2.560 879 601 235 235 330 5 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.560 879 601 235 235 330 5(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
2.560 879 601 235 235 330 5(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: 0.560 879 601 235 235 330 5.

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) 0.560 879 601 235 235 330 5 × 2 = 1 + 0.121 759 202 470 470 661;
  • 2) 0.121 759 202 470 470 661 × 2 = 0 + 0.243 518 404 940 941 322;
  • 3) 0.243 518 404 940 941 322 × 2 = 0 + 0.487 036 809 881 882 644;
  • 4) 0.487 036 809 881 882 644 × 2 = 0 + 0.974 073 619 763 765 288;
  • 5) 0.974 073 619 763 765 288 × 2 = 1 + 0.948 147 239 527 530 576;
  • 6) 0.948 147 239 527 530 576 × 2 = 1 + 0.896 294 479 055 061 152;
  • 7) 0.896 294 479 055 061 152 × 2 = 1 + 0.792 588 958 110 122 304;
  • 8) 0.792 588 958 110 122 304 × 2 = 1 + 0.585 177 916 220 244 608;
  • 9) 0.585 177 916 220 244 608 × 2 = 1 + 0.170 355 832 440 489 216;
  • 10) 0.170 355 832 440 489 216 × 2 = 0 + 0.340 711 664 880 978 432;
  • 11) 0.340 711 664 880 978 432 × 2 = 0 + 0.681 423 329 761 956 864;
  • 12) 0.681 423 329 761 956 864 × 2 = 1 + 0.362 846 659 523 913 728;
  • 13) 0.362 846 659 523 913 728 × 2 = 0 + 0.725 693 319 047 827 456;
  • 14) 0.725 693 319 047 827 456 × 2 = 1 + 0.451 386 638 095 654 912;
  • 15) 0.451 386 638 095 654 912 × 2 = 0 + 0.902 773 276 191 309 824;
  • 16) 0.902 773 276 191 309 824 × 2 = 1 + 0.805 546 552 382 619 648;
  • 17) 0.805 546 552 382 619 648 × 2 = 1 + 0.611 093 104 765 239 296;
  • 18) 0.611 093 104 765 239 296 × 2 = 1 + 0.222 186 209 530 478 592;
  • 19) 0.222 186 209 530 478 592 × 2 = 0 + 0.444 372 419 060 957 184;
  • 20) 0.444 372 419 060 957 184 × 2 = 0 + 0.888 744 838 121 914 368;
  • 21) 0.888 744 838 121 914 368 × 2 = 1 + 0.777 489 676 243 828 736;
  • 22) 0.777 489 676 243 828 736 × 2 = 1 + 0.554 979 352 487 657 472;
  • 23) 0.554 979 352 487 657 472 × 2 = 1 + 0.109 958 704 975 314 944;
  • 24) 0.109 958 704 975 314 944 × 2 = 0 + 0.219 917 409 950 629 888;
  • 25) 0.219 917 409 950 629 888 × 2 = 0 + 0.439 834 819 901 259 776;
  • 26) 0.439 834 819 901 259 776 × 2 = 0 + 0.879 669 639 802 519 552;
  • 27) 0.879 669 639 802 519 552 × 2 = 1 + 0.759 339 279 605 039 104;
  • 28) 0.759 339 279 605 039 104 × 2 = 1 + 0.518 678 559 210 078 208;
  • 29) 0.518 678 559 210 078 208 × 2 = 1 + 0.037 357 118 420 156 416;
  • 30) 0.037 357 118 420 156 416 × 2 = 0 + 0.074 714 236 840 312 832;
  • 31) 0.074 714 236 840 312 832 × 2 = 0 + 0.149 428 473 680 625 664;
  • 32) 0.149 428 473 680 625 664 × 2 = 0 + 0.298 856 947 361 251 328;
  • 33) 0.298 856 947 361 251 328 × 2 = 0 + 0.597 713 894 722 502 656;
  • 34) 0.597 713 894 722 502 656 × 2 = 1 + 0.195 427 789 445 005 312;
  • 35) 0.195 427 789 445 005 312 × 2 = 0 + 0.390 855 578 890 010 624;
  • 36) 0.390 855 578 890 010 624 × 2 = 0 + 0.781 711 157 780 021 248;
  • 37) 0.781 711 157 780 021 248 × 2 = 1 + 0.563 422 315 560 042 496;
  • 38) 0.563 422 315 560 042 496 × 2 = 1 + 0.126 844 631 120 084 992;
  • 39) 0.126 844 631 120 084 992 × 2 = 0 + 0.253 689 262 240 169 984;
  • 40) 0.253 689 262 240 169 984 × 2 = 0 + 0.507 378 524 480 339 968;
  • 41) 0.507 378 524 480 339 968 × 2 = 1 + 0.014 757 048 960 679 936;
  • 42) 0.014 757 048 960 679 936 × 2 = 0 + 0.029 514 097 921 359 872;
  • 43) 0.029 514 097 921 359 872 × 2 = 0 + 0.059 028 195 842 719 744;
  • 44) 0.059 028 195 842 719 744 × 2 = 0 + 0.118 056 391 685 439 488;
  • 45) 0.118 056 391 685 439 488 × 2 = 0 + 0.236 112 783 370 878 976;
  • 46) 0.236 112 783 370 878 976 × 2 = 0 + 0.472 225 566 741 757 952;
  • 47) 0.472 225 566 741 757 952 × 2 = 0 + 0.944 451 133 483 515 904;
  • 48) 0.944 451 133 483 515 904 × 2 = 1 + 0.888 902 266 967 031 808;
  • 49) 0.888 902 266 967 031 808 × 2 = 1 + 0.777 804 533 934 063 616;
  • 50) 0.777 804 533 934 063 616 × 2 = 1 + 0.555 609 067 868 127 232;
  • 51) 0.555 609 067 868 127 232 × 2 = 1 + 0.111 218 135 736 254 464;
  • 52) 0.111 218 135 736 254 464 × 2 = 0 + 0.222 436 271 472 508 928;
  • 53) 0.222 436 271 472 508 928 × 2 = 0 + 0.444 872 542 945 017 856;

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:


0.560 879 601 235 235 330 5(10) =


0.1000 1111 1001 0101 1100 1110 0011 1000 0100 1100 1000 0001 1110 0(2)

5. Positive number before normalization:

2.560 879 601 235 235 330 5(10) =


10.1000 1111 1001 0101 1100 1110 0011 1000 0100 1100 1000 0001 1110 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:


2.560 879 601 235 235 330 5(10) =


10.1000 1111 1001 0101 1100 1110 0011 1000 0100 1100 1000 0001 1110 0(2) =


10.1000 1111 1001 0101 1100 1110 0011 1000 0100 1100 1000 0001 1110 0(2) × 20 =


1.0100 0111 1100 1010 1110 0111 0001 1100 0010 0110 0100 0000 1111 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):
1.0100 0111 1100 1010 1110 0111 0001 1100 0010 0110 0100 0000 1111 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. 0100 0111 1100 1010 1110 0111 0001 1100 0010 0110 0100 0000 1111 00 =


0100 0111 1100 1010 1110 0111 0001 1100 0010 0110 0100 0000 1111


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) =
0100 0111 1100 1010 1110 0111 0001 1100 0010 0110 0100 0000 1111


Decimal number 2.560 879 601 235 235 330 5 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0000 - 0100 0111 1100 1010 1110 0111 0001 1100 0010 0110 0100 0000 1111


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