3.141 592 653 689 793 236 83 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 3.141 592 653 689 793 236 83(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
3.141 592 653 689 793 236 83(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: 3.
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;
  • 3 ÷ 2 = 1 + 1;
  • 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.

3(10) =


11(2)


3. Convert to binary (base 2) the fractional part: 0.141 592 653 689 793 236 83.

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) 0.141 592 653 689 793 236 83 × 2 = 0 + 0.283 185 307 379 586 473 66;
  • 2) 0.283 185 307 379 586 473 66 × 2 = 0 + 0.566 370 614 759 172 947 32;
  • 3) 0.566 370 614 759 172 947 32 × 2 = 1 + 0.132 741 229 518 345 894 64;
  • 4) 0.132 741 229 518 345 894 64 × 2 = 0 + 0.265 482 459 036 691 789 28;
  • 5) 0.265 482 459 036 691 789 28 × 2 = 0 + 0.530 964 918 073 383 578 56;
  • 6) 0.530 964 918 073 383 578 56 × 2 = 1 + 0.061 929 836 146 767 157 12;
  • 7) 0.061 929 836 146 767 157 12 × 2 = 0 + 0.123 859 672 293 534 314 24;
  • 8) 0.123 859 672 293 534 314 24 × 2 = 0 + 0.247 719 344 587 068 628 48;
  • 9) 0.247 719 344 587 068 628 48 × 2 = 0 + 0.495 438 689 174 137 256 96;
  • 10) 0.495 438 689 174 137 256 96 × 2 = 0 + 0.990 877 378 348 274 513 92;
  • 11) 0.990 877 378 348 274 513 92 × 2 = 1 + 0.981 754 756 696 549 027 84;
  • 12) 0.981 754 756 696 549 027 84 × 2 = 1 + 0.963 509 513 393 098 055 68;
  • 13) 0.963 509 513 393 098 055 68 × 2 = 1 + 0.927 019 026 786 196 111 36;
  • 14) 0.927 019 026 786 196 111 36 × 2 = 1 + 0.854 038 053 572 392 222 72;
  • 15) 0.854 038 053 572 392 222 72 × 2 = 1 + 0.708 076 107 144 784 445 44;
  • 16) 0.708 076 107 144 784 445 44 × 2 = 1 + 0.416 152 214 289 568 890 88;
  • 17) 0.416 152 214 289 568 890 88 × 2 = 0 + 0.832 304 428 579 137 781 76;
  • 18) 0.832 304 428 579 137 781 76 × 2 = 1 + 0.664 608 857 158 275 563 52;
  • 19) 0.664 608 857 158 275 563 52 × 2 = 1 + 0.329 217 714 316 551 127 04;
  • 20) 0.329 217 714 316 551 127 04 × 2 = 0 + 0.658 435 428 633 102 254 08;
  • 21) 0.658 435 428 633 102 254 08 × 2 = 1 + 0.316 870 857 266 204 508 16;
  • 22) 0.316 870 857 266 204 508 16 × 2 = 0 + 0.633 741 714 532 409 016 32;
  • 23) 0.633 741 714 532 409 016 32 × 2 = 1 + 0.267 483 429 064 818 032 64;
  • 24) 0.267 483 429 064 818 032 64 × 2 = 0 + 0.534 966 858 129 636 065 28;
  • 25) 0.534 966 858 129 636 065 28 × 2 = 1 + 0.069 933 716 259 272 130 56;
  • 26) 0.069 933 716 259 272 130 56 × 2 = 0 + 0.139 867 432 518 544 261 12;
  • 27) 0.139 867 432 518 544 261 12 × 2 = 0 + 0.279 734 865 037 088 522 24;
  • 28) 0.279 734 865 037 088 522 24 × 2 = 0 + 0.559 469 730 074 177 044 48;
  • 29) 0.559 469 730 074 177 044 48 × 2 = 1 + 0.118 939 460 148 354 088 96;
  • 30) 0.118 939 460 148 354 088 96 × 2 = 0 + 0.237 878 920 296 708 177 92;
  • 31) 0.237 878 920 296 708 177 92 × 2 = 0 + 0.475 757 840 593 416 355 84;
  • 32) 0.475 757 840 593 416 355 84 × 2 = 0 + 0.951 515 681 186 832 711 68;
  • 33) 0.951 515 681 186 832 711 68 × 2 = 1 + 0.903 031 362 373 665 423 36;
  • 34) 0.903 031 362 373 665 423 36 × 2 = 1 + 0.806 062 724 747 330 846 72;
  • 35) 0.806 062 724 747 330 846 72 × 2 = 1 + 0.612 125 449 494 661 693 44;
  • 36) 0.612 125 449 494 661 693 44 × 2 = 1 + 0.224 250 898 989 323 386 88;
  • 37) 0.224 250 898 989 323 386 88 × 2 = 0 + 0.448 501 797 978 646 773 76;
  • 38) 0.448 501 797 978 646 773 76 × 2 = 0 + 0.897 003 595 957 293 547 52;
  • 39) 0.897 003 595 957 293 547 52 × 2 = 1 + 0.794 007 191 914 587 095 04;
  • 40) 0.794 007 191 914 587 095 04 × 2 = 1 + 0.588 014 383 829 174 190 08;
  • 41) 0.588 014 383 829 174 190 08 × 2 = 1 + 0.176 028 767 658 348 380 16;
  • 42) 0.176 028 767 658 348 380 16 × 2 = 0 + 0.352 057 535 316 696 760 32;
  • 43) 0.352 057 535 316 696 760 32 × 2 = 0 + 0.704 115 070 633 393 520 64;
  • 44) 0.704 115 070 633 393 520 64 × 2 = 1 + 0.408 230 141 266 787 041 28;
  • 45) 0.408 230 141 266 787 041 28 × 2 = 0 + 0.816 460 282 533 574 082 56;
  • 46) 0.816 460 282 533 574 082 56 × 2 = 1 + 0.632 920 565 067 148 165 12;
  • 47) 0.632 920 565 067 148 165 12 × 2 = 1 + 0.265 841 130 134 296 330 24;
  • 48) 0.265 841 130 134 296 330 24 × 2 = 0 + 0.531 682 260 268 592 660 48;
  • 49) 0.531 682 260 268 592 660 48 × 2 = 1 + 0.063 364 520 537 185 320 96;
  • 50) 0.063 364 520 537 185 320 96 × 2 = 0 + 0.126 729 041 074 370 641 92;
  • 51) 0.126 729 041 074 370 641 92 × 2 = 0 + 0.253 458 082 148 741 283 84;
  • 52) 0.253 458 082 148 741 283 84 × 2 = 0 + 0.506 916 164 297 482 567 68;
  • 53) 0.506 916 164 297 482 567 68 × 2 = 1 + 0.013 832 328 594 965 135 36;

