-1 302.123 456 789 012 474 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -1 302.123 456 789 012 474(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
-1 302.123 456 789 012 474(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:

|-1 302.123 456 789 012 474| = 1 302.123 456 789 012 474


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: 0.123 456 789 012 474.

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) 0.123 456 789 012 474 × 2 = 0 + 0.246 913 578 024 948;
  • 2) 0.246 913 578 024 948 × 2 = 0 + 0.493 827 156 049 896;
  • 3) 0.493 827 156 049 896 × 2 = 0 + 0.987 654 312 099 792;
  • 4) 0.987 654 312 099 792 × 2 = 1 + 0.975 308 624 199 584;
  • 5) 0.975 308 624 199 584 × 2 = 1 + 0.950 617 248 399 168;
  • 6) 0.950 617 248 399 168 × 2 = 1 + 0.901 234 496 798 336;
  • 7) 0.901 234 496 798 336 × 2 = 1 + 0.802 468 993 596 672;
  • 8) 0.802 468 993 596 672 × 2 = 1 + 0.604 937 987 193 344;
  • 9) 0.604 937 987 193 344 × 2 = 1 + 0.209 875 974 386 688;
  • 10) 0.209 875 974 386 688 × 2 = 0 + 0.419 751 948 773 376;
  • 11) 0.419 751 948 773 376 × 2 = 0 + 0.839 503 897 546 752;
  • 12) 0.839 503 897 546 752 × 2 = 1 + 0.679 007 795 093 504;
  • 13) 0.679 007 795 093 504 × 2 = 1 + 0.358 015 590 187 008;
  • 14) 0.358 015 590 187 008 × 2 = 0 + 0.716 031 180 374 016;
  • 15) 0.716 031 180 374 016 × 2 = 1 + 0.432 062 360 748 032;
  • 16) 0.432 062 360 748 032 × 2 = 0 + 0.864 124 721 496 064;
  • 17) 0.864 124 721 496 064 × 2 = 1 + 0.728 249 442 992 128;
  • 18) 0.728 249 442 992 128 × 2 = 1 + 0.456 498 885 984 256;
  • 19) 0.456 498 885 984 256 × 2 = 0 + 0.912 997 771 968 512;
  • 20) 0.912 997 771 968 512 × 2 = 1 + 0.825 995 543 937 024;
  • 21) 0.825 995 543 937 024 × 2 = 1 + 0.651 991 087 874 048;
  • 22) 0.651 991 087 874 048 × 2 = 1 + 0.303 982 175 748 096;
  • 23) 0.303 982 175 748 096 × 2 = 0 + 0.607 964 351 496 192;
  • 24) 0.607 964 351 496 192 × 2 = 1 + 0.215 928 702 992 384;
  • 25) 0.215 928 702 992 384 × 2 = 0 + 0.431 857 405 984 768;
  • 26) 0.431 857 405 984 768 × 2 = 0 + 0.863 714 811 969 536;
  • 27) 0.863 714 811 969 536 × 2 = 1 + 0.727 429 623 939 072;
  • 28) 0.727 429 623 939 072 × 2 = 1 + 0.454 859 247 878 144;
  • 29) 0.454 859 247 878 144 × 2 = 0 + 0.909 718 495 756 288;
  • 30) 0.909 718 495 756 288 × 2 = 1 + 0.819 436 991 512 576;
  • 31) 0.819 436 991 512 576 × 2 = 1 + 0.638 873 983 025 152;
  • 32) 0.638 873 983 025 152 × 2 = 1 + 0.277 747 966 050 304;
  • 33) 0.277 747 966 050 304 × 2 = 0 + 0.555 495 932 100 608;
  • 34) 0.555 495 932 100 608 × 2 = 1 + 0.110 991 864 201 216;
  • 35) 0.110 991 864 201 216 × 2 = 0 + 0.221 983 728 402 432;
  • 36) 0.221 983 728 402 432 × 2 = 0 + 0.443 967 456 804 864;
  • 37) 0.443 967 456 804 864 × 2 = 0 + 0.887 934 913 609 728;
  • 38) 0.887 934 913 609 728 × 2 = 1 + 0.775 869 827 219 456;
  • 39) 0.775 869 827 219 456 × 2 = 1 + 0.551 739 654 438 912;
  • 40) 0.551 739 654 438 912 × 2 = 1 + 0.103 479 308 877 824;
  • 41) 0.103 479 308 877 824 × 2 = 0 + 0.206 958 617 755 648;
  • 42) 0.206 958 617 755 648 × 2 = 0 + 0.413 917 235 511 296;
  • 43) 0.413 917 235 511 296 × 2 = 0 + 0.827 834 471 022 592;
  • 44) 0.827 834 471 022 592 × 2 = 1 + 0.655 668 942 045 184;
  • 45) 0.655 668 942 045 184 × 2 = 1 + 0.311 337 884 090 368;
  • 46) 0.311 337 884 090 368 × 2 = 0 + 0.622 675 768 180 736;
  • 47) 0.622 675 768 180 736 × 2 = 1 + 0.245 351 536 361 472;
  • 48) 0.245 351 536 361 472 × 2 = 0 + 0.490 703 072 722 944;
  • 49) 0.490 703 072 722 944 × 2 = 0 + 0.981 406 145 445 888;
  • 50) 0.981 406 145 445 888 × 2 = 1 + 0.962 812 290 891 776;
  • 51) 0.962 812 290 891 776 × 2 = 1 + 0.925 624 581 783 552;
  • 52) 0.925 624 581 783 552 × 2 = 1 + 0.851 249 163 567 104;
  • 53) 0.851 249 163 567 104 × 2 = 1 + 0.702 498 327 134 208;

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:


0.123 456 789 012 474(10) =


0.0001 1111 1001 1010 1101 1101 0011 0111 0100 0111 0001 1010 0111 1(2)

6. Positive number before normalization:

1 302.123 456 789 012 474(10) =


101 0001 0110.0001 1111 1001 1010 1101 1101 0011 0111 0100 0111 0001 1010 0111 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:


1 302.123 456 789 012 474(10) =


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


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


1.0100 0101 1000 0111 1110 0110 1011 0111 0100 1101 1101 0001 1100 0110 1001 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 1100 0110 1001 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 1100 011 0100 1111 =


0100 0101 1000 0111 1110 0110 1011 0111 0100 1101 1101 0001 1100


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 1100


Decimal number -1 302.123 456 789 012 474 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 1100


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