32bit IEEE 754: Decimal ↗ Single Precision Floating Point Binary: 1 245 633 434 354 345 Convert the Number to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard, From a Base 10 Decimal System Number

Number 1 245 633 434 354 345(10) converted and written in 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;
  • 1 245 633 434 354 345 ÷ 2 = 622 816 717 177 172 + 1;
  • 622 816 717 177 172 ÷ 2 = 311 408 358 588 586 + 0;
  • 311 408 358 588 586 ÷ 2 = 155 704 179 294 293 + 0;
  • 155 704 179 294 293 ÷ 2 = 77 852 089 647 146 + 1;
  • 77 852 089 647 146 ÷ 2 = 38 926 044 823 573 + 0;
  • 38 926 044 823 573 ÷ 2 = 19 463 022 411 786 + 1;
  • 19 463 022 411 786 ÷ 2 = 9 731 511 205 893 + 0;
  • 9 731 511 205 893 ÷ 2 = 4 865 755 602 946 + 1;
  • 4 865 755 602 946 ÷ 2 = 2 432 877 801 473 + 0;
  • 2 432 877 801 473 ÷ 2 = 1 216 438 900 736 + 1;
  • 1 216 438 900 736 ÷ 2 = 608 219 450 368 + 0;
  • 608 219 450 368 ÷ 2 = 304 109 725 184 + 0;
  • 304 109 725 184 ÷ 2 = 152 054 862 592 + 0;
  • 152 054 862 592 ÷ 2 = 76 027 431 296 + 0;
  • 76 027 431 296 ÷ 2 = 38 013 715 648 + 0;
  • 38 013 715 648 ÷ 2 = 19 006 857 824 + 0;
  • 19 006 857 824 ÷ 2 = 9 503 428 912 + 0;
  • 9 503 428 912 ÷ 2 = 4 751 714 456 + 0;
  • 4 751 714 456 ÷ 2 = 2 375 857 228 + 0;
  • 2 375 857 228 ÷ 2 = 1 187 928 614 + 0;
  • 1 187 928 614 ÷ 2 = 593 964 307 + 0;
  • 593 964 307 ÷ 2 = 296 982 153 + 1;
  • 296 982 153 ÷ 2 = 148 491 076 + 1;
  • 148 491 076 ÷ 2 = 74 245 538 + 0;
  • 74 245 538 ÷ 2 = 37 122 769 + 0;
  • 37 122 769 ÷ 2 = 18 561 384 + 1;
  • 18 561 384 ÷ 2 = 9 280 692 + 0;
  • 9 280 692 ÷ 2 = 4 640 346 + 0;
  • 4 640 346 ÷ 2 = 2 320 173 + 0;
  • 2 320 173 ÷ 2 = 1 160 086 + 1;
  • 1 160 086 ÷ 2 = 580 043 + 0;
  • 580 043 ÷ 2 = 290 021 + 1;
  • 290 021 ÷ 2 = 145 010 + 1;
  • 145 010 ÷ 2 = 72 505 + 0;
  • 72 505 ÷ 2 = 36 252 + 1;
  • 36 252 ÷ 2 = 18 126 + 0;
  • 18 126 ÷ 2 = 9 063 + 0;
  • 9 063 ÷ 2 = 4 531 + 1;
  • 4 531 ÷ 2 = 2 265 + 1;
  • 2 265 ÷ 2 = 1 132 + 1;
  • 1 132 ÷ 2 = 566 + 0;
  • 566 ÷ 2 = 283 + 0;
  • 283 ÷ 2 = 141 + 1;
  • 141 ÷ 2 = 70 + 1;
  • 70 ÷ 2 = 35 + 0;
  • 35 ÷ 2 = 17 + 1;
  • 17 ÷ 2 = 8 + 1;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 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.


1 245 633 434 354 345(10) =


100 0110 1100 1110 0101 1010 0010 0110 0000 0000 0010 1010 1001(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 50 positions to the left, so that only one non zero digit remains to the left of it:


1 245 633 434 354 345(10) =


100 0110 1100 1110 0101 1010 0010 0110 0000 0000 0010 1010 1001(2) =


100 0110 1100 1110 0101 1010 0010 0110 0000 0000 0010 1010 1001(2) × 20 =


1.0001 1011 0011 1001 0110 1000 1001 1000 0000 0000 1010 1010 01(2) × 250


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): 50


Mantissa (not normalized):
1.0001 1011 0011 1001 0110 1000 1001 1000 0000 0000 1010 1010 01


5. Adjust the exponent.

Use the 8 bit excess/bias notation:


Exponent (adjusted) =


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


50 + 2(8-1) - 1 =


(50 + 127)(10) =


177(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;
  • 177 ÷ 2 = 88 + 1;
  • 88 ÷ 2 = 44 + 0;
  • 44 ÷ 2 = 22 + 0;
  • 22 ÷ 2 = 11 + 0;
  • 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) =


177(10) =


1011 0001(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. 000 1101 1001 1100 1011 0100 010 0110 0000 0000 0010 1010 1001 =


000 1101 1001 1100 1011 0100


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 0001


Mantissa (23 bits) =
000 1101 1001 1100 1011 0100


The base ten decimal number 1 245 633 434 354 345 converted and written in 32 bit single precision IEEE 754 binary floating point representation:
0 - 1011 0001 - 000 1101 1001 1100 1011 0100

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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