5.141 339 658 588 347 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 5.141 339 658 588 347(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
5.141 339 658 588 347(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. First, convert to binary (in base 2) the integer part: 5.
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;
  • 5 ÷ 2 = 2 + 1;
  • 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.

5(10) =


101(2)


3. Convert to binary (base 2) the fractional part: 0.141 339 658 588 347.

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) 0.141 339 658 588 347 × 2 = 0 + 0.282 679 317 176 694;
  • 2) 0.282 679 317 176 694 × 2 = 0 + 0.565 358 634 353 388;
  • 3) 0.565 358 634 353 388 × 2 = 1 + 0.130 717 268 706 776;
  • 4) 0.130 717 268 706 776 × 2 = 0 + 0.261 434 537 413 552;
  • 5) 0.261 434 537 413 552 × 2 = 0 + 0.522 869 074 827 104;
  • 6) 0.522 869 074 827 104 × 2 = 1 + 0.045 738 149 654 208;
  • 7) 0.045 738 149 654 208 × 2 = 0 + 0.091 476 299 308 416;
  • 8) 0.091 476 299 308 416 × 2 = 0 + 0.182 952 598 616 832;
  • 9) 0.182 952 598 616 832 × 2 = 0 + 0.365 905 197 233 664;
  • 10) 0.365 905 197 233 664 × 2 = 0 + 0.731 810 394 467 328;
  • 11) 0.731 810 394 467 328 × 2 = 1 + 0.463 620 788 934 656;
  • 12) 0.463 620 788 934 656 × 2 = 0 + 0.927 241 577 869 312;
  • 13) 0.927 241 577 869 312 × 2 = 1 + 0.854 483 155 738 624;
  • 14) 0.854 483 155 738 624 × 2 = 1 + 0.708 966 311 477 248;
  • 15) 0.708 966 311 477 248 × 2 = 1 + 0.417 932 622 954 496;
  • 16) 0.417 932 622 954 496 × 2 = 0 + 0.835 865 245 908 992;
  • 17) 0.835 865 245 908 992 × 2 = 1 + 0.671 730 491 817 984;
  • 18) 0.671 730 491 817 984 × 2 = 1 + 0.343 460 983 635 968;
  • 19) 0.343 460 983 635 968 × 2 = 0 + 0.686 921 967 271 936;
  • 20) 0.686 921 967 271 936 × 2 = 1 + 0.373 843 934 543 872;
  • 21) 0.373 843 934 543 872 × 2 = 0 + 0.747 687 869 087 744;
  • 22) 0.747 687 869 087 744 × 2 = 1 + 0.495 375 738 175 488;
  • 23) 0.495 375 738 175 488 × 2 = 0 + 0.990 751 476 350 976;
  • 24) 0.990 751 476 350 976 × 2 = 1 + 0.981 502 952 701 952;
  • 25) 0.981 502 952 701 952 × 2 = 1 + 0.963 005 905 403 904;
  • 26) 0.963 005 905 403 904 × 2 = 1 + 0.926 011 810 807 808;
  • 27) 0.926 011 810 807 808 × 2 = 1 + 0.852 023 621 615 616;
  • 28) 0.852 023 621 615 616 × 2 = 1 + 0.704 047 243 231 232;
  • 29) 0.704 047 243 231 232 × 2 = 1 + 0.408 094 486 462 464;
  • 30) 0.408 094 486 462 464 × 2 = 0 + 0.816 188 972 924 928;
  • 31) 0.816 188 972 924 928 × 2 = 1 + 0.632 377 945 849 856;
  • 32) 0.632 377 945 849 856 × 2 = 1 + 0.264 755 891 699 712;
  • 33) 0.264 755 891 699 712 × 2 = 0 + 0.529 511 783 399 424;
  • 34) 0.529 511 783 399 424 × 2 = 1 + 0.059 023 566 798 848;
  • 35) 0.059 023 566 798 848 × 2 = 0 + 0.118 047 133 597 696;
  • 36) 0.118 047 133 597 696 × 2 = 0 + 0.236 094 267 195 392;
  • 37) 0.236 094 267 195 392 × 2 = 0 + 0.472 188 534 390 784;
  • 38) 0.472 188 534 390 784 × 2 = 0 + 0.944 377 068 781 568;
  • 39) 0.944 377 068 781 568 × 2 = 1 + 0.888 754 137 563 136;
  • 40) 0.888 754 137 563 136 × 2 = 1 + 0.777 508 275 126 272;
  • 41) 0.777 508 275 126 272 × 2 = 1 + 0.555 016 550 252 544;
  • 42) 0.555 016 550 252 544 × 2 = 1 + 0.110 033 100 505 088;
  • 43) 0.110 033 100 505 088 × 2 = 0 + 0.220 066 201 010 176;
  • 44) 0.220 066 201 010 176 × 2 = 0 + 0.440 132 402 020 352;
  • 45) 0.440 132 402 020 352 × 2 = 0 + 0.880 264 804 040 704;
  • 46) 0.880 264 804 040 704 × 2 = 1 + 0.760 529 608 081 408;
  • 47) 0.760 529 608 081 408 × 2 = 1 + 0.521 059 216 162 816;
  • 48) 0.521 059 216 162 816 × 2 = 1 + 0.042 118 432 325 632;
  • 49) 0.042 118 432 325 632 × 2 = 0 + 0.084 236 864 651 264;
  • 50) 0.084 236 864 651 264 × 2 = 0 + 0.168 473 729 302 528;
  • 51) 0.168 473 729 302 528 × 2 = 0 + 0.336 947 458 605 056;
  • 52) 0.336 947 458 605 056 × 2 = 0 + 0.673 894 917 210 112;
  • 53) 0.673 894 917 210 112 × 2 = 1 + 0.347 789 834 420 224;

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).


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:


0.141 339 658 588 347(10) =


0.0010 0100 0010 1110 1101 0101 1111 1011 0100 0011 1100 0111 0000 1(2)

5. Positive number before normalization:

5.141 339 658 588 347(10) =


101.0010 0100 0010 1110 1101 0101 1111 1011 0100 0011 1100 0111 0000 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 2 positions to the left, so that only one non zero digit remains to the left of it:


5.141 339 658 588 347(10) =


101.0010 0100 0010 1110 1101 0101 1111 1011 0100 0011 1100 0111 0000 1(2) =


101.0010 0100 0010 1110 1101 0101 1111 1011 0100 0011 1100 0111 0000 1(2) × 20 =


1.0100 1001 0000 1011 1011 0101 0111 1110 1101 0000 1111 0001 1100 001(2) × 22


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): 2


Mantissa (not normalized):
1.0100 1001 0000 1011 1011 0101 0111 1110 1101 0000 1111 0001 1100 001


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


2 + 2(11-1) - 1 =


(2 + 1 023)(10) =


1 025(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;
  • 1 025 ÷ 2 = 512 + 1;
  • 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;

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) =


1025(10) =


100 0000 0001(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. 0100 1001 0000 1011 1011 0101 0111 1110 1101 0000 1111 0001 1100 001 =


0100 1001 0000 1011 1011 0101 0111 1110 1101 0000 1111 0001 1100


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 0001


Mantissa (52 bits) =
0100 1001 0000 1011 1011 0101 0111 1110 1101 0000 1111 0001 1100


Decimal number 5.141 339 658 588 347 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0001 - 0100 1001 0000 1011 1011 0101 0111 1110 1101 0000 1111 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