Understanding Floating-Point Values - Developer Help

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I would actually opt for integral mantissa/exponent representation of floats/doubles – i.e. at the earliest opportunity, convert the float/double to a pair of integers and then transmit that. You then only have to worry about the portability of integers and well, various routines (such as the hton() routines to handle conversions for you). If you notice in the mantissa there is the repeating pattern 0011. 1/10 in binary is like 1/3 in decimal. It goes on forever. So to retrieve the values from the 32-bit single precision floating point value we must first convert the exponent and mantissa to decimal numbers so we can use them. sign = 0 = a positive number. exponent: 01111111 = 127 After converting 36 into binary, we get the result as 100100 . Step 2 - Convert the mantissa part to binary . Multiply the exponent part by 2 ; If the resulting product is a whole number, that is About the Decimal to Floating-Point Converter. This is a decimal to binary floating-point converter. It will convert a decimal number to its nearest single-precision and double-precision IEEE 754 binary floating-point number, using round-half-to-even rounding (the default IEEE rounding mode). The interface can then have several implementations and you can test your options. As said before, obvious options would be: IEEE754 which writes / reads the binary chunk if directly supported by the architecture or parses it if not supported by the architecture; Text: always needs to parse. Whatever you else you can think of.

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