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Unlike the bitset in C++, the Java BitSet does not have a "size" state (it has an effectively infinite size, initialized with 0 bits); a bit can be set or tested at any index. In addition, there is a class EnumSet , which represents a Set of values of an enumerated type internally as a bit vector, as a safer alternative to bit fields.
LZCNT is related to the Bit Scan Reverse (BSR) instruction, but sets the ZF (if the result is zero) and CF (if the source is zero) flags rather than setting the ZF (if the source is zero). Also, it produces a defined result (the source operand size in bits) if the source operand is zero.
The Hamming weight is named after the American mathematician Richard Hamming, although he did not originate the notion. [5] The Hamming weight of binary numbers was already used in 1899 by James W. L. Glaisher to give a formula for the number of odd binomial coefficients in a single row of Pascal's triangle. [6]
In computer software and hardware, find first set (ffs) or find first one is a bit operation that, given an unsigned machine word, [nb 1] designates the index or position of the least significant bit set to one in the word counting from the least significant bit position.
In computer programming, a bitwise operation operates on a bit string, a bit array or a binary numeral (considered as a bit string) at the level of its individual bits.It is a fast and simple action, basic to the higher-level arithmetic operations and directly supported by the processor.
A bit field is distinguished from a bit array in that the latter is used to store a large set of bits indexed by integers and is often wider than any integral type supported by the language. [citation needed] Bit fields, on the other hand, typically fit within a machine word, [3] and the denotation of bits is independent of their numerical ...
PER Aligned: a fixed number of bits if the integer type has a finite range and the size of the range is less than 65536; a variable number of octets otherwise; OER: 1, 2, or 4 octets (either signed or unsigned) if the integer type has a finite range that fits in that number of octets; a variable number of octets otherwise
Amdahl's law applies only to the cases where the problem size is fixed. In practice, as more computing resources become available, they tend to get used on larger problems (larger datasets), and the time spent in the parallelizable part often grows much faster than the inherently serial work.