0.974 013 318 541 578 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.974 013 318 541 578(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
0.974 013 318 541 578(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: 0.
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;
  • 0 ÷ 2 = 0 + 0;

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.

0(10) =


0(2)


3. Convert to binary (base 2) the fractional part: 0.974 013 318 541 578.

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) 0.974 013 318 541 578 × 2 = 1 + 0.948 026 637 083 156;
  • 2) 0.948 026 637 083 156 × 2 = 1 + 0.896 053 274 166 312;
  • 3) 0.896 053 274 166 312 × 2 = 1 + 0.792 106 548 332 624;
  • 4) 0.792 106 548 332 624 × 2 = 1 + 0.584 213 096 665 248;
  • 5) 0.584 213 096 665 248 × 2 = 1 + 0.168 426 193 330 496;
  • 6) 0.168 426 193 330 496 × 2 = 0 + 0.336 852 386 660 992;
  • 7) 0.336 852 386 660 992 × 2 = 0 + 0.673 704 773 321 984;
  • 8) 0.673 704 773 321 984 × 2 = 1 + 0.347 409 546 643 968;
  • 9) 0.347 409 546 643 968 × 2 = 0 + 0.694 819 093 287 936;
  • 10) 0.694 819 093 287 936 × 2 = 1 + 0.389 638 186 575 872;
  • 11) 0.389 638 186 575 872 × 2 = 0 + 0.779 276 373 151 744;
  • 12) 0.779 276 373 151 744 × 2 = 1 + 0.558 552 746 303 488;
  • 13) 0.558 552 746 303 488 × 2 = 1 + 0.117 105 492 606 976;
  • 14) 0.117 105 492 606 976 × 2 = 0 + 0.234 210 985 213 952;
  • 15) 0.234 210 985 213 952 × 2 = 0 + 0.468 421 970 427 904;
  • 16) 0.468 421 970 427 904 × 2 = 0 + 0.936 843 940 855 808;
  • 17) 0.936 843 940 855 808 × 2 = 1 + 0.873 687 881 711 616;
  • 18) 0.873 687 881 711 616 × 2 = 1 + 0.747 375 763 423 232;
  • 19) 0.747 375 763 423 232 × 2 = 1 + 0.494 751 526 846 464;
  • 20) 0.494 751 526 846 464 × 2 = 0 + 0.989 503 053 692 928;
  • 21) 0.989 503 053 692 928 × 2 = 1 + 0.979 006 107 385 856;
  • 22) 0.979 006 107 385 856 × 2 = 1 + 0.958 012 214 771 712;
  • 23) 0.958 012 214 771 712 × 2 = 1 + 0.916 024 429 543 424;
  • 24) 0.916 024 429 543 424 × 2 = 1 + 0.832 048 859 086 848;
  • 25) 0.832 048 859 086 848 × 2 = 1 + 0.664 097 718 173 696;
  • 26) 0.664 097 718 173 696 × 2 = 1 + 0.328 195 436 347 392;
  • 27) 0.328 195 436 347 392 × 2 = 0 + 0.656 390 872 694 784;
  • 28) 0.656 390 872 694 784 × 2 = 1 + 0.312 781 745 389 568;
  • 29) 0.312 781 745 389 568 × 2 = 0 + 0.625 563 490 779 136;
  • 30) 0.625 563 490 779 136 × 2 = 1 + 0.251 126 981 558 272;
  • 31) 0.251 126 981 558 272 × 2 = 0 + 0.502 253 963 116 544;
  • 32) 0.502 253 963 116 544 × 2 = 1 + 0.004 507 926 233 088;
  • 33) 0.004 507 926 233 088 × 2 = 0 + 0.009 015 852 466 176;
  • 34) 0.009 015 852 466 176 × 2 = 0 + 0.018 031 704 932 352;
  • 35) 0.018 031 704 932 352 × 2 = 0 + 0.036 063 409 864 704;
  • 36) 0.036 063 409 864 704 × 2 = 0 + 0.072 126 819 729 408;
  • 37) 0.072 126 819 729 408 × 2 = 0 + 0.144 253 639 458 816;
  • 38) 0.144 253 639 458 816 × 2 = 0 + 0.288 507 278 917 632;
  • 39) 0.288 507 278 917 632 × 2 = 0 + 0.577 014 557 835 264;
  • 40) 0.577 014 557 835 264 × 2 = 1 + 0.154 029 115 670 528;
  • 41) 0.154 029 115 670 528 × 2 = 0 + 0.308 058 231 341 056;
  • 42) 0.308 058 231 341 056 × 2 = 0 + 0.616 116 462 682 112;
  • 43) 0.616 116 462 682 112 × 2 = 1 + 0.232 232 925 364 224;
  • 44) 0.232 232 925 364 224 × 2 = 0 + 0.464 465 850 728 448;
  • 45) 0.464 465 850 728 448 × 2 = 0 + 0.928 931 701 456 896;
  • 46) 0.928 931 701 456 896 × 2 = 1 + 0.857 863 402 913 792;
  • 47) 0.857 863 402 913 792 × 2 = 1 + 0.715 726 805 827 584;
  • 48) 0.715 726 805 827 584 × 2 = 1 + 0.431 453 611 655 168;
  • 49) 0.431 453 611 655 168 × 2 = 0 + 0.862 907 223 310 336;
  • 50) 0.862 907 223 310 336 × 2 = 1 + 0.725 814 446 620 672;
  • 51) 0.725 814 446 620 672 × 2 = 1 + 0.451 628 893 241 344;
  • 52) 0.451 628 893 241 344 × 2 = 0 + 0.903 257 786 482 688;
  • 53) 0.903 257 786 482 688 × 2 = 1 + 0.806 515 572 965 376;

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:


0.974 013 318 541 578(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0010 0111 0110 1(2)

5. Positive number before normalization:

0.974 013 318 541 578(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0010 0111 0110 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 1 positions to the right, so that only one non zero digit remains to the left of it:


0.974 013 318 541 578(10) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0010 0111 0110 1(2) =


0.1111 1001 0101 1000 1110 1111 1101 0101 0000 0001 0010 0111 0110 1(2) × 20 =


1.1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 0100 1110 1101(2) × 2-1


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): -1


Mantissa (not normalized):
1.1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 0100 1110 1101


8. 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) =


1 022(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;
  • 1 022 ÷ 2 = 511 + 0;
  • 511 ÷ 2 = 255 + 1;
  • 255 ÷ 2 = 127 + 1;
  • 127 ÷ 2 = 63 + 1;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 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) =


1022(10) =


011 1111 1110(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, only if necessary (not the case here).


Mantissa (normalized) =


1. 1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 0100 1110 1101 =


1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 0100 1110 1101


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) =
011 1111 1110


Mantissa (52 bits) =
1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 0100 1110 1101


Decimal number 0.974 013 318 541 578 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 011 1111 1110 - 1111 0010 1011 0001 1101 1111 1010 1010 0000 0010 0100 1110 1101


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