2.560 879 601 235 235 321 2 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.560 879 601 235 235 321 2(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
2.560 879 601 235 235 321 2(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: 0.560 879 601 235 235 321 2.

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) 0.560 879 601 235 235 321 2 × 2 = 1 + 0.121 759 202 470 470 642 4;
  • 2) 0.121 759 202 470 470 642 4 × 2 = 0 + 0.243 518 404 940 941 284 8;
  • 3) 0.243 518 404 940 941 284 8 × 2 = 0 + 0.487 036 809 881 882 569 6;
  • 4) 0.487 036 809 881 882 569 6 × 2 = 0 + 0.974 073 619 763 765 139 2;
  • 5) 0.974 073 619 763 765 139 2 × 2 = 1 + 0.948 147 239 527 530 278 4;
  • 6) 0.948 147 239 527 530 278 4 × 2 = 1 + 0.896 294 479 055 060 556 8;
  • 7) 0.896 294 479 055 060 556 8 × 2 = 1 + 0.792 588 958 110 121 113 6;
  • 8) 0.792 588 958 110 121 113 6 × 2 = 1 + 0.585 177 916 220 242 227 2;
  • 9) 0.585 177 916 220 242 227 2 × 2 = 1 + 0.170 355 832 440 484 454 4;
  • 10) 0.170 355 832 440 484 454 4 × 2 = 0 + 0.340 711 664 880 968 908 8;
  • 11) 0.340 711 664 880 968 908 8 × 2 = 0 + 0.681 423 329 761 937 817 6;
  • 12) 0.681 423 329 761 937 817 6 × 2 = 1 + 0.362 846 659 523 875 635 2;
  • 13) 0.362 846 659 523 875 635 2 × 2 = 0 + 0.725 693 319 047 751 270 4;
  • 14) 0.725 693 319 047 751 270 4 × 2 = 1 + 0.451 386 638 095 502 540 8;
  • 15) 0.451 386 638 095 502 540 8 × 2 = 0 + 0.902 773 276 191 005 081 6;
  • 16) 0.902 773 276 191 005 081 6 × 2 = 1 + 0.805 546 552 382 010 163 2;
  • 17) 0.805 546 552 382 010 163 2 × 2 = 1 + 0.611 093 104 764 020 326 4;
  • 18) 0.611 093 104 764 020 326 4 × 2 = 1 + 0.222 186 209 528 040 652 8;
  • 19) 0.222 186 209 528 040 652 8 × 2 = 0 + 0.444 372 419 056 081 305 6;
  • 20) 0.444 372 419 056 081 305 6 × 2 = 0 + 0.888 744 838 112 162 611 2;
  • 21) 0.888 744 838 112 162 611 2 × 2 = 1 + 0.777 489 676 224 325 222 4;
  • 22) 0.777 489 676 224 325 222 4 × 2 = 1 + 0.554 979 352 448 650 444 8;
  • 23) 0.554 979 352 448 650 444 8 × 2 = 1 + 0.109 958 704 897 300 889 6;
  • 24) 0.109 958 704 897 300 889 6 × 2 = 0 + 0.219 917 409 794 601 779 2;
  • 25) 0.219 917 409 794 601 779 2 × 2 = 0 + 0.439 834 819 589 203 558 4;
  • 26) 0.439 834 819 589 203 558 4 × 2 = 0 + 0.879 669 639 178 407 116 8;
  • 27) 0.879 669 639 178 407 116 8 × 2 = 1 + 0.759 339 278 356 814 233 6;
  • 28) 0.759 339 278 356 814 233 6 × 2 = 1 + 0.518 678 556 713 628 467 2;
  • 29) 0.518 678 556 713 628 467 2 × 2 = 1 + 0.037 357 113 427 256 934 4;
  • 30) 0.037 357 113 427 256 934 4 × 2 = 0 + 0.074 714 226 854 513 868 8;
  • 31) 0.074 714 226 854 513 868 8 × 2 = 0 + 0.149 428 453 709 027 737 6;
  • 32) 0.149 428 453 709 027 737 6 × 2 = 0 + 0.298 856 907 418 055 475 2;
  • 33) 0.298 856 907 418 055 475 2 × 2 = 0 + 0.597 713 814 836 110 950 4;
  • 34) 0.597 713 814 836 110 950 4 × 2 = 1 + 0.195 427 629 672 221 900 8;
  • 35) 0.195 427 629 672 221 900 8 × 2 = 0 + 0.390 855 259 344 443 801 6;
  • 36) 0.390 855 259 344 443 801 6 × 2 = 0 + 0.781 710 518 688 887 603 2;
  • 37) 0.781 710 518 688 887 603 2 × 2 = 1 + 0.563 421 037 377 775 206 4;
  • 38) 0.563 421 037 377 775 206 4 × 2 = 1 + 0.126 842 074 755 550 412 8;
  • 39) 0.126 842 074 755 550 412 8 × 2 = 0 + 0.253 684 149 511 100 825 6;
  • 40) 0.253 684 149 511 100 825 6 × 2 = 0 + 0.507 368 299 022 201 651 2;
  • 41) 0.507 368 299 022 201 651 2 × 2 = 1 + 0.014 736 598 044 403 302 4;
  • 42) 0.014 736 598 044 403 302 4 × 2 = 0 + 0.029 473 196 088 806 604 8;
  • 43) 0.029 473 196 088 806 604 8 × 2 = 0 + 0.058 946 392 177 613 209 6;
  • 44) 0.058 946 392 177 613 209 6 × 2 = 0 + 0.117 892 784 355 226 419 2;
  • 45) 0.117 892 784 355 226 419 2 × 2 = 0 + 0.235 785 568 710 452 838 4;
  • 46) 0.235 785 568 710 452 838 4 × 2 = 0 + 0.471 571 137 420 905 676 8;
  • 47) 0.471 571 137 420 905 676 8 × 2 = 0 + 0.943 142 274 841 811 353 6;
  • 48) 0.943 142 274 841 811 353 6 × 2 = 1 + 0.886 284 549 683 622 707 2;
  • 49) 0.886 284 549 683 622 707 2 × 2 = 1 + 0.772 569 099 367 245 414 4;
  • 50) 0.772 569 099 367 245 414 4 × 2 = 1 + 0.545 138 198 734 490 828 8;
  • 51) 0.545 138 198 734 490 828 8 × 2 = 1 + 0.090 276 397 468 981 657 6;
  • 52) 0.090 276 397 468 981 657 6 × 2 = 0 + 0.180 552 794 937 963 315 2;
  • 53) 0.180 552 794 937 963 315 2 × 2 = 0 + 0.361 105 589 875 926 630 4;

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:


0.560 879 601 235 235 321 2(10) =


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

5. Positive number before normalization:

2.560 879 601 235 235 321 2(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:


2.560 879 601 235 235 321 2(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 2.560 879 601 235 235 321 2 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