-1 302.123 456 789 012 355 8 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -1 302.123 456 789 012 355 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
-1 302.123 456 789 012 355 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. Start with the positive version of the number:

|-1 302.123 456 789 012 355 8| = 1 302.123 456 789 012 355 8


2. First, convert to binary (in base 2) the integer part: 1 302.
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;
  • 1 302 ÷ 2 = 651 + 0;
  • 651 ÷ 2 = 325 + 1;
  • 325 ÷ 2 = 162 + 1;
  • 162 ÷ 2 = 81 + 0;
  • 81 ÷ 2 = 40 + 1;
  • 40 ÷ 2 = 20 + 0;
  • 20 ÷ 2 = 10 + 0;
  • 10 ÷ 2 = 5 + 0;
  • 5 ÷ 2 = 2 + 1;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

3. 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.

1 302(10) =


101 0001 0110(2)


4. Convert to binary (base 2) the fractional part: 0.123 456 789 012 355 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) 0.123 456 789 012 355 8 × 2 = 0 + 0.246 913 578 024 711 6;
  • 2) 0.246 913 578 024 711 6 × 2 = 0 + 0.493 827 156 049 423 2;
  • 3) 0.493 827 156 049 423 2 × 2 = 0 + 0.987 654 312 098 846 4;
  • 4) 0.987 654 312 098 846 4 × 2 = 1 + 0.975 308 624 197 692 8;
  • 5) 0.975 308 624 197 692 8 × 2 = 1 + 0.950 617 248 395 385 6;
  • 6) 0.950 617 248 395 385 6 × 2 = 1 + 0.901 234 496 790 771 2;
  • 7) 0.901 234 496 790 771 2 × 2 = 1 + 0.802 468 993 581 542 4;
  • 8) 0.802 468 993 581 542 4 × 2 = 1 + 0.604 937 987 163 084 8;
  • 9) 0.604 937 987 163 084 8 × 2 = 1 + 0.209 875 974 326 169 6;
  • 10) 0.209 875 974 326 169 6 × 2 = 0 + 0.419 751 948 652 339 2;
  • 11) 0.419 751 948 652 339 2 × 2 = 0 + 0.839 503 897 304 678 4;
  • 12) 0.839 503 897 304 678 4 × 2 = 1 + 0.679 007 794 609 356 8;
  • 13) 0.679 007 794 609 356 8 × 2 = 1 + 0.358 015 589 218 713 6;
  • 14) 0.358 015 589 218 713 6 × 2 = 0 + 0.716 031 178 437 427 2;
  • 15) 0.716 031 178 437 427 2 × 2 = 1 + 0.432 062 356 874 854 4;
  • 16) 0.432 062 356 874 854 4 × 2 = 0 + 0.864 124 713 749 708 8;
  • 17) 0.864 124 713 749 708 8 × 2 = 1 + 0.728 249 427 499 417 6;
  • 18) 0.728 249 427 499 417 6 × 2 = 1 + 0.456 498 854 998 835 2;
  • 19) 0.456 498 854 998 835 2 × 2 = 0 + 0.912 997 709 997 670 4;
  • 20) 0.912 997 709 997 670 4 × 2 = 1 + 0.825 995 419 995 340 8;
  • 21) 0.825 995 419 995 340 8 × 2 = 1 + 0.651 990 839 990 681 6;
  • 22) 0.651 990 839 990 681 6 × 2 = 1 + 0.303 981 679 981 363 2;
  • 23) 0.303 981 679 981 363 2 × 2 = 0 + 0.607 963 359 962 726 4;
  • 24) 0.607 963 359 962 726 4 × 2 = 1 + 0.215 926 719 925 452 8;
  • 25) 0.215 926 719 925 452 8 × 2 = 0 + 0.431 853 439 850 905 6;
  • 26) 0.431 853 439 850 905 6 × 2 = 0 + 0.863 706 879 701 811 2;
  • 27) 0.863 706 879 701 811 2 × 2 = 1 + 0.727 413 759 403 622 4;
  • 28) 0.727 413 759 403 622 4 × 2 = 1 + 0.454 827 518 807 244 8;
  • 29) 0.454 827 518 807 244 8 × 2 = 0 + 0.909 655 037 614 489 6;
  • 30) 0.909 655 037 614 489 6 × 2 = 1 + 0.819 310 075 228 979 2;
  • 31) 0.819 310 075 228 979 2 × 2 = 1 + 0.638 620 150 457 958 4;
  • 32) 0.638 620 150 457 958 4 × 2 = 1 + 0.277 240 300 915 916 8;
  • 33) 0.277 240 300 915 916 8 × 2 = 0 + 0.554 480 601 831 833 6;
  • 34) 0.554 480 601 831 833 6 × 2 = 1 + 0.108 961 203 663 667 2;
  • 35) 0.108 961 203 663 667 2 × 2 = 0 + 0.217 922 407 327 334 4;
  • 36) 0.217 922 407 327 334 4 × 2 = 0 + 0.435 844 814 654 668 8;
  • 37) 0.435 844 814 654 668 8 × 2 = 0 + 0.871 689 629 309 337 6;
  • 38) 0.871 689 629 309 337 6 × 2 = 1 + 0.743 379 258 618 675 2;
  • 39) 0.743 379 258 618 675 2 × 2 = 1 + 0.486 758 517 237 350 4;
  • 40) 0.486 758 517 237 350 4 × 2 = 0 + 0.973 517 034 474 700 8;
  • 41) 0.973 517 034 474 700 8 × 2 = 1 + 0.947 034 068 949 401 6;
  • 42) 0.947 034 068 949 401 6 × 2 = 1 + 0.894 068 137 898 803 2;
  • 43) 0.894 068 137 898 803 2 × 2 = 1 + 0.788 136 275 797 606 4;
  • 44) 0.788 136 275 797 606 4 × 2 = 1 + 0.576 272 551 595 212 8;
  • 45) 0.576 272 551 595 212 8 × 2 = 1 + 0.152 545 103 190 425 6;
  • 46) 0.152 545 103 190 425 6 × 2 = 0 + 0.305 090 206 380 851 2;
  • 47) 0.305 090 206 380 851 2 × 2 = 0 + 0.610 180 412 761 702 4;
  • 48) 0.610 180 412 761 702 4 × 2 = 1 + 0.220 360 825 523 404 8;
  • 49) 0.220 360 825 523 404 8 × 2 = 0 + 0.440 721 651 046 809 6;
  • 50) 0.440 721 651 046 809 6 × 2 = 0 + 0.881 443 302 093 619 2;
  • 51) 0.881 443 302 093 619 2 × 2 = 1 + 0.762 886 604 187 238 4;
  • 52) 0.762 886 604 187 238 4 × 2 = 1 + 0.525 773 208 374 476 8;
  • 53) 0.525 773 208 374 476 8 × 2 = 1 + 0.051 546 416 748 953 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).


