.820 480 353 075 2;
  • 19) 0.820 480 353 075 2 × 2 = 1 + 0.640 960 706 150 4;
  • 20) 0.640 960 706 150 4 × 2 = 1 + 0.281 921 412 300 8;
  • 21) 0.281 921 412 300 8 × 2 = 0 + 0.563 842 824 601 6;
  • 22) 0.563 842 824 601 6 × 2 = 1 + 0.127 685 649 203 2;
  • 23) 0.127 685 649 203 2 × 2 = 0 + 0.255 371 298 406 4;
  • 24) 0.255 371 298 406 4 × 2 = 0 + 0.510 742 596 812 8;
  • 25) 0.510 742 596 812 8 × 2 = 1 + 0.021 485 193 625 6;
  • 26) 0.021 485 193 625 6 × 2 = 0 + 0.042 970 387 251 2;
  • 27) 0.042 970 387 251 2 × 2 = 0 + 0.085 940 774 502 4;
  • 28) 0.085 940 774 502 4 × 2 = 0 + 0.171 881 549 004 8;
  • 29) 0.171 881 549 004 8 × 2 = 0 + 0.343 763 098 009 6;
  • 30) 0.343 763 098 009 6 × 2 = 0 + 0.687 526 196 019 2;
  • 31) 0.687 526 196 019 2 × 2 = 1 + 0.375 052 392 038 4;
  • 32) 0.375 052 392 038 4 × 2 = 0 + 0.750 104 784 076 8;
  • 33) 0.750 104 784 076 8 × 2 = 1 + 0.500 209 568 153 6;
  • 34) 0.500 209 568 153 6 × 2 = 1 + 0.000 419 136 307 2;
  • 35) 0.000 419 136 307 2 × 2 = 0 + 0.000 838 272 614 4;
  • 36) 0.000 838 272 614 4 × 2 = 0 + 0.001 676 545 228 8;
  • 37) 0.001 676 545 228 8 × 2 = 0 + 0.003 353 090 457 6;
  • 38) 0.003 353 090 457 6 × 2 = 0 + 0.006 706 180 915 2;
  • 39) 0.006 706 180 915 2 × 2 = 0 + 0.013 412 361 830 4;
  • 40) 0.013 412 361 830 4 × 2 = 0 + 0.026 824 723 660 8;
  • 41) 0.026 824 723 660 8 × 2 = 0 + 0.053 649 447 321 6;
  • 42) 0.053 649 447 321 6 × 2 = 0 + 0.107 298 894 643 2;
  • 43) 0.107 298 894 643 2 × 2 = 0 + 0.214 597 789 286 4;
  • 44) 0.214 597 789 286 4 × 2 = 0 + 0.429 195 578 572 8;
  • 45) 0.429 195 578 572 8 × 2 = 0 + 0.858 391 157 145 6;
  • 46) 0.858 391 157 145 6 × 2 = 1 + 0.716 782 314 291 2;
  • 47) 0.716 782 314 291 2 × 2 = 1 + 0.433 564 628 582 4;
  • 48) 0.433 564 628 582 4 × 2 = 0 + 0.867 129 257 164 8;
  • 49) 0.867 129 257 164 8 × 2 = 1 + 0.734 258 514 329 6;
  • 50) 0.734 258 514 329 6 × 2 = 1 + 0.468 517 028 659 2;
  • 51) 0.468 517 028 659 2 × 2 = 0 + 0.937 034 057 318 4;
  • 52) 0.937 034 057 318 4 × 2 = 1 + 0.874 068 114 636 8;
  • 53) 0.874 068 114 636 8 × 2 = 1 + 0.748 136 229 273 6;

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:


0.098 120 958 253 3(10) =


0.0001 1001 0001 1110 0111 0100 1000 0010 1100 0000 0000 0110 1101 1(2)

5. Positive number before normalization:

2 048.098 120 958 253 3(10) =


1000 0000 0000.0001 1001 0001 1110 0111 0100 1000 0010 1100 0000 0000 0110 1101 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 11 positions to the left, so that only one non zero digit remains to the left of it:


2 048.098 120 958 253 3(10) =


1000 0000 0000.0001 1001 0001 1110 0111 0100 1000 0010 1100 0000 0000 0110 1101 1(2) =


1000 0000 0000.0001 1001 0001 1110 0111 0100 1000 0010 1100 0000 0000 0110 1101 1(2) × 20 =


1.0000 0000 0000 0011 0010 0011 1100 1110 1001 0000 0101 1000 0000 0000 1101 1011(2) × 211


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): 11


Mantissa (not normalized):
1.0000 0000 0000 0011 0010 0011 1100 1110 1001 0000 0101 1000 0000 0000 1101 1011


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


11 + 2(11-1) - 1 =


(11 + 1 023)(10) =


1 034(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;
  • 1 034 ÷ 2 = 517 + 0;
  • 517 ÷ 2 = 258 + 1;
  • 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;

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) =


1034(10) =


100 0000 1010(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. 0000 0000 0000 0011 0010 0011 1100 1110 1001 0000 0101 1000 0000 0000 1101 1011 =


0000 0000 0000 0011 0010 0011 1100 1110 1001 0000 0101 1000 0000


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 1010


Mantissa (52 bits) =
0000 0000 0000 0011 0010 0011 1100 1110 1001 0000 0101 1000 0000


Decimal number 2 048.098 120 958 253 3 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 1010 - 0000 0000 0000 0011 0010 0011 1100 1110 1001 0000 0101 1000 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