Related concepts (6)
Cache control instruction
In computing, a cache control instruction is a hint embedded in the instruction stream of a processor intended to improve the performance of hardware caches, using foreknowledge of the memory access pattern supplied by the programmer or compiler. They may reduce cache pollution, reduce bandwidth requirement, bypass latencies, by providing better control over the working set. Most cache control instructions do not affect the semantics of a program, although some can.
Glossary of computer graphics
This is a glossary of terms relating to computer graphics. For more general computer hardware terms, see glossary of computer hardware terms.
Glossary of computer hardware terms
This glossary of computer hardware terms is a list of definitions of terms and concepts related to computer hardware, i.e. the physical and structural components of computers, architectural issues, and peripheral devices.
Texture mapping
Texture mapping is a method for mapping a texture on a . Texture here can be high frequency detail, surface texture, or color. The original technique was pioneered by Edwin Catmull in 1974. Texture mapping originally referred to diffuse mapping, a method that simply mapped pixels from a texture to a 3D surface ("wrapping" the image around the object).
Cache (computing)
In computing, a cache (kæʃ ) is a hardware or software component that stores data so that future requests for that data can be served faster; the data stored in a cache might be the result of an earlier computation or a copy of data stored elsewhere. A cache hit occurs when the requested data can be found in a cache, while a cache miss occurs when it cannot. Cache hits are served by reading data from the cache, which is faster than recomputing a result or reading from a slower data store; thus, the more requests that can be served from the cache, the faster the system performs.
Parallel computing
Parallel computing is a type of computation in which many calculations or processes are carried out simultaneously. Large problems can often be divided into smaller ones, which can then be solved at the same time. There are several different forms of parallel computing: bit-level, instruction-level, data, and task parallelism. Parallelism has long been employed in high-performance computing, but has gained broader interest due to the physical constraints preventing frequency scaling.

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