1 963 141 111 211 218 337 Converted to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 1 963 141 111 211 218 337(10) to 32 bit single precision IEEE 754 binary floating point representation standard (1 bit for sign, 8 bits for exponent, 23 bits for mantissa)

What are the steps to convert decimal number
1 963 141 111 211 218 337(10) to 32 bit single precision IEEE 754 binary floating point representation (1 bit for sign, 8 bits for exponent, 23 bits for mantissa)

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;
  • 1 963 141 111 211 218 337 ÷ 2 = 981 570 555 605 609 168 + 1;
  • 981 570 555 605 609 168 ÷ 2 = 490 785 277 802 804 584 + 0;
  • 490 785 277 802 804 584 ÷ 2 = 245 392 638 901 402 292 + 0;
  • 245 392 638 901 402 292 ÷ 2 = 122 696 319 450 701 146 + 0;
  • 122 696 319 450 701 146 ÷ 2 = 61 348 159 725 350 573 + 0;
  • 61 348 159 725 350 573 ÷ 2 = 30 674 079 862 675 286 + 1;
  • 30 674 079 862 675 286 ÷ 2 = 15 337 039 931 337 643 + 0;
  • 15 337 039 931 337 643 ÷ 2 = 7 668 519 965 668 821 + 1;
  • 7 668 519 965 668 821 ÷ 2 = 3 834 259 982 834 410 + 1;
  • 3 834 259 982 834 410 ÷ 2 = 1 917 129 991 417 205 + 0;
  • 1 917 129 991 417 205 ÷ 2 = 958 564 995 708 602 + 1;
  • 958 564 995 708 602 ÷ 2 = 479 282 497 854 301 + 0;
  • 479 282 497 854 301 ÷ 2 = 239 641 248 927 150 + 1;
  • 239 641 248 927 150 ÷ 2 = 119 820 624 463 575 + 0;
  • 119 820 624 463 575 ÷ 2 = 59 910 312 231 787 + 1;
  • 59 910 312 231 787 ÷ 2 = 29 955 156 115 893 + 1;
  • 29 955 156 115 893 ÷ 2 = 14 977 578 057 946 + 1;
  • 14 977 578 057 946 ÷ 2 = 7 488 789 028 973 + 0;
  • 7 488 789 028 973 ÷ 2 = 3 744 394 514 486 + 1;
  • 3 744 394 514 486 ÷ 2 = 1 872 197 257 243 + 0;
  • 1 872 197 257 243 ÷ 2 = 936 098 628 621 + 1;
  • 936 098 628 621 ÷ 2 = 468 049 314 310 + 1;
  • 468 049 314 310 ÷ 2 = 234 024 657 155 + 0;
  • 234 024 657 155 ÷ 2 = 117 012 328 577 + 1;
  • 117 012 328 577 ÷ 2 = 58 506 164 288 + 1;
  • 58 506 164 288 ÷ 2 = 29 253 082 144 + 0;
  • 29 253 082 144 ÷ 2 = 14 626 541 072 + 0;
  • 14 626 541 072 ÷ 2 = 7 313 270 536 + 0;
  • 7 313 270 536 ÷ 2 = 3 656 635 268 + 0;
  • 3 656 635 268 ÷ 2 = 1 828 317 634 + 0;
  • 1 828 317 634 ÷ 2 = 914 158 817 + 0;
  • 914 158 817 ÷ 2 = 457 079 408 + 1;
  • 457 079 408 ÷ 2 = 228 539 704 + 0;
  • 228 539 704 ÷ 2 = 114 269 852 + 0;
  • 114 269 852 ÷ 2 = 57 134 926 + 0;
  • 57 134 926 ÷ 2 = 28 567 463 + 0;
  • 28 567 463 ÷ 2 = 14 283 731 + 1;
  • 14 283 731 ÷ 2 = 7 141 865 + 1;
  • 7 141 865 ÷ 2 = 3 570 932 + 1;
  • 3 570 932 ÷ 2 = 1 785 466 + 0;
  • 1 785 466 ÷ 2 = 892 733 + 0;
  • 892 733 ÷ 2 = 446 366 + 1;
  • 446 366 ÷ 2 = 223 183 + 0;
  • 223 183 ÷ 2 = 111 591 + 1;
  • 111 591 ÷ 2 = 55 795 + 1;
  • 55 795 ÷ 2 = 27 897 + 1;
  • 27 897 ÷ 2 = 13 948 + 1;
  • 13 948 ÷ 2 = 6 974 + 0;
  • 6 974 ÷ 2 = 3 487 + 0;
  • 3 487 ÷ 2 = 1 743 + 1;
  • 1 743 ÷ 2 = 871 + 1;
  • 871 ÷ 2 = 435 + 1;
  • 435 ÷ 2 = 217 + 1;
  • 217 ÷ 2 = 108 + 1;
  • 108 ÷ 2 = 54 + 0;
  • 54 ÷ 2 = 27 + 0;
  • 27 ÷ 2 = 13 + 1;
  • 13 ÷ 2 = 6 + 1;
  • 6 ÷ 2 = 3 + 0;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

