-2.211 829 052 383 358 300 119 548 647 3 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -2.211 829 052 383 358 300 119 548 647 3(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
-2.211 829 052 383 358 300 119 548 647 3(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:

|-2.211 829 052 383 358 300 119 548 647 3| = 2.211 829 052 383 358 300 119 548 647 3


2. 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;

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.

2(10) =


10(2)


4. Convert to binary (base 2) the fractional part: 0.211 829 052 383 358 300 119 548 647 3.

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) 0.211 829 052 383 358 300 119 548 647 3 × 2 = 0 + 0.423 658 104 766 716 600 239 097 294 6;
  • 2) 0.423 658 104 766 716 600 239 097 294 6 × 2 = 0 + 0.847 316 209 533 433 200 478 194 589 2;
  • 3) 0.847 316 209 533 433 200 478 194 589 2 × 2 = 1 + 0.694 632 419 066 866 400 956 389 178 4;
  • 4) 0.694 632 419 066 866 400 956 389 178 4 × 2 = 1 + 0.389 264 838 133 732 801 912 778 356 8;
  • 5) 0.389 264 838 133 732 801 912 778 356 8 × 2 = 0 + 0.778 529 676 267 465 603 825 556 713 6;
  • 6) 0.778 529 676 267 465 603 825 556 713 6 × 2 = 1 + 0.557 059 352 534 931 207 651 113 427 2;
  • 7) 0.557 059 352 534 931 207 651 113 427 2 × 2 = 1 + 0.114 118 705 069 862 415 302 226 854 4;
  • 8) 0.114 118 705 069 862 415 302 226 854 4 × 2 = 0 + 0.228 237 410 139 724 830 604 453 708 8;
  • 9) 0.228 237 410 139 724 830 604 453 708 8 × 2 = 0 + 0.456 474 820 279 449 661 208 907 417 6;
  • 10) 0.456 474 820 279 449 661 208 907 417 6 × 2 = 0 + 0.912 949 640 558 899 322 417 814 835 2;
  • 11) 0.912 949 640 558 899 322 417 814 835 2 × 2 = 1 + 0.825 899 281 117 798 644 835 629 670 4;
  • 12) 0.825 899 281 117 798 644 835 629 670 4 × 2 = 1 + 0.651 798 562 235 597 289 671 259 340 8;
  • 13) 0.651 798 562 235 597 289 671 259 340 8 × 2 = 1 + 0.303 597 124 471 194 579 342 518 681 6;
  • 14) 0.303 597 124 471 194 579 342 518 681 6 × 2 = 0 + 0.607 194 248 942 389 158 685 037 363 2;
  • 15) 0.607 194 248 942 389 158 685 037 363 2 × 2 = 1 + 0.214 388 497 884 778 317 370 074 726 4;
  • 16) 0.214 388 497 884 778 317 370 074 726 4 × 2 = 0 + 0.428 776 995 769 556 634 740 149 452 8;
  • 17) 0.428 776 995 769 556 634 740 149 452 8 × 2 = 0 + 0.857 553 991 539 113 269 480 298 905 6;
  • 18) 0.857 553 991 539 113 269 480 298 905 6 × 2 = 1 + 0.715 107 983 078 226 538 960 597 811 2;
  • 19) 0.715 107 983 078 226 538 960 597 811 2 × 2 = 1 + 0.430 215 966 156 453 077 921 195 622 4;
  • 20) 0.430 215 966 156 453 077 921 195 622 4 × 2 = 0 + 0.860 431 932 312 906 155 842 391 244 8;
  • 21) 0.860 431 932 312 906 155 842 391 244 8 × 2 = 1 + 0.720 863 864 625 812 311 684 782 489 6;
  • 22) 0.720 863 864 625 812 311 684 782 489 6 × 2 = 1 + 0.441 727 729 251 624 623 369 564 979 2;
  • 23) 0.441 727 729 251 624 623 369 564 979 2 × 2 = 0 + 0.883 455 458 503 249 246 739 129 958 4;
  • 24) 0.883 455 458 503 249 246 739 129 958 4 × 2 = 1 + 0.766 910 917 006 498 493 478 259 916 8;
  • 25) 0.766 910 917 006 498 493 478 259 916 8 × 2 = 1 + 0.533 821 834 012 996 986 956 519 833 6;
  • 26) 0.533 821 834 012 996 986 956 519 833 6 × 2 = 1 + 0.067 643 668 025 993 973 913 039 667 2;
  • 27) 0.067 643 668 025 993 973 913 039 667 2 × 2 = 0 + 0.135 287 336 051 987 947 826 079 334 4;
  • 28) 0.135 287 336 051 987 947 826 079 334 4 × 2 = 0 + 0.270 574 672 103 975 895 652 158 668 8;
  • 29) 0.270 574 672 103 975 895 652 158 668 8 × 2 = 0 + 0.541 149 344 207 951 791 304 317 337 6;
  • 30) 0.541 149 344 207 951 791 304 317 337 6 × 2 = 1 + 0.082 298 688 415 903 582 608 634 675 2;
  • 31) 0.082 298 688 415 903 582 608 634 675 2 × 2 = 0 + 0.164 597 376 831 807 165 217 269 350 4;
  • 32) 0.164 597 376 831 807 165 217 269 350 4 × 2 = 0 + 0.329 194 753 663 614 330 434 538 700 8;
  • 33) 0.329 194 753 663 614 330 434 538 700 8 × 2 = 0 + 0.658 389 507 327 228 660 869 077 401 6;
  • 34) 0.658 389 507 327 228 660 869 077 401 6 × 2 = 1 + 0.316 779 014 654 457 321 738 154 803 2;
  • 35) 0.316 779 014 654 457 321 738 154 803 2 × 2 = 0 + 0.633 558 029 308 914 643 476 309 606 4;
  • 36) 0.633 558 029 308 914 643 476 309 606 4 × 2 = 1 + 0.267 116 058 617 829 286 952 619 212 8;
  • 37) 0.267 116 058 617 829 286 952 619 212 8 × 2 = 0 + 0.534 232 117 235 658 573 905 238 425 6;
  • 38) 0.534 232 117 235 658 573 905 238 425 6 × 2 = 1 + 0.068 464 234 471 317 147 810 476 851 2;
  • 39) 0.068 464 234 471 317 147 810 476 851 2 × 2 = 0 + 0.136 928 468 942 634 295 620 953 702 4;
  • 40) 0.136 928 468 942 634 295 620 953 702 4 × 2 = 0 + 0.273 856 937 885 268 591 241 907 404 8;
  • 41) 0.273 856 937 885 268 591 241 907 404 8 × 2 = 0 + 0.547 713 875 770 537 182 483 814 809 6;
  • 42) 0.547 713 875 770 537 182 483 814 809 6 × 2 = 1 + 0.095 427 751 541 074 364 967 629 619 2;
  • 43) 0.095 427 751 541 074 364 967 629 619 2 × 2 = 0 + 0.190 855 503 082 148 729 935 259 238 4;
  • 44) 0.190 855 503 082 148 729 935 259 238 4 × 2 = 0 + 0.381 711 006 164 297 459 870 518 476 8;
  • 45) 0.381 711 006 164 297 459 870 518 476 8 × 2 = 0 + 0.763 422 012 328 594 919 741 036 953 6;
  • 46) 0.763 422 012 328 594 919 741 036 953 6 × 2 = 1 + 0.526 844 024 657 189 839 482 073 907 2;
  • 47) 0.526 844 024 657 189 839 482 073 907 2 × 2 = 1 + 0.053 688 049 314 379 678 964 147 814 4;
  • 48) 0.053 688 049 314 379 678 964 147 814 4 × 2 = 0 + 0.107 376 098 628 759 357 928 295 628 8;
  • 49) 0.107 376 098 628 759 357 928 295 628 8 × 2 = 0 + 0.214 752 197 257 518 715 856 591 257 6;
  • 50) 0.214 752 197 257 518 715 856 591 257 6 × 2 = 0 + 0.429 504 394 515 037 431 713 182 515 2;
  • 51) 0.429 504 394 515 037 431 713 182 515 2 × 2 = 0 + 0.859 008 789 030 074 863 426 365 030 4;
  • 52) 0.859 008 789 030 074 863 426 365 030 4 × 2 = 1 + 0.718 017 578 060 149 726 852 730 060 8;
  • 53) 0.718 017 578 060 149 726 852 730 060 8 × 2 = 1 + 0.436 035 156 120 299 453 705 460 121 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:


