64bit IEEE 754: Decimal ↗ Double Precision Floating Point Binary: 8.000 976 681 723 843 242 364 Convert the Number to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From a Base Ten Decimal System Number

Number 8.000 976 681 723 843 242 364(10) converted and written in 64 bit double precision IEEE 754 binary floating point representation (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

1. First, convert to binary (in base 2) the integer part: 8.
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;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

2. 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.


8(10) =


1000(2)


3. Convert to binary (base 2) the fractional part: 0.000 976 681 723 843 242 364.

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) 0.000 976 681 723 843 242 364 × 2 = 0 + 0.001 953 363 447 686 484 728;
  • 2) 0.001 953 363 447 686 484 728 × 2 = 0 + 0.003 906 726 895 372 969 456;
  • 3) 0.003 906 726 895 372 969 456 × 2 = 0 + 0.007 813 453 790 745 938 912;
  • 4) 0.007 813 453 790 745 938 912 × 2 = 0 + 0.015 626 907 581 491 877 824;
  • 5) 0.015 626 907 581 491 877 824 × 2 = 0 + 0.031 253 815 162 983 755 648;
  • 6) 0.031 253 815 162 983 755 648 × 2 = 0 + 0.062 507 630 325 967 511 296;
  • 7) 0.062 507 630 325 967 511 296 × 2 = 0 + 0.125 015 260 651 935 022 592;
  • 8) 0.125 015 260 651 935 022 592 × 2 = 0 + 0.250 030 521 303 870 045 184;
  • 9) 0.250 030 521 303 870 045 184 × 2 = 0 + 0.500 061 042 607 740 090 368;
  • 10) 0.500 061 042 607 740 090 368 × 2 = 1 + 0.000 122 085 215 480 180 736;
  • 11) 0.000 122 085 215 480 180 736 × 2 = 0 + 0.000 244 170 430 960 361 472;
  • 12) 0.000 244 170 430 960 361 472 × 2 = 0 + 0.000 488 340 861 920 722 944;
  • 13) 0.000 488 340 861 920 722 944 × 2 = 0 + 0.000 976 681 723 841 445 888;
  • 14) 0.000 976 681 723 841 445 888 × 2 = 0 + 0.001 953 363 447 682 891 776;
  • 15) 0.001 953 363 447 682 891 776 × 2 = 0 + 0.003 906 726 895 365 783 552;
  • 16) 0.003 906 726 895 365 783 552 × 2 = 0 + 0.007 813 453 790 731 567 104;
  • 17) 0.007 813 453 790 731 567 104 × 2 = 0 + 0.015 626 907 581 463 134 208;
  • 18) 0.015 626 907 581 463 134 208 × 2 = 0 + 0.031 253 815 162 926 268 416;
  • 19) 0.031 253 815 162 926 268 416 × 2 = 0 + 0.062 507 630 325 852 536 832;
  • 20) 0.062 507 630 325 852 536 832 × 2 = 0 + 0.125 015 260 651 705 073 664;
  • 21) 0.125 015 260 651 705 073 664 × 2 = 0 + 0.250 030 521 303 410 147 328;
  • 22) 0.250 030 521 303 410 147 328 × 2 = 0 + 0.500 061 042 606 820 294 656;
  • 23) 0.500 061 042 606 820 294 656 × 2 = 1 + 0.000 122 085 213 640 589 312;
  • 24) 0.000 122 085 213 640 589 312 × 2 = 0 + 0.000 244 170 427 281 178 624;
  • 25) 0.000 244 170 427 281 178 624 × 2 = 0 + 0.000 488 340 854 562 357 248;
  • 26) 0.000 488 340 854 562 357 248 × 2 = 0 + 0.000 976 681 709 124 714 496;
  • 27) 0.000 976 681 709 124 714 496 × 2 = 0 + 0.001 953 363 418 249 428 992;
  • 28) 0.001 953 363 418 249 428 992 × 2 = 0 + 0.003 906 726 836 498 857 984;
  • 29) 0.003 906 726 836 498 857 984 × 2 = 0 + 0.007 813 453 672 997 715 968;
  • 30) 0.007 813 453 672 997 715 968 × 2 = 0 + 0.015 626 907 345 995 431 936;
  • 31) 0.015 626 907 345 995 431 936 × 2 = 0 + 0.031 253 814 691 990 863 872;
  • 32) 0.031 253 814 691 990 863 872 × 2 = 0 + 0.062 507 629 383 981 727 744;
  • 33) 0.062 507 629 383 981 727 744 × 2 = 0 + 0.125 015 258 767 963 455 488;
  • 34) 0.125 015 258 767 963 455 488 × 2 = 0 + 0.250 030 517 535 926 910 976;
  • 35) 0.250 030 517 535 926 910 976 × 2 = 0 + 0.500 061 035 071 853 821 952;
  • 36) 0.500 061 035 071 853 821 952 × 2 = 1 + 0.000 122 070 143 707 643 904;
  • 37) 0.000 122 070 143 707 643 904 × 2 = 0 + 0.000 244 140 287 415 287 808;
  • 38) 0.000 244 140 287 415 287 808 × 2 = 0 + 0.000 488 280 574 830 575 616;
  • 39) 0.000 488 280 574 830 575 616 × 2 = 0 + 0.000 976 561 149 661 151 232;
  • 40) 0.000 976 561 149 661 151 232 × 2 = 0 + 0.001 953 122 299 322 302 464;
  • 41) 0.001 953 122 299 322 302 464 × 2 = 0 + 0.003 906 244 598 644 604 928;
  • 42) 0.003 906 244 598 644 604 928 × 2 = 0 + 0.007 812 489 197 289 209 856;
  • 43) 0.007 812 489 197 289 209 856 × 2 = 0 + 0.015 624 978 394 578 419 712;
  • 44) 0.015 624 978 394 578 419 712 × 2 = 0 + 0.031 249 956 789 156 839 424;
  • 45) 0.031 249 956 789 156 839 424 × 2 = 0 + 0.062 499 913 578 313 678 848;
  • 46) 0.062 499 913 578 313 678 848 × 2 = 0 + 0.124 999 827 156 627 357 696;
  • 47) 0.124 999 827 156 627 357 696 × 2 = 0 + 0.249 999 654 313 254 715 392;
  • 48) 0.249 999 654 313 254 715 392 × 2 = 0 + 0.499 999 308 626 509 430 784;
  • 49) 0.499 999 308 626 509 430 784 × 2 = 0 + 0.999 998 617 253 018 861 568;
  • 50) 0.999 998 617 253 018 861 568 × 2 = 1 + 0.999 997 234 506 037 723 136;
  • 51) 0.999 997 234 506 037 723 136 × 2 = 1 + 0.999 994 469 012 075 446 272;
  • 52) 0.999 994 469 012 075 446 272 × 2 = 1 + 0.999 988 938 024 150 892 544;
  • 53) 0.999 988 938 024 150 892 544 × 2 = 1 + 0.999 977 876 048 301 785 088;

