-19.981 999 999 999 999 317 878 973 714 6 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -19.981 999 999 999 999 317 878 973 714 6(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
-19.981 999 999 999 999 317 878 973 714 6(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:

|-19.981 999 999 999 999 317 878 973 714 6| = 19.981 999 999 999 999 317 878 973 714 6


2. First, convert to binary (in base 2) the integer part: 19.
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;
  • 19 ÷ 2 = 9 + 1;
  • 9 ÷ 2 = 4 + 1;
  • 4 ÷ 2 = 2 + 0;
  • 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.

19(10) =


1 0011(2)


4. Convert to binary (base 2) the fractional part: 0.981 999 999 999 999 317 878 973 714 6.

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) 0.981 999 999 999 999 317 878 973 714 6 × 2 = 1 + 0.963 999 999 999 998 635 757 947 429 2;
  • 2) 0.963 999 999 999 998 635 757 947 429 2 × 2 = 1 + 0.927 999 999 999 997 271 515 894 858 4;
  • 3) 0.927 999 999 999 997 271 515 894 858 4 × 2 = 1 + 0.855 999 999 999 994 543 031 789 716 8;
  • 4) 0.855 999 999 999 994 543 031 789 716 8 × 2 = 1 + 0.711 999 999 999 989 086 063 579 433 6;
  • 5) 0.711 999 999 999 989 086 063 579 433 6 × 2 = 1 + 0.423 999 999 999 978 172 127 158 867 2;
  • 6) 0.423 999 999 999 978 172 127 158 867 2 × 2 = 0 + 0.847 999 999 999 956 344 254 317 734 4;
  • 7) 0.847 999 999 999 956 344 254 317 734 4 × 2 = 1 + 0.695 999 999 999 912 688 508 635 468 8;
  • 8) 0.695 999 999 999 912 688 508 635 468 8 × 2 = 1 + 0.391 999 999 999 825 377 017 270 937 6;
  • 9) 0.391 999 999 999 825 377 017 270 937 6 × 2 = 0 + 0.783 999 999 999 650 754 034 541 875 2;
  • 10) 0.783 999 999 999 650 754 034 541 875 2 × 2 = 1 + 0.567 999 999 999 301 508 069 083 750 4;
  • 11) 0.567 999 999 999 301 508 069 083 750 4 × 2 = 1 + 0.135 999 999 998 603 016 138 167 500 8;
  • 12) 0.135 999 999 998 603 016 138 167 500 8 × 2 = 0 + 0.271 999 999 997 206 032 276 335 001 6;
  • 13) 0.271 999 999 997 206 032 276 335 001 6 × 2 = 0 + 0.543 999 999 994 412 064 552 670 003 2;
  • 14) 0.543 999 999 994 412 064 552 670 003 2 × 2 = 1 + 0.087 999 999 988 824 129 105 340 006 4;
  • 15) 0.087 999 999 988 824 129 105 340 006 4 × 2 = 0 + 0.175 999 999 977 648 258 210 680 012 8;
  • 16) 0.175 999 999 977 648 258 210 680 012 8 × 2 = 0 + 0.351 999 999 955 296 516 421 360 025 6;
  • 17) 0.351 999 999 955 296 516 421 360 025 6 × 2 = 0 + 0.703 999 999 910 593 032 842 720 051 2;
  • 18) 0.703 999 999 910 593 032 842 720 051 2 × 2 = 1 + 0.407 999 999 821 186 065 685 440 102 4;
  • 19) 0.407 999 999 821 186 065 685 440 102 4 × 2 = 0 + 0.815 999 999 642 372 131 370 880 204 8;
  • 20) 0.815 999 999 642 372 131 370 880 204 8 × 2 = 1 + 0.631 999 999 284 744 262 741 760 409 6;
  • 21) 0.631 999 999 284 744 262 741 760 409 6 × 2 = 1 + 0.263 999 998 569 488 525 483 520 819 2;
  • 22) 0.263 999 998 569 488 525 483 520 819 2 × 2 = 0 + 0.527 999 997 138 977 050 967 041 638 4;
  • 23) 0.527 999 997 138 977 050 967 041 638 4 × 2 = 1 + 0.055 999 994 277 954 101 934 083 276 8;
  • 24) 0.055 999 994 277 954 101 934 083 276 8 × 2 = 0 + 0.111 999 988 555 908 203 868 166 553 6;
  • 25) 0.111 999 988 555 908 203 868 166 553 6 × 2 = 0 + 0.223 999 977 111 816 407 736 333 107 2;
  • 26) 0.223 999 977 111 816 407 736 333 107 2 × 2 = 0 + 0.447 999 954 223 632 815 472 666 214 4;
  • 27) 0.447 999 954 223 632 815 472 666 214 4 × 2 = 0 + 0.895 999 908 447 265 630 945 332 428 8;
  • 28) 0.895 999 908 447 265 630 945 332 428 8 × 2 = 1 + 0.791 999 816 894 531 261 890 664 857 6;
  • 29) 0.791 999 816 894 531 261 890 664 857 6 × 2 = 1 + 0.583 999 633 789 062 523 781 329 715 2;
  • 30) 0.583 999 633 789 062 523 781 329 715 2 × 2 = 1 + 0.167 999 267 578 125 047 562 659 430 4;
  • 31) 0.167 999 267 578 125 047 562 659 430 4 × 2 = 0 + 0.335 998 535 156 250 095 125 318 860 8;
  • 32) 0.335 998 535 156 250 095 125 318 860 8 × 2 = 0 + 0.671 997 070 312 500 190 250 637 721 6;
  • 33) 0.671 997 070 312 500 190 250 637 721 6 × 2 = 1 + 0.343 994 140 625 000 380 501 275 443 2;
  • 34) 0.343 994 140 625 000 380 501 275 443 2 × 2 = 0 + 0.687 988 281 250 000 761 002 550 886 4;
  • 35) 0.687 988 281 250 000 761 002 550 886 4 × 2 = 1 + 0.375 976 562 500 001 522 005 101 772 8;
  • 36) 0.375 976 562 500 001 522 005 101 772 8 × 2 = 0 + 0.751 953 125 000 003 044 010 203 545 6;
  • 37) 0.751 953 125 000 003 044 010 203 545 6 × 2 = 1 + 0.503 906 250 000 006 088 020 407 091 2;
  • 38) 0.503 906 250 000 006 088 020 407 091 2 × 2 = 1 + 0.007 812 500 000 012 176 040 814 182 4;
  • 39) 0.007 812 500 000 012 176 040 814 182 4 × 2 = 0 + 0.015 625 000 000 024 352 081 628 364 8;
  • 40) 0.015 625 000 000 024 352 081 628 364 8 × 2 = 0 + 0.031 250 000 000 048 704 163 256 729 6;
  • 41) 0.031 250 000 000 048 704 163 256 729 6 × 2 = 0 + 0.062 500 000 000 097 408 326 513 459 2;
  • 42) 0.062 500 000 000 097 408 326 513 459 2 × 2 = 0 + 0.125 000 000 000 194 816 653 026 918 4;
  • 43) 0.125 000 000 000 194 816 653 026 918 4 × 2 = 0 + 0.250 000 000 000 389 633 306 053 836 8;
  • 44) 0.250 000 000 000 389 633 306 053 836 8 × 2 = 0 + 0.500 000 000 000 779 266 612 107 673 6;
  • 45) 0.500 000 000 000 779 266 612 107 673 6 × 2 = 1 + 0.000 000 000 001 558 533 224 215 347 2;
  • 46) 0.000 000 000 001 558 533 224 215 347 2 × 2 = 0 + 0.000 000 000 003 117 066 448 430 694 4;
  • 47) 0.000 000 000 003 117 066 448 430 694 4 × 2 = 0 + 0.000 000 000 006 234 132 896 861 388 8;
  • 48) 0.000 000 000 006 234 132 896 861 388 8 × 2 = 0 + 0.000 000 000 012 468 265 793 722 777 6;
  • 49) 0.000 000 000 012 468 265 793 722 777 6 × 2 = 0 + 0.000 000 000 024 936 531 587 445 555 2;
  • 50) 0.000 000 000 024 936 531 587 445 555 2 × 2 = 0 + 0.000 000 000 049 873 063 174 891 110 4;
  • 51) 0.000 000 000 049 873 063 174 891 110 4 × 2 = 0 + 0.000 000 000 099 746 126 349 782 220 8;
  • 52) 0.000 000 000 099 746 126 349 782 220 8 × 2 = 0 + 0.000 000 000 199 492 252 699 564 441 6;
  • 53) 0.000 000 000 199 492 252 699 564 441 6 × 2 = 0 + 0.000 000 000 398 984 505 399 128 883 2;