0.211 829 052 383 358 300 119 548 647 3(10) =


0.0011 0110 0011 1010 0110 1101 1100 0100 0101 0100 0100 0110 0001 1(2)

6. Positive number before normalization:

2.211 829 052 383 358 300 119 548 647 3(10) =


10.0011 0110 0011 1010 0110 1101 1100 0100 0101 0100 0100 0110 0001 1(2)

7. 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:


2.211 829 052 383 358 300 119 548 647 3(10) =


10.0011 0110 0011 1010 0110 1101 1100 0100 0101 0100 0100 0110 0001 1(2) =


10.0011 0110 0011 1010 0110 1101 1100 0100 0101 0100 0100 0110 0001 1(2) × 20 =


1.0001 1011 0001 1101 0011 0110 1110 0010 0010 1010 0010 0011 0000 11(2) × 21


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): 1


Mantissa (not normalized):
1.0001 1011 0001 1101 0011 0110 1110 0010 0010 1010 0010 0011 0000 11


9. 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)


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;
  • 1 024 ÷ 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;

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) =


1024(10) =


100 0000 0000(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. 0001 1011 0001 1101 0011 0110 1110 0010 0010 1010 0010 0011 0000 11 =


0001 1011 0001 1101 0011 0110 1110 0010 0010 1010 0010 0011 0000


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 0000


Mantissa (52 bits) =
0001 1011 0001 1101 0011 0110 1110 0010 0010 1010 0010 0011 0000


Decimal number -2.211 829 052 383 358 300 119 548 647 3 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 100 0000 0000 - 0001 1011 0001 1101 0011 0110 1110 0010 0010 1010 0010 0011 0000


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