2.714 285 714 293 51 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.714 285 714 293 51(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
2.714 285 714 293 51(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.
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 ÷ 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(10) =


10(2)


3. Convert to binary (base 2) the fractional part: 0.714 285 714 293 51.

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) 0.714 285 714 293 51 × 2 = 1 + 0.428 571 428 587 02;
  • 2) 0.428 571 428 587 02 × 2 = 0 + 0.857 142 857 174 04;
  • 3) 0.857 142 857 174 04 × 2 = 1 + 0.714 285 714 348 08;
  • 4) 0.714 285 714 348 08 × 2 = 1 + 0.428 571 428 696 16;
  • 5) 0.428 571 428 696 16 × 2 = 0 + 0.857 142 857 392 32;
  • 6) 0.857 142 857 392 32 × 2 = 1 + 0.714 285 714 784 64;
  • 7) 0.714 285 714 784 64 × 2 = 1 + 0.428 571 429 569 28;
  • 8) 0.428 571 429 569 28 × 2 = 0 + 0.857 142 859 138 56;
  • 9) 0.857 142 859 138 56 × 2 = 1 + 0.714 285 718 277 12;
  • 10) 0.714 285 718 277 12 × 2 = 1 + 0.428 571 436 554 24;
  • 11) 0.428 571 436 554 24 × 2 = 0 + 0.857 142 873 108 48;
  • 12) 0.857 142 873 108 48 × 2 = 1 + 0.714 285 746 216 96;
  • 13) 0.714 285 746 216 96 × 2 = 1 + 0.428 571 492 433 92;
  • 14) 0.428 571 492 433 92 × 2 = 0 + 0.857 142 984 867 84;
  • 15) 0.857 142 984 867 84 × 2 = 1 + 0.714 285 969 735 68;
  • 16) 0.714 285 969 735 68 × 2 = 1 + 0.428 571 939 471 36;
  • 17) 0.428 571 939 471 36 × 2 = 0 + 0.857 143 878 942 72;
  • 18) 0.857 143 878 942 72 × 2 = 1 + 0.714 287 757 885 44;
  • 19) 0.714 287 757 885 44 × 2 = 1 + 0.428 575 515 770 88;
  • 20) 0.428 575 515 770 88 × 2 = 0 + 0.857 151 031 541 76;
  • 21) 0.857 151 031 541 76 × 2 = 1 + 0.714 302 063 083 52;
  • 22) 0.714 302 063 083 52 × 2 = 1 + 0.428 604 126 167 04;
  • 23) 0.428 604 126 167 04 × 2 = 0 + 0.857 208 252 334 08;
  • 24) 0.857 208 252 334 08 × 2 = 1 + 0.714 416 504 668 16;
  • 25) 0.714 416 504 668 16 × 2 = 1 + 0.428 833 009 336 32;
  • 26) 0.428 833 009 336 32 × 2 = 0 + 0.857 666 018 672 64;
  • 27) 0.857 666 018 672 64 × 2 = 1 + 0.715 332 037 345 28;
  • 28) 0.715 332 037 345 28 × 2 = 1 + 0.430 664 074 690 56;
  • 29) 0.430 664 074 690 56 × 2 = 0 + 0.861 328 149 381 12;
  • 30) 0.861 328 149 381 12 × 2 = 1 + 0.722 656 298 762 24;
  • 31) 0.722 656 298 762 24 × 2 = 1 + 0.445 312 597 524 48;
  • 32) 0.445 312 597 524 48 × 2 = 0 + 0.890 625 195 048 96;
  • 33) 0.890 625 195 048 96 × 2 = 1 + 0.781 250 390 097 92;
  • 34) 0.781 250 390 097 92 × 2 = 1 + 0.562 500 780 195 84;
  • 35) 0.562 500 780 195 84 × 2 = 1 + 0.125 001 560 391 68;
  • 36) 0.125 001 560 391 68 × 2 = 0 + 0.250 003 120 783 36;
  • 37) 0.250 003 120 783 36 × 2 = 0 + 0.500 006 241 566 72;
  • 38) 0.500 006 241 566 72 × 2 = 1 + 0.000 012 483 133 44;
  • 39) 0.000 012 483 133 44 × 2 = 0 + 0.000 024 966 266 88;
  • 40) 0.000 024 966 266 88 × 2 = 0 + 0.000 049 932 533 76;
  • 41) 0.000 049 932 533 76 × 2 = 0 + 0.000 099 865 067 52;
  • 42) 0.000 099 865 067 52 × 2 = 0 + 0.000 199 730 135 04;
  • 43) 0.000 199 730 135 04 × 2 = 0 + 0.000 399 460 270 08;
  • 44) 0.000 399 460 270 08 × 2 = 0 + 0.000 798 920 540 16;
  • 45) 0.000 798 920 540 16 × 2 = 0 + 0.001 597 841 080 32;
  • 46) 0.001 597 841 080 32 × 2 = 0 + 0.003 195 682 160 64;
  • 47) 0.003 195 682 160 64 × 2 = 0 + 0.006 391 364 321 28;
  • 48) 0.006 391 364 321 28 × 2 = 0 + 0.012 782 728 642 56;
  • 49) 0.012 782 728 642 56 × 2 = 0 + 0.025 565 457 285 12;
  • 50) 0.025 565 457 285 12 × 2 = 0 + 0.051 130 914 570 24;
  • 51) 0.051 130 914 570 24 × 2 = 0 + 0.102 261 829 140 48;
  • 52) 0.102 261 829 140 48 × 2 = 0 + 0.204 523 658 280 96;
  • 53) 0.204 523 658 280 96 × 2 = 0 + 0.409 047 316 561 92;

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:


0.714 285 714 293 51(10) =


0.1011 0110 1101 1011 0110 1101 1011 0110 1110 0100 0000 0000 0000 0(2)

5. Positive number before normalization:

2.714 285 714 293 51(10) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1110 0100 0000 0000 0000 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 1 positions to the left, so that only one non zero digit remains to the left of it:


2.714 285 714 293 51(10) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1110 0100 0000 0000 0000 0(2) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1110 0100 0000 0000 0000 0(2) × 20 =


1.0101 1011 0110 1101 1011 0110 1101 1011 0111 0010 0000 0000 0000 00(2) × 21


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): 1


Mantissa (not normalized):
1.0101 1011 0110 1101 1011 0110 1101 1011 0111 0010 0000 0000 0000 00


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


1 + 2(11-1) - 1 =


(1 + 1 023)(10) =


1 024(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;
  • 1 024 ÷ 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;

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) =


1024(10) =


100 0000 0000(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. 0101 1011 0110 1101 1011 0110 1101 1011 0111 0010 0000 0000 0000 00 =


0101 1011 0110 1101 1011 0110 1101 1011 0111 0010 0000 0000 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 0000


Mantissa (52 bits) =
0101 1011 0110 1101 1011 0110 1101 1011 0111 0010 0000 0000 0000


Decimal number 2.714 285 714 293 51 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0000 - 0101 1011 0110 1101 1011 0110 1101 1011 0111 0010 0000 0000 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