2 145 571 579.002 405 112 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2 145 571 579.002 405 112(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
2 145 571 579.002 405 112(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: 2 145 571 579.
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;
  • 2 145 571 579 ÷ 2 = 1 072 785 789 + 1;
  • 1 072 785 789 ÷ 2 = 536 392 894 + 1;
  • 536 392 894 ÷ 2 = 268 196 447 + 0;
  • 268 196 447 ÷ 2 = 134 098 223 + 1;
  • 134 098 223 ÷ 2 = 67 049 111 + 1;
  • 67 049 111 ÷ 2 = 33 524 555 + 1;
  • 33 524 555 ÷ 2 = 16 762 277 + 1;
  • 16 762 277 ÷ 2 = 8 381 138 + 1;
  • 8 381 138 ÷ 2 = 4 190 569 + 0;
  • 4 190 569 ÷ 2 = 2 095 284 + 1;
  • 2 095 284 ÷ 2 = 1 047 642 + 0;
  • 1 047 642 ÷ 2 = 523 821 + 0;
  • 523 821 ÷ 2 = 261 910 + 1;
  • 261 910 ÷ 2 = 130 955 + 0;
  • 130 955 ÷ 2 = 65 477 + 1;
  • 65 477 ÷ 2 = 32 738 + 1;
  • 32 738 ÷ 2 = 16 369 + 0;
  • 16 369 ÷ 2 = 8 184 + 1;
  • 8 184 ÷ 2 = 4 092 + 0;
  • 4 092 ÷ 2 = 2 046 + 0;
  • 2 046 ÷ 2 = 1 023 + 0;
  • 1 023 ÷ 2 = 511 + 1;
  • 511 ÷ 2 = 255 + 1;
  • 255 ÷ 2 = 127 + 1;
  • 127 ÷ 2 = 63 + 1;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 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.

2 145 571 579(10) =


111 1111 1110 0010 1101 0010 1111 1011(2)


3. Convert to binary (base 2) the fractional part: 0.002 405 112.

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) 0.002 405 112 × 2 = 0 + 0.004 810 224;
  • 2) 0.004 810 224 × 2 = 0 + 0.009 620 448;
  • 3) 0.009 620 448 × 2 = 0 + 0.019 240 896;
  • 4) 0.019 240 896 × 2 = 0 + 0.038 481 792;
  • 5) 0.038 481 792 × 2 = 0 + 0.076 963 584;
  • 6) 0.076 963 584 × 2 = 0 + 0.153 927 168;
  • 7) 0.153 927 168 × 2 = 0 + 0.307 854 336;
  • 8) 0.307 854 336 × 2 = 0 + 0.615 708 672;
  • 9) 0.615 708 672 × 2 = 1 + 0.231 417 344;
  • 10) 0.231 417 344 × 2 = 0 + 0.462 834 688;
  • 11) 0.462 834 688 × 2 = 0 + 0.925 669 376;
  • 12) 0.925 669 376 × 2 = 1 + 0.851 338 752;
  • 13) 0.851 338 752 × 2 = 1 + 0.702 677 504;
  • 14) 0.702 677 504 × 2 = 1 + 0.405 355 008;
  • 15) 0.405 355 008 × 2 = 0 + 0.810 710 016;
  • 16) 0.810 710 016 × 2 = 1 + 0.621 420 032;
  • 17) 0.621 420 032 × 2 = 1 + 0.242 840 064;
  • 18) 0.242 840 064 × 2 = 0 + 0.485 680 128;
  • 19) 0.485 680 128 × 2 = 0 + 0.971 360 256;
  • 20) 0.971 360 256 × 2 = 1 + 0.942 720 512;
  • 21) 0.942 720 512 × 2 = 1 + 0.885 441 024;
  • 22) 0.885 441 024 × 2 = 1 + 0.770 882 048;
  • 23) 0.770 882 048 × 2 = 1 + 0.541 764 096;
  • 24) 0.541 764 096 × 2 = 1 + 0.083 528 192;
  • 25) 0.083 528 192 × 2 = 0 + 0.167 056 384;
  • 26) 0.167 056 384 × 2 = 0 + 0.334 112 768;
  • 27) 0.334 112 768 × 2 = 0 + 0.668 225 536;
  • 28) 0.668 225 536 × 2 = 1 + 0.336 451 072;
  • 29) 0.336 451 072 × 2 = 0 + 0.672 902 144;
  • 30) 0.672 902 144 × 2 = 1 + 0.345 804 288;
  • 31) 0.345 804 288 × 2 = 0 + 0.691 608 576;
  • 32) 0.691 608 576 × 2 = 1 + 0.383 217 152;
  • 33) 0.383 217 152 × 2 = 0 + 0.766 434 304;
  • 34) 0.766 434 304 × 2 = 1 + 0.532 868 608;
  • 35) 0.532 868 608 × 2 = 1 + 0.065 737 216;
  • 36) 0.065 737 216 × 2 = 0 + 0.131 474 432;
  • 37) 0.131 474 432 × 2 = 0 + 0.262 948 864;
  • 38) 0.262 948 864 × 2 = 0 + 0.525 897 728;
  • 39) 0.525 897 728 × 2 = 1 + 0.051 795 456;
  • 40) 0.051 795 456 × 2 = 0 + 0.103 590 912;
  • 41) 0.103 590 912 × 2 = 0 + 0.207 181 824;
  • 42) 0.207 181 824 × 2 = 0 + 0.414 363 648;
  • 43) 0.414 363 648 × 2 = 0 + 0.828 727 296;
  • 44) 0.828 727 296 × 2 = 1 + 0.657 454 592;
  • 45) 0.657 454 592 × 2 = 1 + 0.314 909 184;
  • 46) 0.314 909 184 × 2 = 0 + 0.629 818 368;
  • 47) 0.629 818 368 × 2 = 1 + 0.259 636 736;
  • 48) 0.259 636 736 × 2 = 0 + 0.519 273 472;
  • 49) 0.519 273 472 × 2 = 1 + 0.038 546 944;
  • 50) 0.038 546 944 × 2 = 0 + 0.077 093 888;
  • 51) 0.077 093 888 × 2 = 0 + 0.154 187 776;
  • 52) 0.154 187 776 × 2 = 0 + 0.308 375 552;
  • 53) 0.308 375 552 × 2 = 0 + 0.616 751 104;