2. Construct the base 2 representation of the positive number.

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

1 963 141 111 211 218 337(10) =


1 1011 0011 1110 0111 1010 0111 0000 1000 0001 1011 0101 1101 0101 1010 0001(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 60 positions to the left, so that only one non zero digit remains to the left of it:


1 963 141 111 211 218 337(10) =


1 1011 0011 1110 0111 1010 0111 0000 1000 0001 1011 0101 1101 0101 1010 0001(2) =


1 1011 0011 1110 0111 1010 0111 0000 1000 0001 1011 0101 1101 0101 1010 0001(2) × 20 =


1.1011 0011 1110 0111 1010 0111 0000 1000 0001 1011 0101 1101 0101 1010 0001(2) × 260


4. Up to this moment, there are the following elements that would feed into the 32 bit single precision IEEE 754 binary floating point representation:

Sign 0 (a positive number)


Exponent (unadjusted): 60


Mantissa (not normalized):
1.1011 0011 1110 0111 1010 0111 0000 1000 0001 1011 0101 1101 0101 1010 0001


5. Adjust the exponent.

Use the 8 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(8-1) - 1 =


60 + 2(8-1) - 1 =


(60 + 127)(10) =


187(10)


6. Convert the adjusted exponent from the decimal (base 10) to 8 bit binary.

Use the same technique of repeatedly dividing by 2:


  • division = quotient + remainder;
  • 187 ÷ 2 = 93 + 1;
  • 93 ÷ 2 = 46 + 1;
  • 46 ÷ 2 = 23 + 0;
  • 23 ÷ 2 = 11 + 1;
  • 11 ÷ 2 = 5 + 1;
  • 5 ÷ 2 = 2 + 1;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

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

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


Exponent (adjusted) =


187(10) =


1011 1011(2)


8. 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 23 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. 101 1001 1111 0011 1101 0011 1 0000 1000 0001 1011 0101 1101 0101 1010 0001 =


101 1001 1111 0011 1101 0011


9. The three elements that make up the number's 32 bit single precision IEEE 754 binary floating point representation:

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


Exponent (8 bits) =
1011 1011


Mantissa (23 bits) =
101 1001 1111 0011 1101 0011


Decimal number 1 963 141 111 211 218 337 converted to 32 bit single precision IEEE 754 binary floating point representation:

0 - 1011 1011 - 101 1001 1111 0011 1101 0011


How to convert decimal numbers from base ten to 32 bit single precision IEEE 754 binary floating point standard

Follow the steps below to convert a base 10 decimal number to 32 bit single 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 base ten 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 of the previous dividing 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 previous multiplying operations, starting from the top of the constructed list 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, by shifting the decimal point (or if you prefer, the decimal mark) "n" positions either to the left or to the right, so that only one non zero digit remains to the left of the decimal point.
  • 7. Adjust the exponent in 8 bit excess/bias notation and then convert it from decimal (base 10) to 8 bit binary, by using the same technique of repeatedly dividing by 2, as shown above:
    Exponent (adjusted) = Exponent (unadjusted) + 2(8-1) - 1
  • 8. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal sign if the case) and adjust its length to 23 bits, either by removing the excess bits from the right (losing precision...) or by adding extra '0' bits 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 -25.347 from decimal system (base ten) to 32 bit single precision IEEE 754 binary floating point:

  • 1. Start with the positive version of the number:

    |-25.347| = 25.347

  • 2. First convert the integer part, 25. Divide it repeatedly by 2, keeping track of each remainder, until we get a quotient that is equal to zero:
    • division = quotient + remainder;
    • 25 ÷ 2 = 12 + 1;
    • 12 ÷ 2 = 6 + 0;
    • 6 ÷ 2 = 3 + 0;
    • 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:

    25(10) = 1 1001(2)

  • 4. Then convert the fractional part, 0.347. 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) 0.347 × 2 = 0 + 0.694;
    • 2) 0.694 × 2 = 1 + 0.388;
    • 3) 0.388 × 2 = 0 + 0.776;
    • 4) 0.776 × 2 = 1 + 0.552;
    • 5) 0.552 × 2 = 1 + 0.104;
    • 6) 0.104 × 2 = 0 + 0.208;
    • 7) 0.208 × 2 = 0 + 0.416;
    • 8) 0.416 × 2 = 0 + 0.832;
    • 9) 0.832 × 2 = 1 + 0.664;
    • 10) 0.664 × 2 = 1 + 0.328;
    • 11) 0.328 × 2 = 0 + 0.656;
    • 12) 0.656 × 2 = 1 + 0.312;
    • 13) 0.312 × 2 = 0 + 0.624;
    • 14) 0.624 × 2 = 1 + 0.248;
    • 15) 0.248 × 2 = 0 + 0.496;
    • 16) 0.496 × 2 = 0 + 0.992;
    • 17) 0.992 × 2 = 1 + 0.984;
    • 18) 0.984 × 2 = 1 + 0.968;
    • 19) 0.968 × 2 = 1 + 0.936;
    • 20) 0.936 × 2 = 1 + 0.872;
    • 21) 0.872 × 2 = 1 + 0.744;
    • 22) 0.744 × 2 = 1 + 0.488;
    • 23) 0.488 × 2 = 0 + 0.976;
    • 24) 0.976 × 2 = 1 + 0.952;
    • We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit = 23) 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:

    0.347(10) = 0.0101 1000 1101 0100 1111 1101(2)

  • 6. Summarizing - the positive number before normalization:

    25.347(10) = 1 1001.0101 1000 1101 0100 1111 1101(2)

  • 7. Normalize the binary representation of the number, shifting the decimal point 4 positions to the left so that only one non-zero digit stays to the left of the decimal point:

    25.347(10) =
    1 1001.0101 1000 1101 0100 1111 1101(2) =
    1 1001.0101 1000 1101 0100 1111 1101(2) × 20 =
    1.1001 0101 1000 1101 0100 1111 1101(2) × 24

  • 8. Up to this moment, there are the following elements that would feed into the 32 bit single precision IEEE 754 binary floating point:

    Sign: 1 (a negative number)

    Exponent (unadjusted): 4

    Mantissa (not-normalized): 1.1001 0101 1000 1101 0100 1111 1101

  • 9. Adjust the exponent in 8 bit excess/bias notation and then convert it from decimal (base 10) to 8 bit binary (base 2), by using the same technique of repeatedly dividing it by 2, as already demonstrated above:

    Exponent (adjusted) = Exponent (unadjusted) + 2(8-1) - 1 = (4 + 127)(10) = 131(10) =
    1000 0011(2)

  • 10. Normalize the mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal point) and adjust its length to 23 bits, by removing the excess bits from the right (losing precision...):

    Mantissa (not-normalized): 1.1001 0101 1000 1101 0100 1111 1101

    Mantissa (normalized): 100 1010 1100 0110 1010 0111

  • Conclusion:

    Sign (1 bit) = 1 (a negative number)

    Exponent (8 bits) = 1000 0011

    Mantissa (23 bits) = 100 1010 1100 0110 1010 0111

  • Number -25.347, converted from the decimal system (base 10) to 32 bit single precision IEEE 754 binary floating point =
    1 - 1000 0011 - 100 1010 1100 0110 1010 0111