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...)


4. 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:


0.000 976 681 723 843 242 364(10) =


0.0000 0000 0100 0000 0000 0010 0000 0000 0001 0000 0000 0000 0111 1(2)


5. Positive number before normalization:

8.000 976 681 723 843 242 364(10) =


1000.0000 0000 0100 0000 0000 0010 0000 0000 0001 0000 0000 0000 0111 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 3 positions to the left, so that only one non zero digit remains to the left of it:


8.000 976 681 723 843 242 364(10) =


1000.0000 0000 0100 0000 0000 0010 0000 0000 0001 0000 0000 0000 0111 1(2) =


1000.0000 0000 0100 0000 0000 0010 0000 0000 0001 0000 0000 0000 0111 1(2) × 20 =


1.0000 0000 0000 1000 0000 0000 0100 0000 0000 0010 0000 0000 0000 1111(2) × 23


7. 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 0 (a positive number)


Exponent (unadjusted): 3


Mantissa (not normalized):
1.0000 0000 0000 1000 0000 0000 0100 0000 0000 0010 0000 0000 0000 1111


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


3 + 2(11-1) - 1 =


(3 + 1 023)(10) =


1 026(10)


9. 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;
  • 1 026 ÷ 2 = 513 + 0;
  • 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;

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

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


Exponent (adjusted) =


1026(10) =


100 0000 0010(2)


11. 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 0000 0000 1000 0000 0000 0100 0000 0000 0010 0000 0000 0000 1111 =


0000 0000 0000 1000 0000 0000 0100 0000 0000 0010 0000 0000 0000


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

Sign (1 bit) =
0 (a positive number)


Exponent (11 bits) =
100 0000 0010


Mantissa (52 bits) =
0000 0000 0000 1000 0000 0000 0100 0000 0000 0010 0000 0000 0000


The base ten decimal number 8.000 976 681 723 843 242 364 converted and written in 64 bit double precision IEEE 754 binary floating point representation:
0 - 100 0000 0010 - 0000 0000 0000 1000 0000 0000 0100 0000 0000 0010 0000 0000 0000

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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