-2 373 549 912 751 300 369 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -2 373 549 912 751 300 369(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
-2 373 549 912 751 300 369(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:

|-2 373 549 912 751 300 369| = 2 373 549 912 751 300 369


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;
  • 2 373 549 912 751 300 369 ÷ 2 = 1 186 774 956 375 650 184 + 1;
  • 1 186 774 956 375 650 184 ÷ 2 = 593 387 478 187 825 092 + 0;
  • 593 387 478 187 825 092 ÷ 2 = 296 693 739 093 912 546 + 0;
  • 296 693 739 093 912 546 ÷ 2 = 148 346 869 546 956 273 + 0;
  • 148 346 869 546 956 273 ÷ 2 = 74 173 434 773 478 136 + 1;
  • 74 173 434 773 478 136 ÷ 2 = 37 086 717 386 739 068 + 0;
  • 37 086 717 386 739 068 ÷ 2 = 18 543 358 693 369 534 + 0;
  • 18 543 358 693 369 534 ÷ 2 = 9 271 679 346 684 767 + 0;
  • 9 271 679 346 684 767 ÷ 2 = 4 635 839 673 342 383 + 1;
  • 4 635 839 673 342 383 ÷ 2 = 2 317 919 836 671 191 + 1;
  • 2 317 919 836 671 191 ÷ 2 = 1 158 959 918 335 595 + 1;
  • 1 158 959 918 335 595 ÷ 2 = 579 479 959 167 797 + 1;
  • 579 479 959 167 797 ÷ 2 = 289 739 979 583 898 + 1;
  • 289 739 979 583 898 ÷ 2 = 144 869 989 791 949 + 0;
  • 144 869 989 791 949 ÷ 2 = 72 434 994 895 974 + 1;
  • 72 434 994 895 974 ÷ 2 = 36 217 497 447 987 + 0;
  • 36 217 497 447 987 ÷ 2 = 18 108 748 723 993 + 1;
  • 18 108 748 723 993 ÷ 2 = 9 054 374 361 996 + 1;
  • 9 054 374 361 996 ÷ 2 = 4 527 187 180 998 + 0;
  • 4 527 187 180 998 ÷ 2 = 2 263 593 590 499 + 0;
  • 2 263 593 590 499 ÷ 2 = 1 131 796 795 249 + 1;
  • 1 131 796 795 249 ÷ 2 = 565 898 397 624 + 1;
  • 565 898 397 624 ÷ 2 = 282 949 198 812 + 0;
  • 282 949 198 812 ÷ 2 = 141 474 599 406 + 0;
  • 141 474 599 406 ÷ 2 = 70 737 299 703 + 0;
  • 70 737 299 703 ÷ 2 = 35 368 649 851 + 1;
  • 35 368 649 851 ÷ 2 = 17 684 324 925 + 1;
  • 17 684 324 925 ÷ 2 = 8 842 162 462 + 1;
  • 8 842 162 462 ÷ 2 = 4 421 081 231 + 0;
  • 4 421 081 231 ÷ 2 = 2 210 540 615 + 1;
  • 2 210 540 615 ÷ 2 = 1 105 270 307 + 1;
  • 1 105 270 307 ÷ 2 = 552 635 153 + 1;
  • 552 635 153 ÷ 2 = 276 317 576 + 1;
  • 276 317 576 ÷ 2 = 138 158 788 + 0;
  • 138 158 788 ÷ 2 = 69 079 394 + 0;
  • 69 079 394 ÷ 2 = 34 539 697 + 0;
  • 34 539 697 ÷ 2 = 17 269 848 + 1;
  • 17 269 848 ÷ 2 = 8 634 924 + 0;
  • 8 634 924 ÷ 2 = 4 317 462 + 0;
  • 4 317 462 ÷ 2 = 2 158 731 + 0;
  • 2 158 731 ÷ 2 = 1 079 365 + 1;
  • 1 079 365 ÷ 2 = 539 682 + 1;
  • 539 682 ÷ 2 = 269 841 + 0;
  • 269 841 ÷ 2 = 134 920 + 1;
  • 134 920 ÷ 2 = 67 460 + 0;
  • 67 460 ÷ 2 = 33 730 + 0;
  • 33 730 ÷ 2 = 16 865 + 0;
  • 16 865 ÷ 2 = 8 432 + 1;
  • 8 432 ÷ 2 = 4 216 + 0;
  • 4 216 ÷ 2 = 2 108 + 0;
  • 2 108 ÷ 2 = 1 054 + 0;
  • 1 054 ÷ 2 = 527 + 0;
  • 527 ÷ 2 = 263 + 1;
  • 263 ÷ 2 = 131 + 1;
  • 131 ÷ 2 = 65 + 1;
  • 65 ÷ 2 = 32 + 1;
  • 32 ÷ 2 = 16 + 0;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

3. Construct the base 2 representation of the positive number.

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

2 373 549 912 751 300 369(10) =


10 0000 1111 0000 1000 1011 0001 0001 1110 1110 0011 0011 0101 1111 0001 0001(2)


4. Normalize the binary representation of the number.

Shift the decimal mark 61 positions to the left, so that only one non zero digit remains to the left of it:


2 373 549 912 751 300 369(10) =


10 0000 1111 0000 1000 1011 0001 0001 1110 1110 0011 0011 0101 1111 0001 0001(2) =


10 0000 1111 0000 1000 1011 0001 0001 1110 1110 0011 0011 0101 1111 0001 0001(2) × 20 =


1.0000 0111 1000 0100 0101 1000 1000 1111 0111 0001 1001 1010 1111 1000 1000 1(2) × 261


5. 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): 61


Mantissa (not normalized):
1.0000 0111 1000 0100 0101 1000 1000 1111 0111 0001 1001 1010 1111 1000 1000 1


6. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


61 + 2(11-1) - 1 =


(61 + 1 023)(10) =


1 084(10)


7. 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;
  • 1 084 ÷ 2 = 542 + 0;
  • 542 ÷ 2 = 271 + 0;
  • 271 ÷ 2 = 135 + 1;
  • 135 ÷ 2 = 67 + 1;
  • 67 ÷ 2 = 33 + 1;
  • 33 ÷ 2 = 16 + 1;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

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

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


Exponent (adjusted) =


1084(10) =


100 0011 1100(2)


9. 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. 0000 0111 1000 0100 0101 1000 1000 1111 0111 0001 1001 1010 1111 1 0001 0001 =


0000 0111 1000 0100 0101 1000 1000 1111 0111 0001 1001 1010 1111


10. 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 0011 1100


Mantissa (52 bits) =
0000 0111 1000 0100 0101 1000 1000 1111 0111 0001 1001 1010 1111


Decimal number -2 373 549 912 751 300 369 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 100 0011 1100 - 0000 0111 1000 0100 0101 1000 1000 1111 0111 0001 1001 1010 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