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:


0.141 592 653 689 793 236 83(10) =


0.0010 0100 0011 1111 0110 1010 1000 1000 1111 0011 1001 0110 1000 1(2)

5. Positive number before normalization:

3.141 592 653 689 793 236 83(10) =


11.0010 0100 0011 1111 0110 1010 1000 1000 1111 0011 1001 0110 1000 1(2)

6. 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:


3.141 592 653 689 793 236 83(10) =


11.0010 0100 0011 1111 0110 1010 1000 1000 1111 0011 1001 0110 1000 1(2) =


11.0010 0100 0011 1111 0110 1010 1000 1000 1111 0011 1001 0110 1000 1(2) × 20 =


1.1001 0010 0001 1111 1011 0101 0100 0100 0111 1001 1100 1011 0100 01(2) × 21


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):
1.1001 0010 0001 1111 1011 0101 0100 0100 0111 1001 1100 1011 0100 01


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) =


1 024(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;
  • 1 024 ÷ 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;

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) =


1024(10) =


100 0000 0000(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. 1001 0010 0001 1111 1011 0101 0100 0100 0111 1001 1100 1011 0100 01 =


1001 0010 0001 1111 1011 0101 0100 0100 0111 1001 1100 1011 0100


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 0000


Mantissa (52 bits) =
1001 0010 0001 1111 1011 0101 0100 0100 0111 1001 1100 1011 0100


Decimal number 3.141 592 653 689 793 236 83 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0000 - 1001 0010 0001 1111 1011 0101 0100 0100 0111 1001 1100 1011 0100


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