5. 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:


0.123 456 789 012 355 8(10) =


0.0001 1111 1001 1010 1101 1101 0011 0111 0100 0110 1111 1001 0011 1(2)

6. Positive number before normalization:

1 302.123 456 789 012 355 8(10) =


101 0001 0110.0001 1111 1001 1010 1101 1101 0011 0111 0100 0110 1111 1001 0011 1(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 10 positions to the left, so that only one non zero digit remains to the left of it:


1 302.123 456 789 012 355 8(10) =


101 0001 0110.0001 1111 1001 1010 1101 1101 0011 0111 0100 0110 1111 1001 0011 1(2) =


101 0001 0110.0001 1111 1001 1010 1101 1101 0011 0111 0100 0110 1111 1001 0011 1(2) × 20 =


1.0100 0101 1000 0111 1110 0110 1011 0111 0100 1101 1101 0001 1011 1110 0100 111(2) × 210


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): 10


Mantissa (not normalized):
1.0100 0101 1000 0111 1110 0110 1011 0111 0100 1101 1101 0001 1011 1110 0100 111


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(11-1) - 1 =


10 + 2(11-1) - 1 =


(10 + 1 023)(10) =


1 033(10)


10. 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;
  • 1 033 ÷ 2 = 516 + 1;
  • 516 ÷ 2 = 258 + 0;
  • 258 ÷ 2 = 129 + 0;
  • 129 ÷ 2 = 64 + 1;
  • 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;

11. Construct the base 2 representation of the adjusted exponent.

Take all the remainders starting from the bottom of the list constructed above.


Exponent (adjusted) =


1033(10) =


100 0000 1001(2)


12. 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 0101 1000 0111 1110 0110 1011 0111 0100 1101 1101 0001 1011 111 0010 0111 =


0100 0101 1000 0111 1110 0110 1011 0111 0100 1101 1101 0001 1011


13. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

Sign (1 bit) =
1 (a negative number)


Exponent (11 bits) =
100 0000 1001


Mantissa (52 bits) =
0100 0101 1000 0111 1110 0110 1011 0111 0100 1101 1101 0001 1011


Decimal number -1 302.123 456 789 012 355 8 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 100 0000 1001 - 0100 0101 1000 0111 1110 0110 1011 0111 0100 1101 1101 0001 1011


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