1.570 796 326 795 003 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 1.570 796 326 795 003(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
1.570 796 326 795 003(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: 1.
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;
  • 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.

1(10) =


1(2)


3. Convert to binary (base 2) the fractional part: 0.570 796 326 795 003.

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) 0.570 796 326 795 003 × 2 = 1 + 0.141 592 653 590 006;
  • 2) 0.141 592 653 590 006 × 2 = 0 + 0.283 185 307 180 012;
  • 3) 0.283 185 307 180 012 × 2 = 0 + 0.566 370 614 360 024;
  • 4) 0.566 370 614 360 024 × 2 = 1 + 0.132 741 228 720 048;
  • 5) 0.132 741 228 720 048 × 2 = 0 + 0.265 482 457 440 096;
  • 6) 0.265 482 457 440 096 × 2 = 0 + 0.530 964 914 880 192;
  • 7) 0.530 964 914 880 192 × 2 = 1 + 0.061 929 829 760 384;
  • 8) 0.061 929 829 760 384 × 2 = 0 + 0.123 859 659 520 768;
  • 9) 0.123 859 659 520 768 × 2 = 0 + 0.247 719 319 041 536;
  • 10) 0.247 719 319 041 536 × 2 = 0 + 0.495 438 638 083 072;
  • 11) 0.495 438 638 083 072 × 2 = 0 + 0.990 877 276 166 144;
  • 12) 0.990 877 276 166 144 × 2 = 1 + 0.981 754 552 332 288;
  • 13) 0.981 754 552 332 288 × 2 = 1 + 0.963 509 104 664 576;
  • 14) 0.963 509 104 664 576 × 2 = 1 + 0.927 018 209 329 152;
  • 15) 0.927 018 209 329 152 × 2 = 1 + 0.854 036 418 658 304;
  • 16) 0.854 036 418 658 304 × 2 = 1 + 0.708 072 837 316 608;
  • 17) 0.708 072 837 316 608 × 2 = 1 + 0.416 145 674 633 216;
  • 18) 0.416 145 674 633 216 × 2 = 0 + 0.832 291 349 266 432;
  • 19) 0.832 291 349 266 432 × 2 = 1 + 0.664 582 698 532 864;
  • 20) 0.664 582 698 532 864 × 2 = 1 + 0.329 165 397 065 728;
  • 21) 0.329 165 397 065 728 × 2 = 0 + 0.658 330 794 131 456;
  • 22) 0.658 330 794 131 456 × 2 = 1 + 0.316 661 588 262 912;
  • 23) 0.316 661 588 262 912 × 2 = 0 + 0.633 323 176 525 824;
  • 24) 0.633 323 176 525 824 × 2 = 1 + 0.266 646 353 051 648;
  • 25) 0.266 646 353 051 648 × 2 = 0 + 0.533 292 706 103 296;
  • 26) 0.533 292 706 103 296 × 2 = 1 + 0.066 585 412 206 592;
  • 27) 0.066 585 412 206 592 × 2 = 0 + 0.133 170 824 413 184;
  • 28) 0.133 170 824 413 184 × 2 = 0 + 0.266 341 648 826 368;
  • 29) 0.266 341 648 826 368 × 2 = 0 + 0.532 683 297 652 736;
  • 30) 0.532 683 297 652 736 × 2 = 1 + 0.065 366 595 305 472;
  • 31) 0.065 366 595 305 472 × 2 = 0 + 0.130 733 190 610 944;
  • 32) 0.130 733 190 610 944 × 2 = 0 + 0.261 466 381 221 888;
  • 33) 0.261 466 381 221 888 × 2 = 0 + 0.522 932 762 443 776;
  • 34) 0.522 932 762 443 776 × 2 = 1 + 0.045 865 524 887 552;
  • 35) 0.045 865 524 887 552 × 2 = 0 + 0.091 731 049 775 104;
  • 36) 0.091 731 049 775 104 × 2 = 0 + 0.183 462 099 550 208;
  • 37) 0.183 462 099 550 208 × 2 = 0 + 0.366 924 199 100 416;
  • 38) 0.366 924 199 100 416 × 2 = 0 + 0.733 848 398 200 832;
  • 39) 0.733 848 398 200 832 × 2 = 1 + 0.467 696 796 401 664;
  • 40) 0.467 696 796 401 664 × 2 = 0 + 0.935 393 592 803 328;
  • 41) 0.935 393 592 803 328 × 2 = 1 + 0.870 787 185 606 656;
  • 42) 0.870 787 185 606 656 × 2 = 1 + 0.741 574 371 213 312;
  • 43) 0.741 574 371 213 312 × 2 = 1 + 0.483 148 742 426 624;
  • 44) 0.483 148 742 426 624 × 2 = 0 + 0.966 297 484 853 248;
  • 45) 0.966 297 484 853 248 × 2 = 1 + 0.932 594 969 706 496;
  • 46) 0.932 594 969 706 496 × 2 = 1 + 0.865 189 939 412 992;
  • 47) 0.865 189 939 412 992 × 2 = 1 + 0.730 379 878 825 984;
  • 48) 0.730 379 878 825 984 × 2 = 1 + 0.460 759 757 651 968;
  • 49) 0.460 759 757 651 968 × 2 = 0 + 0.921 519 515 303 936;
  • 50) 0.921 519 515 303 936 × 2 = 1 + 0.843 039 030 607 872;
  • 51) 0.843 039 030 607 872 × 2 = 1 + 0.686 078 061 215 744;
  • 52) 0.686 078 061 215 744 × 2 = 1 + 0.372 156 122 431 488;
  • 53) 0.372 156 122 431 488 × 2 = 0 + 0.744 312 244 862 976;

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:


0.570 796 326 795 003(10) =


0.1001 0010 0001 1111 1011 0101 0100 0100 0100 0010 1110 1111 0111 0(2)

5. Positive number before normalization:

1.570 796 326 795 003(10) =


1.1001 0010 0001 1111 1011 0101 0100 0100 0100 0010 1110 1111 0111 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 0 positions to the left, so that only one non zero digit remains to the left of it:


1.570 796 326 795 003(10) =


1.1001 0010 0001 1111 1011 0101 0100 0100 0100 0010 1110 1111 0111 0(2) =


1.1001 0010 0001 1111 1011 0101 0100 0100 0100 0010 1110 1111 0111 0(2) × 20


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): 0


Mantissa (not normalized):
1.1001 0010 0001 1111 1011 0101 0100 0100 0100 0010 1110 1111 0111 0


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


0 + 2(11-1) - 1 =


(0 + 1 023)(10) =


1 023(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;
  • 1 023 ÷ 2 = 511 + 1;
  • 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) =


1023(10) =


011 1111 1111(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 0100 0010 1110 1111 0111 0 =


1001 0010 0001 1111 1011 0101 0100 0100 0100 0010 1110 1111 0111


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 1111


Mantissa (52 bits) =
1001 0010 0001 1111 1011 0101 0100 0100 0100 0010 1110 1111 0111


Decimal number 1.570 796 326 795 003 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 011 1111 1111 - 1001 0010 0001 1111 1011 0101 0100 0100 0100 0010 1110 1111 0111


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