Essay about Numerical Precision

1246 Words Feb 18th, 2014 5 Pages
Numerical Precision

by

John Nelems

Professor Lu

CIS512

Strayer University

January 26th, 2014

Floating Point Format for storing floating numbers in memory
Numeric precision and representation are very familiar discussions in computer science. The way that numbers are stored and represented in a computer system has to be represented correctly in order to avoid costly mistakes. Numbers are stored as binary numbers in computerized system.
Floating point numbers are expressed as the product of two parts: the mantissa and a power of two. For example: ± mantissa x 2 exponent
The mantissa represents the binary digits of the floating number. The power of two is represented by the exponent. The stored form of the exponent
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In other words, the information is encoded as a sequence of 1’s and 0’s. The memory is organized into 8-bit bytes on most computers. The 8- bit byte will be stored in memory and will have a separate address. Precision is what is used to express values which are represented in alternatives, decimal digits, bytes, or binary bits.
Determine if the BCD format is more or less memory efficient than the floating point format
Binary Coded Decimal format is a type of format that is used to simplify devices that use decimal numbers. The numbers are coded in a binary format. The BCD value is an unassigned 8- bit integer, with a range of 0 to 9. In contrast, the floating point format is a method used to store and calculate numbers in which the decimal points do not line up as in fixed numbers. Therefore, I think that in regards to which format is memory efficient would be Binary Coded Decimal because it can accurately represent numbers assuming that there are enough bytes to store the number. Floating Point formats can’t accurately represent that number but only provide an approximation.
Compare and contrast the BCD format to the floating point format in terms of: precision, performance in calculation, and memory usage. The binary coded decimal format precision uses the IEEE 754 and how they are in a format of single, double, double extended and quadruple formats that can accurately

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