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:


0.002 405 112(10) =


0.0000 0000 1001 1101 1001 1111 0001 0101 0110 0010 0001 1010 1000 0(2)

5. Positive number before normalization:

2 145 571 579.002 405 112(10) =


111 1111 1110 0010 1101 0010 1111 1011.0000 0000 1001 1101 1001 1111 0001 0101 0110 0010 0001 1010 1000 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 30 positions to the left, so that only one non zero digit remains to the left of it:


2 145 571 579.002 405 112(10) =


111 1111 1110 0010 1101 0010 1111 1011.0000 0000 1001 1101 1001 1111 0001 0101 0110 0010 0001 1010 1000 0(2) =


111 1111 1110 0010 1101 0010 1111 1011.0000 0000 1001 1101 1001 1111 0001 0101 0110 0010 0001 1010 1000 0(2) × 20 =


1.1111 1111 1000 1011 0100 1011 1110 1100 0000 0010 0111 0110 0111 1100 0101 0101 1000 1000 0110 1010 000(2) × 230


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): 30


Mantissa (not normalized):
1.1111 1111 1000 1011 0100 1011 1110 1100 0000 0010 0111 0110 0111 1100 0101 0101 1000 1000 0110 1010 000


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


30 + 2(11-1) - 1 =


(30 + 1 023)(10) =


1 053(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;
  • 1 053 ÷ 2 = 526 + 1;
  • 526 ÷ 2 = 263 + 0;
  • 263 ÷ 2 = 131 + 1;
  • 131 ÷ 2 = 65 + 1;
  • 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;

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) =


1053(10) =


100 0001 1101(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. 1111 1111 1000 1011 0100 1011 1110 1100 0000 0010 0111 0110 0111 110 0010 1010 1100 0100 0011 0101 0000 =


1111 1111 1000 1011 0100 1011 1110 1100 0000 0010 0111 0110 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 0001 1101


Mantissa (52 bits) =
1111 1111 1000 1011 0100 1011 1110 1100 0000 0010 0111 0110 0111


Decimal number 2 145 571 579.002 405 112 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0001 1101 - 1111 1111 1000 1011 0100 1011 1110 1100 0000 0010 0111 0110 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