2.560 879 601 235 235 337 8 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.560 879 601 235 235 337 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
2.560 879 601 235 235 337 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: 0.560 879 601 235 235 337 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) 0.560 879 601 235 235 337 8 × 2 = 1 + 0.121 759 202 470 470 675 6;
  • 2) 0.121 759 202 470 470 675 6 × 2 = 0 + 0.243 518 404 940 941 351 2;
  • 3) 0.243 518 404 940 941 351 2 × 2 = 0 + 0.487 036 809 881 882 702 4;
  • 4) 0.487 036 809 881 882 702 4 × 2 = 0 + 0.974 073 619 763 765 404 8;
  • 5) 0.974 073 619 763 765 404 8 × 2 = 1 + 0.948 147 239 527 530 809 6;
  • 6) 0.948 147 239 527 530 809 6 × 2 = 1 + 0.896 294 479 055 061 619 2;
  • 7) 0.896 294 479 055 061 619 2 × 2 = 1 + 0.792 588 958 110 123 238 4;
  • 8) 0.792 588 958 110 123 238 4 × 2 = 1 + 0.585 177 916 220 246 476 8;
  • 9) 0.585 177 916 220 246 476 8 × 2 = 1 + 0.170 355 832 440 492 953 6;
  • 10) 0.170 355 832 440 492 953 6 × 2 = 0 + 0.340 711 664 880 985 907 2;
  • 11) 0.340 711 664 880 985 907 2 × 2 = 0 + 0.681 423 329 761 971 814 4;
  • 12) 0.681 423 329 761 971 814 4 × 2 = 1 + 0.362 846 659 523 943 628 8;
  • 13) 0.362 846 659 523 943 628 8 × 2 = 0 + 0.725 693 319 047 887 257 6;
  • 14) 0.725 693 319 047 887 257 6 × 2 = 1 + 0.451 386 638 095 774 515 2;
  • 15) 0.451 386 638 095 774 515 2 × 2 = 0 + 0.902 773 276 191 549 030 4;
  • 16) 0.902 773 276 191 549 030 4 × 2 = 1 + 0.805 546 552 383 098 060 8;
  • 17) 0.805 546 552 383 098 060 8 × 2 = 1 + 0.611 093 104 766 196 121 6;
  • 18) 0.611 093 104 766 196 121 6 × 2 = 1 + 0.222 186 209 532 392 243 2;
  • 19) 0.222 186 209 532 392 243 2 × 2 = 0 + 0.444 372 419 064 784 486 4;
  • 20) 0.444 372 419 064 784 486 4 × 2 = 0 + 0.888 744 838 129 568 972 8;
  • 21) 0.888 744 838 129 568 972 8 × 2 = 1 + 0.777 489 676 259 137 945 6;
  • 22) 0.777 489 676 259 137 945 6 × 2 = 1 + 0.554 979 352 518 275 891 2;
  • 23) 0.554 979 352 518 275 891 2 × 2 = 1 + 0.109 958 705 036 551 782 4;
  • 24) 0.109 958 705 036 551 782 4 × 2 = 0 + 0.219 917 410 073 103 564 8;
  • 25) 0.219 917 410 073 103 564 8 × 2 = 0 + 0.439 834 820 146 207 129 6;
  • 26) 0.439 834 820 146 207 129 6 × 2 = 0 + 0.879 669 640 292 414 259 2;
  • 27) 0.879 669 640 292 414 259 2 × 2 = 1 + 0.759 339 280 584 828 518 4;
  • 28) 0.759 339 280 584 828 518 4 × 2 = 1 + 0.518 678 561 169 657 036 8;
  • 29) 0.518 678 561 169 657 036 8 × 2 = 1 + 0.037 357 122 339 314 073 6;
  • 30) 0.037 357 122 339 314 073 6 × 2 = 0 + 0.074 714 244 678 628 147 2;
  • 31) 0.074 714 244 678 628 147 2 × 2 = 0 + 0.149 428 489 357 256 294 4;
  • 32) 0.149 428 489 357 256 294 4 × 2 = 0 + 0.298 856 978 714 512 588 8;
  • 33) 0.298 856 978 714 512 588 8 × 2 = 0 + 0.597 713 957 429 025 177 6;
  • 34) 0.597 713 957 429 025 177 6 × 2 = 1 + 0.195 427 914 858 050 355 2;
  • 35) 0.195 427 914 858 050 355 2 × 2 = 0 + 0.390 855 829 716 100 710 4;
  • 36) 0.390 855 829 716 100 710 4 × 2 = 0 + 0.781 711 659 432 201 420 8;
  • 37) 0.781 711 659 432 201 420 8 × 2 = 1 + 0.563 423 318 864 402 841 6;
  • 38) 0.563 423 318 864 402 841 6 × 2 = 1 + 0.126 846 637 728 805 683 2;
  • 39) 0.126 846 637 728 805 683 2 × 2 = 0 + 0.253 693 275 457 611 366 4;
  • 40) 0.253 693 275 457 611 366 4 × 2 = 0 + 0.507 386 550 915 222 732 8;
  • 41) 0.507 386 550 915 222 732 8 × 2 = 1 + 0.014 773 101 830 445 465 6;
  • 42) 0.014 773 101 830 445 465 6 × 2 = 0 + 0.029 546 203 660 890 931 2;
  • 43) 0.029 546 203 660 890 931 2 × 2 = 0 + 0.059 092 407 321 781 862 4;
  • 44) 0.059 092 407 321 781 862 4 × 2 = 0 + 0.118 184 814 643 563 724 8;
  • 45) 0.118 184 814 643 563 724 8 × 2 = 0 + 0.236 369 629 287 127 449 6;
  • 46) 0.236 369 629 287 127 449 6 × 2 = 0 + 0.472 739 258 574 254 899 2;
  • 47) 0.472 739 258 574 254 899 2 × 2 = 0 + 0.945 478 517 148 509 798 4;
  • 48) 0.945 478 517 148 509 798 4 × 2 = 1 + 0.890 957 034 297 019 596 8;
  • 49) 0.890 957 034 297 019 596 8 × 2 = 1 + 0.781 914 068 594 039 193 6;
  • 50) 0.781 914 068 594 039 193 6 × 2 = 1 + 0.563 828 137 188 078 387 2;
  • 51) 0.563 828 137 188 078 387 2 × 2 = 1 + 0.127 656 274 376 156 774 4;
  • 52) 0.127 656 274 376 156 774 4 × 2 = 0 + 0.255 312 548 752 313 548 8;
  • 53) 0.255 312 548 752 313 548 8 × 2 = 0 + 0.510 625 097 504 627 097 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:


0.560 879 601 235 235 337 8(10) =


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

5. Positive number before normalization:

2.560 879 601 235 235 337 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:


2.560 879 601 235 235 337 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 2.560 879 601 235 235 337 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