9 439 544 819 036 717 600 Converted to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 9 439 544 819 036 717 600(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
9 439 544 819 036 717 600(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;
  • 9 439 544 819 036 717 600 ÷ 2 = 4 719 772 409 518 358 800 + 0;
  • 4 719 772 409 518 358 800 ÷ 2 = 2 359 886 204 759 179 400 + 0;
  • 2 359 886 204 759 179 400 ÷ 2 = 1 179 943 102 379 589 700 + 0;
  • 1 179 943 102 379 589 700 ÷ 2 = 589 971 551 189 794 850 + 0;
  • 589 971 551 189 794 850 ÷ 2 = 294 985 775 594 897 425 + 0;
  • 294 985 775 594 897 425 ÷ 2 = 147 492 887 797 448 712 + 1;
  • 147 492 887 797 448 712 ÷ 2 = 73 746 443 898 724 356 + 0;
  • 73 746 443 898 724 356 ÷ 2 = 36 873 221 949 362 178 + 0;
  • 36 873 221 949 362 178 ÷ 2 = 18 436 610 974 681 089 + 0;
  • 18 436 610 974 681 089 ÷ 2 = 9 218 305 487 340 544 + 1;
  • 9 218 305 487 340 544 ÷ 2 = 4 609 152 743 670 272 + 0;
  • 4 609 152 743 670 272 ÷ 2 = 2 304 576 371 835 136 + 0;
  • 2 304 576 371 835 136 ÷ 2 = 1 152 288 185 917 568 + 0;
  • 1 152 288 185 917 568 ÷ 2 = 576 144 092 958 784 + 0;
  • 576 144 092 958 784 ÷ 2 = 288 072 046 479 392 + 0;
  • 288 072 046 479 392 ÷ 2 = 144 036 023 239 696 + 0;
  • 144 036 023 239 696 ÷ 2 = 72 018 011 619 848 + 0;
  • 72 018 011 619 848 ÷ 2 = 36 009 005 809 924 + 0;
  • 36 009 005 809 924 ÷ 2 = 18 004 502 904 962 + 0;
  • 18 004 502 904 962 ÷ 2 = 9 002 251 452 481 + 0;
  • 9 002 251 452 481 ÷ 2 = 4 501 125 726 240 + 1;
  • 4 501 125 726 240 ÷ 2 = 2 250 562 863 120 + 0;
  • 2 250 562 863 120 ÷ 2 = 1 125 281 431 560 + 0;
  • 1 125 281 431 560 ÷ 2 = 562 640 715 780 + 0;
  • 562 640 715 780 ÷ 2 = 281 320 357 890 + 0;
  • 281 320 357 890 ÷ 2 = 140 660 178 945 + 0;
  • 140 660 178 945 ÷ 2 = 70 330 089 472 + 1;
  • 70 330 089 472 ÷ 2 = 35 165 044 736 + 0;
  • 35 165 044 736 ÷ 2 = 17 582 522 368 + 0;
  • 17 582 522 368 ÷ 2 = 8 791 261 184 + 0;
  • 8 791 261 184 ÷ 2 = 4 395 630 592 + 0;
  • 4 395 630 592 ÷ 2 = 2 197 815 296 + 0;
  • 2 197 815 296 ÷ 2 = 1 098 907 648 + 0;
  • 1 098 907 648 ÷ 2 = 549 453 824 + 0;
  • 549 453 824 ÷ 2 = 274 726 912 + 0;
  • 274 726 912 ÷ 2 = 137 363 456 + 0;
  • 137 363 456 ÷ 2 = 68 681 728 + 0;
  • 68 681 728 ÷ 2 = 34 340 864 + 0;
  • 34 340 864 ÷ 2 = 17 170 432 + 0;
  • 17 170 432 ÷ 2 = 8 585 216 + 0;
  • 8 585 216 ÷ 2 = 4 292 608 + 0;
  • 4 292 608 ÷ 2 = 2 146 304 + 0;
  • 2 146 304 ÷ 2 = 1 073 152 + 0;
  • 1 073 152 ÷ 2 = 536 576 + 0;
  • 536 576 ÷ 2 = 268 288 + 0;
  • 268 288 ÷ 2 = 134 144 + 0;
  • 134 144 ÷ 2 = 67 072 + 0;
  • 67 072 ÷ 2 = 33 536 + 0;
  • 33 536 ÷ 2 = 16 768 + 0;
  • 16 768 ÷ 2 = 8 384 + 0;
  • 8 384 ÷ 2 = 4 192 + 0;
  • 4 192 ÷ 2 = 2 096 + 0;
  • 2 096 ÷ 2 = 1 048 + 0;
  • 1 048 ÷ 2 = 524 + 0;
  • 524 ÷ 2 = 262 + 0;
  • 262 ÷ 2 = 131 + 0;
  • 131 ÷ 2 = 65 + 1;
  • 65 ÷ 2 = 32 + 1;
  • 32 ÷ 2 = 16 + 0;
  • 16 ÷ 2 = 8 + 0;
  • 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.

9 439 544 819 036 717 600(10) =


1000 0011 0000 0000 0000 0000 0000 0000 0000 0100 0001 0000 0000 0010 0010 0000(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 63 positions to the left, so that only one non zero digit remains to the left of it:


9 439 544 819 036 717 600(10) =


1000 0011 0000 0000 0000 0000 0000 0000 0000 0100 0001 0000 0000 0010 0010 0000(2) =


1000 0011 0000 0000 0000 0000 0000 0000 0000 0100 0001 0000 0000 0010 0010 0000(2) × 20 =


1.0000 0110 0000 0000 0000 0000 0000 0000 0000 1000 0010 0000 0000 0100 0100 000(2) × 263


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): 63


Mantissa (not normalized):
1.0000 0110 0000 0000 0000 0000 0000 0000 0000 1000 0010 0000 0000 0100 0100 000


5. Adjust the exponent.

Use the 8 bit excess/bias notation:


Exponent (adjusted) =


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


63 + 2(8-1) - 1 =


(63 + 127)(10) =


190(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;
  • 190 ÷ 2 = 95 + 0;
  • 95 ÷ 2 = 47 + 1;
  • 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) =


190(10) =


1011 1110(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 0011 0000 0000 0000 0000 0000 0000 0000 0100 0001 0000 0000 0010 0010 0000 =


000 0011 0000 0000 0000 0000


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 1110


Mantissa (23 bits) =
000 0011 0000 0000 0000 0000


Decimal number 9 439 544 819 036 717 600 converted to 32 bit single precision IEEE 754 binary floating point representation:

0 - 1011 1110 - 000 0011 0000 0000 0000 0000


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