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On some PowerPC systems, [11] long double is implemented as a double-double arithmetic, where a long double value is regarded as the exact sum of two double-precision values, giving at least a 106-bit precision; with such a format, the long double type does not conform to the IEEE floating-point standard.
Double-precision floating-point format (sometimes called FP64 or float64) is a floating-point number format, usually occupying 64 bits in computer memory; it represents a wide range of numeric values by using a floating radix point. Double precision may be chosen when the range or precision of single precision would be insufficient.
The Java virtual machine's set of primitive data types consists of: [12] byte, short, int, long, char (integer types with a variety of ranges) float and double, floating-point numbers with single and double precisions; boolean, a Boolean type with logical values true and false; returnAddress, a value referring to an executable memory address ...
negate a double drem 73 0111 0011 value1, value2 → result get the remainder from a division between two doubles dreturn af 1010 1111 value → [empty] return a double from a method dstore 39 0011 1001 1: index value → store a double value into a local variable #index: dstore_0 47 0100 0111 value → store a double into local variable 0 dstore_1
Floating-point arithmetic operations are performed by software, and double precision is not supported at all. The extended format occupies three 16-bit words, with the extra space simply ignored. [3] The IBM System/360 supports a 32-bit "short" floating-point format and a 64-bit "long" floating-point format. [4]
If, however, intermediate computations are all performed in extended precision (e.g. by setting line [1] to C99 long double), then up to full precision in the final double result can be maintained. [nb 13] Alternatively, a numerical analysis of the algorithm reveals that if the following non-obvious change to line [2] is made:
Collection classes are Java API-defined classes that can store objects in a manner similar to how data structures like arrays store primitive data types like int, double, long or char, etc., [2] but arrays store primitive data types while collections actually store objects. The primitive wrapper classes and their corresponding primitive types are:
In single precision, the bias is 127, so in this example the biased exponent is 124; in double precision, the bias is 1023, so the biased exponent in this example is 1020. fraction = .01000… 2 . IEEE 754 adds a bias to the exponent so that numbers can in many cases be compared conveniently by the same hardware that compares signed 2's ...