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:


0.981 999 999 999 999 317 878 973 714 6(10) =


0.1111 1011 0110 0100 0101 1010 0001 1100 1010 1100 0000 1000 0000 0(2)

6. Positive number before normalization:

19.981 999 999 999 999 317 878 973 714 6(10) =


1 0011.1111 1011 0110 0100 0101 1010 0001 1100 1010 1100 0000 1000 0000 0(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 4 positions to the left, so that only one non zero digit remains to the left of it:


19.981 999 999 999 999 317 878 973 714 6(10) =


1 0011.1111 1011 0110 0100 0101 1010 0001 1100 1010 1100 0000 1000 0000 0(2) =


1 0011.1111 1011 0110 0100 0101 1010 0001 1100 1010 1100 0000 1000 0000 0(2) × 20 =


1.0011 1111 1011 0110 0100 0101 1010 0001 1100 1010 1100 0000 1000 0000 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):
1.0011 1111 1011 0110 0100 0101 1010 0001 1100 1010 1100 0000 1000 0000 0


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


4 + 2(11-1) - 1 =


(4 + 1 023)(10) =


1 027(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;
  • 1 027 ÷ 2 = 513 + 1;
  • 513 ÷ 2 = 256 + 1;
  • 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;

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) =


1027(10) =


100 0000 0011(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. 0011 1111 1011 0110 0100 0101 1010 0001 1100 1010 1100 0000 1000 0 0000 =


0011 1111 1011 0110 0100 0101 1010 0001 1100 1010 1100 0000 1000


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 0011


Mantissa (52 bits) =
0011 1111 1011 0110 0100 0101 1010 0001 1100 1010 1100 0000 1000


Decimal number -19.981 999 999 999 999 317 878 973 714 6 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 100 0000 0011 - 0011 1111 1011 0110 0100 0101 1010 0001 1100 1010 1100 0000 1000


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