2.560 879 601 235 235 327 8 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.560 879 601 235 235 327 8(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
2.560 879 601 235 235 327 8(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: 0.560 879 601 235 235 327 8.

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) 0.560 879 601 235 235 327 8 × 2 = 1 + 0.121 759 202 470 470 655 6;
  • 2) 0.121 759 202 470 470 655 6 × 2 = 0 + 0.243 518 404 940 941 311 2;
  • 3) 0.243 518 404 940 941 311 2 × 2 = 0 + 0.487 036 809 881 882 622 4;
  • 4) 0.487 036 809 881 882 622 4 × 2 = 0 + 0.974 073 619 763 765 244 8;
  • 5) 0.974 073 619 763 765 244 8 × 2 = 1 + 0.948 147 239 527 530 489 6;
  • 6) 0.948 147 239 527 530 489 6 × 2 = 1 + 0.896 294 479 055 060 979 2;
  • 7) 0.896 294 479 055 060 979 2 × 2 = 1 + 0.792 588 958 110 121 958 4;
  • 8) 0.792 588 958 110 121 958 4 × 2 = 1 + 0.585 177 916 220 243 916 8;
  • 9) 0.585 177 916 220 243 916 8 × 2 = 1 + 0.170 355 832 440 487 833 6;
  • 10) 0.170 355 832 440 487 833 6 × 2 = 0 + 0.340 711 664 880 975 667 2;
  • 11) 0.340 711 664 880 975 667 2 × 2 = 0 + 0.681 423 329 761 951 334 4;
  • 12) 0.681 423 329 761 951 334 4 × 2 = 1 + 0.362 846 659 523 902 668 8;
  • 13) 0.362 846 659 523 902 668 8 × 2 = 0 + 0.725 693 319 047 805 337 6;
  • 14) 0.725 693 319 047 805 337 6 × 2 = 1 + 0.451 386 638 095 610 675 2;
  • 15) 0.451 386 638 095 610 675 2 × 2 = 0 + 0.902 773 276 191 221 350 4;
  • 16) 0.902 773 276 191 221 350 4 × 2 = 1 + 0.805 546 552 382 442 700 8;
  • 17) 0.805 546 552 382 442 700 8 × 2 = 1 + 0.611 093 104 764 885 401 6;
  • 18) 0.611 093 104 764 885 401 6 × 2 = 1 + 0.222 186 209 529 770 803 2;
  • 19) 0.222 186 209 529 770 803 2 × 2 = 0 + 0.444 372 419 059 541 606 4;
  • 20) 0.444 372 419 059 541 606 4 × 2 = 0 + 0.888 744 838 119 083 212 8;
  • 21) 0.888 744 838 119 083 212 8 × 2 = 1 + 0.777 489 676 238 166 425 6;
  • 22) 0.777 489 676 238 166 425 6 × 2 = 1 + 0.554 979 352 476 332 851 2;
  • 23) 0.554 979 352 476 332 851 2 × 2 = 1 + 0.109 958 704 952 665 702 4;
  • 24) 0.109 958 704 952 665 702 4 × 2 = 0 + 0.219 917 409 905 331 404 8;
  • 25) 0.219 917 409 905 331 404 8 × 2 = 0 + 0.439 834 819 810 662 809 6;
  • 26) 0.439 834 819 810 662 809 6 × 2 = 0 + 0.879 669 639 621 325 619 2;
  • 27) 0.879 669 639 621 325 619 2 × 2 = 1 + 0.759 339 279 242 651 238 4;
  • 28) 0.759 339 279 242 651 238 4 × 2 = 1 + 0.518 678 558 485 302 476 8;
  • 29) 0.518 678 558 485 302 476 8 × 2 = 1 + 0.037 357 116 970 604 953 6;
  • 30) 0.037 357 116 970 604 953 6 × 2 = 0 + 0.074 714 233 941 209 907 2;
  • 31) 0.074 714 233 941 209 907 2 × 2 = 0 + 0.149 428 467 882 419 814 4;
  • 32) 0.149 428 467 882 419 814 4 × 2 = 0 + 0.298 856 935 764 839 628 8;
  • 33) 0.298 856 935 764 839 628 8 × 2 = 0 + 0.597 713 871 529 679 257 6;
  • 34) 0.597 713 871 529 679 257 6 × 2 = 1 + 0.195 427 743 059 358 515 2;
  • 35) 0.195 427 743 059 358 515 2 × 2 = 0 + 0.390 855 486 118 717 030 4;
  • 36) 0.390 855 486 118 717 030 4 × 2 = 0 + 0.781 710 972 237 434 060 8;
  • 37) 0.781 710 972 237 434 060 8 × 2 = 1 + 0.563 421 944 474 868 121 6;
  • 38) 0.563 421 944 474 868 121 6 × 2 = 1 + 0.126 843 888 949 736 243 2;
  • 39) 0.126 843 888 949 736 243 2 × 2 = 0 + 0.253 687 777 899 472 486 4;
  • 40) 0.253 687 777 899 472 486 4 × 2 = 0 + 0.507 375 555 798 944 972 8;
  • 41) 0.507 375 555 798 944 972 8 × 2 = 1 + 0.014 751 111 597 889 945 6;
  • 42) 0.014 751 111 597 889 945 6 × 2 = 0 + 0.029 502 223 195 779 891 2;
  • 43) 0.029 502 223 195 779 891 2 × 2 = 0 + 0.059 004 446 391 559 782 4;
  • 44) 0.059 004 446 391 559 782 4 × 2 = 0 + 0.118 008 892 783 119 564 8;
  • 45) 0.118 008 892 783 119 564 8 × 2 = 0 + 0.236 017 785 566 239 129 6;
  • 46) 0.236 017 785 566 239 129 6 × 2 = 0 + 0.472 035 571 132 478 259 2;
  • 47) 0.472 035 571 132 478 259 2 × 2 = 0 + 0.944 071 142 264 956 518 4;
  • 48) 0.944 071 142 264 956 518 4 × 2 = 1 + 0.888 142 284 529 913 036 8;
  • 49) 0.888 142 284 529 913 036 8 × 2 = 1 + 0.776 284 569 059 826 073 6;
  • 50) 0.776 284 569 059 826 073 6 × 2 = 1 + 0.552 569 138 119 652 147 2;
  • 51) 0.552 569 138 119 652 147 2 × 2 = 1 + 0.105 138 276 239 304 294 4;
  • 52) 0.105 138 276 239 304 294 4 × 2 = 0 + 0.210 276 552 478 608 588 8;
  • 53) 0.210 276 552 478 608 588 8 × 2 = 0 + 0.420 553 104 957 217 177 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:


0.560 879 601 235 235 327 8(10) =


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

5. Positive number before normalization:

2.560 879 601 235 235 327 8(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:


2.560 879 601 235 235 327 8(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 2.560 879 601 235 235 327 8 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