9 182 344 890 109 280 342 Converted to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 9 182 344 890 109 280 342(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
9 182 344 890 109 280 342(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;
  • 9 182 344 890 109 280 342 ÷ 2 = 4 591 172 445 054 640 171 + 0;
  • 4 591 172 445 054 640 171 ÷ 2 = 2 295 586 222 527 320 085 + 1;
  • 2 295 586 222 527 320 085 ÷ 2 = 1 147 793 111 263 660 042 + 1;
  • 1 147 793 111 263 660 042 ÷ 2 = 573 896 555 631 830 021 + 0;
  • 573 896 555 631 830 021 ÷ 2 = 286 948 277 815 915 010 + 1;
  • 286 948 277 815 915 010 ÷ 2 = 143 474 138 907 957 505 + 0;
  • 143 474 138 907 957 505 ÷ 2 = 71 737 069 453 978 752 + 1;
  • 71 737 069 453 978 752 ÷ 2 = 35 868 534 726 989 376 + 0;
  • 35 868 534 726 989 376 ÷ 2 = 17 934 267 363 494 688 + 0;
  • 17 934 267 363 494 688 ÷ 2 = 8 967 133 681 747 344 + 0;
  • 8 967 133 681 747 344 ÷ 2 = 4 483 566 840 873 672 + 0;
  • 4 483 566 840 873 672 ÷ 2 = 2 241 783 420 436 836 + 0;
  • 2 241 783 420 436 836 ÷ 2 = 1 120 891 710 218 418 + 0;
  • 1 120 891 710 218 418 ÷ 2 = 560 445 855 109 209 + 0;
  • 560 445 855 109 209 ÷ 2 = 280 222 927 554 604 + 1;
  • 280 222 927 554 604 ÷ 2 = 140 111 463 777 302 + 0;
  • 140 111 463 777 302 ÷ 2 = 70 055 731 888 651 + 0;
  • 70 055 731 888 651 ÷ 2 = 35 027 865 944 325 + 1;
  • 35 027 865 944 325 ÷ 2 = 17 513 932 972 162 + 1;
  • 17 513 932 972 162 ÷ 2 = 8 756 966 486 081 + 0;
  • 8 756 966 486 081 ÷ 2 = 4 378 483 243 040 + 1;
  • 4 378 483 243 040 ÷ 2 = 2 189 241 621 520 + 0;
  • 2 189 241 621 520 ÷ 2 = 1 094 620 810 760 + 0;
  • 1 094 620 810 760 ÷ 2 = 547 310 405 380 + 0;
  • 547 310 405 380 ÷ 2 = 273 655 202 690 + 0;
  • 273 655 202 690 ÷ 2 = 136 827 601 345 + 0;
  • 136 827 601 345 ÷ 2 = 68 413 800 672 + 1;
  • 68 413 800 672 ÷ 2 = 34 206 900 336 + 0;
  • 34 206 900 336 ÷ 2 = 17 103 450 168 + 0;
  • 17 103 450 168 ÷ 2 = 8 551 725 084 + 0;
  • 8 551 725 084 ÷ 2 = 4 275 862 542 + 0;
  • 4 275 862 542 ÷ 2 = 2 137 931 271 + 0;
  • 2 137 931 271 ÷ 2 = 1 068 965 635 + 1;
  • 1 068 965 635 ÷ 2 = 534 482 817 + 1;
  • 534 482 817 ÷ 2 = 267 241 408 + 1;
  • 267 241 408 ÷ 2 = 133 620 704 + 0;
  • 133 620 704 ÷ 2 = 66 810 352 + 0;
  • 66 810 352 ÷ 2 = 33 405 176 + 0;
  • 33 405 176 ÷ 2 = 16 702 588 + 0;
  • 16 702 588 ÷ 2 = 8 351 294 + 0;
  • 8 351 294 ÷ 2 = 4 175 647 + 0;
  • 4 175 647 ÷ 2 = 2 087 823 + 1;
  • 2 087 823 ÷ 2 = 1 043 911 + 1;
  • 1 043 911 ÷ 2 = 521 955 + 1;
  • 521 955 ÷ 2 = 260 977 + 1;
  • 260 977 ÷ 2 = 130 488 + 1;
  • 130 488 ÷ 2 = 65 244 + 0;
  • 65 244 ÷ 2 = 32 622 + 0;
  • 32 622 ÷ 2 = 16 311 + 0;
  • 16 311 ÷ 2 = 8 155 + 1;
  • 8 155 ÷ 2 = 4 077 + 1;
  • 4 077 ÷ 2 = 2 038 + 1;
  • 2 038 ÷ 2 = 1 019 + 0;
  • 1 019 ÷ 2 = 509 + 1;
  • 509 ÷ 2 = 254 + 1;
  • 254 ÷ 2 = 127 + 0;
  • 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;

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

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

9 182 344 890 109 280 342(10) =


111 1111 0110 1110 0011 1110 0000 0111 0000 0100 0001 0110 0100 0000 0101 0110(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 62 positions to the left, so that only one non zero digit remains to the left of it:


9 182 344 890 109 280 342(10) =


111 1111 0110 1110 0011 1110 0000 0111 0000 0100 0001 0110 0100 0000 0101 0110(2) =


111 1111 0110 1110 0011 1110 0000 0111 0000 0100 0001 0110 0100 0000 0101 0110(2) × 20 =


1.1111 1101 1011 1000 1111 1000 0001 1100 0001 0000 0101 1001 0000 0001 0101 10(2) × 262


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): 62


Mantissa (not normalized):
1.1111 1101 1011 1000 1111 1000 0001 1100 0001 0000 0101 1001 0000 0001 0101 10


5. Adjust the exponent.

Use the 8 bit excess/bias notation:


Exponent (adjusted) =


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


62 + 2(8-1) - 1 =


(62 + 127)(10) =


189(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;
  • 189 ÷ 2 = 94 + 1;
  • 94 ÷ 2 = 47 + 0;
  • 47 ÷ 2 = 23 + 1;
  • 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) =


189(10) =


1011 1101(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. 111 1110 1101 1100 0111 1100 000 0111 0000 0100 0001 0110 0100 0000 0101 0110 =


111 1110 1101 1100 0111 1100


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 1101


Mantissa (23 bits) =
111 1110 1101 1100 0111 1100


Decimal number 9 182 344 890 109 280 342 converted to 32 bit single precision IEEE 754 binary floating point representation:

0 - 1011 1101 - 111 1110 1101 1100 0111 1100


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