2.560 879 601 235 235 333 9 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.560 879 601 235 235 333 9(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
2.560 879 601 235 235 333 9(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: 0.560 879 601 235 235 333 9.

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) 0.560 879 601 235 235 333 9 × 2 = 1 + 0.121 759 202 470 470 667 8;
  • 2) 0.121 759 202 470 470 667 8 × 2 = 0 + 0.243 518 404 940 941 335 6;
  • 3) 0.243 518 404 940 941 335 6 × 2 = 0 + 0.487 036 809 881 882 671 2;
  • 4) 0.487 036 809 881 882 671 2 × 2 = 0 + 0.974 073 619 763 765 342 4;
  • 5) 0.974 073 619 763 765 342 4 × 2 = 1 + 0.948 147 239 527 530 684 8;
  • 6) 0.948 147 239 527 530 684 8 × 2 = 1 + 0.896 294 479 055 061 369 6;
  • 7) 0.896 294 479 055 061 369 6 × 2 = 1 + 0.792 588 958 110 122 739 2;
  • 8) 0.792 588 958 110 122 739 2 × 2 = 1 + 0.585 177 916 220 245 478 4;
  • 9) 0.585 177 916 220 245 478 4 × 2 = 1 + 0.170 355 832 440 490 956 8;
  • 10) 0.170 355 832 440 490 956 8 × 2 = 0 + 0.340 711 664 880 981 913 6;
  • 11) 0.340 711 664 880 981 913 6 × 2 = 0 + 0.681 423 329 761 963 827 2;
  • 12) 0.681 423 329 761 963 827 2 × 2 = 1 + 0.362 846 659 523 927 654 4;
  • 13) 0.362 846 659 523 927 654 4 × 2 = 0 + 0.725 693 319 047 855 308 8;
  • 14) 0.725 693 319 047 855 308 8 × 2 = 1 + 0.451 386 638 095 710 617 6;
  • 15) 0.451 386 638 095 710 617 6 × 2 = 0 + 0.902 773 276 191 421 235 2;
  • 16) 0.902 773 276 191 421 235 2 × 2 = 1 + 0.805 546 552 382 842 470 4;
  • 17) 0.805 546 552 382 842 470 4 × 2 = 1 + 0.611 093 104 765 684 940 8;
  • 18) 0.611 093 104 765 684 940 8 × 2 = 1 + 0.222 186 209 531 369 881 6;
  • 19) 0.222 186 209 531 369 881 6 × 2 = 0 + 0.444 372 419 062 739 763 2;
  • 20) 0.444 372 419 062 739 763 2 × 2 = 0 + 0.888 744 838 125 479 526 4;
  • 21) 0.888 744 838 125 479 526 4 × 2 = 1 + 0.777 489 676 250 959 052 8;
  • 22) 0.777 489 676 250 959 052 8 × 2 = 1 + 0.554 979 352 501 918 105 6;
  • 23) 0.554 979 352 501 918 105 6 × 2 = 1 + 0.109 958 705 003 836 211 2;
  • 24) 0.109 958 705 003 836 211 2 × 2 = 0 + 0.219 917 410 007 672 422 4;
  • 25) 0.219 917 410 007 672 422 4 × 2 = 0 + 0.439 834 820 015 344 844 8;
  • 26) 0.439 834 820 015 344 844 8 × 2 = 0 + 0.879 669 640 030 689 689 6;
  • 27) 0.879 669 640 030 689 689 6 × 2 = 1 + 0.759 339 280 061 379 379 2;
  • 28) 0.759 339 280 061 379 379 2 × 2 = 1 + 0.518 678 560 122 758 758 4;
  • 29) 0.518 678 560 122 758 758 4 × 2 = 1 + 0.037 357 120 245 517 516 8;
  • 30) 0.037 357 120 245 517 516 8 × 2 = 0 + 0.074 714 240 491 035 033 6;
  • 31) 0.074 714 240 491 035 033 6 × 2 = 0 + 0.149 428 480 982 070 067 2;
  • 32) 0.149 428 480 982 070 067 2 × 2 = 0 + 0.298 856 961 964 140 134 4;
  • 33) 0.298 856 961 964 140 134 4 × 2 = 0 + 0.597 713 923 928 280 268 8;
  • 34) 0.597 713 923 928 280 268 8 × 2 = 1 + 0.195 427 847 856 560 537 6;
  • 35) 0.195 427 847 856 560 537 6 × 2 = 0 + 0.390 855 695 713 121 075 2;
  • 36) 0.390 855 695 713 121 075 2 × 2 = 0 + 0.781 711 391 426 242 150 4;
  • 37) 0.781 711 391 426 242 150 4 × 2 = 1 + 0.563 422 782 852 484 300 8;
  • 38) 0.563 422 782 852 484 300 8 × 2 = 1 + 0.126 845 565 704 968 601 6;
  • 39) 0.126 845 565 704 968 601 6 × 2 = 0 + 0.253 691 131 409 937 203 2;
  • 40) 0.253 691 131 409 937 203 2 × 2 = 0 + 0.507 382 262 819 874 406 4;
  • 41) 0.507 382 262 819 874 406 4 × 2 = 1 + 0.014 764 525 639 748 812 8;
  • 42) 0.014 764 525 639 748 812 8 × 2 = 0 + 0.029 529 051 279 497 625 6;
  • 43) 0.029 529 051 279 497 625 6 × 2 = 0 + 0.059 058 102 558 995 251 2;
  • 44) 0.059 058 102 558 995 251 2 × 2 = 0 + 0.118 116 205 117 990 502 4;
  • 45) 0.118 116 205 117 990 502 4 × 2 = 0 + 0.236 232 410 235 981 004 8;
  • 46) 0.236 232 410 235 981 004 8 × 2 = 0 + 0.472 464 820 471 962 009 6;
  • 47) 0.472 464 820 471 962 009 6 × 2 = 0 + 0.944 929 640 943 924 019 2;
  • 48) 0.944 929 640 943 924 019 2 × 2 = 1 + 0.889 859 281 887 848 038 4;
  • 49) 0.889 859 281 887 848 038 4 × 2 = 1 + 0.779 718 563 775 696 076 8;
  • 50) 0.779 718 563 775 696 076 8 × 2 = 1 + 0.559 437 127 551 392 153 6;
  • 51) 0.559 437 127 551 392 153 6 × 2 = 1 + 0.118 874 255 102 784 307 2;
  • 52) 0.118 874 255 102 784 307 2 × 2 = 0 + 0.237 748 510 205 568 614 4;
  • 53) 0.237 748 510 205 568 614 4 × 2 = 0 + 0.475 497 020 411 137 228 8;

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:


0.560 879 601 235 235 333 9(10) =


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

5. Positive number before normalization:

2.560 879 601 235 235 333 9(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:


2.560 879 601 235 235 333 9(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 2.560 879 601 235 235 333 9 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