Data parallelism
Data parallelism - Search results - Wiki Data Parallelism
The page "Data+parallelism" does not exist. You can create a draft and submit it for review or request that a redirect be created, but consider checking the search results below to see whether the topic is already covered.
Data parallelism is parallelization across multiple processors in parallel computing environments. It focuses on distributing the data across different...- parallelism focuses on distributing tasks—concurrently performed by processes or threads—across different processors. In contrast to data parallelism...
- Parallel programming model (section Data parallelism)Flynn's taxonomy, data parallelism is usually classified as MIMD/SPMD or SIMD. Stream parallelism, also known as pipeline parallelism, focuses on dividing...
Central processing unit (section Data parallelism)CPUs devote a lot of semiconductor area to caches and instruction-level parallelism to increase performance and to CPU modes to support operating systems...
Parallel computing (redirect from Computer Parallelism)forms of parallel computing: bit-level, instruction-level, data, and task parallelism. Parallelism has long been employed in high-performance computing, but...- Granularity (parallel computing) (redirect from Fine-grained parallelism)problem-to-problem. Instruction-level parallelism Data Parallelism Hwang, Kai (1992). Advanced Computer Architecture: Parallelism, Scalability, Programmability...
- Ateji PX (section Data parallelism)Data parallelism features can also be implemented by libraries using dedicated data structures, such as parallel arrays. The term task parallelism is...
- with statically predictable access patterns are a major source of data parallelism. Dynamic arrays or growable arrays are similar to arrays but add the...
- computing. Data-parallelism applied computation independently to each data item of a set of data, which allows the degree of parallelism to be scaled with...
- important new ideas behind NESL are Nested data parallelism: this feature offers the benefits of data parallelism, concise code that is easy to understand...
- The opportunity for loop-level parallelism often arises in computing programs where data is stored in random access data structures. Where a sequential...
Apache Spark (category Big data products)analytics engine for large-scale data processing. Spark provides an interface for programming clusters with implicit data parallelism and fault tolerance. Originally...
Instruction-level parallelism (ILP) is the parallel or simultaneous execution of a sequence of instructions in a computer program. More specifically ILP...- Pipeline (computing) (redirect from Pipeline parallelism)fashion can handle the building and running of big data pipelines. Dataflow Throughput Parallelism Instruction pipeline Classic RISC pipeline Graphics...
In computing, multiple instruction, multiple data (MIMD) is a technique employed to achieve parallelism. Machines using MIMD have a number of processors...- size N. As in this example, scalable parallelism is typically a form of data parallelism. This form of parallelism is often the target of automatic parallelization...
perform the same operation on multiple data points simultaneously. Such machines exploit data level parallelism, but not concurrency: there are simultaneous...- single program, multiple data (SPMD) is a term that has been used to refer to computational models for exploiting parallelism where-by multiple processors...
- technique is used when a loop cannot be fully parallelized by DOALL parallelism due to data dependencies between loop iterations, typically loop-carried dependencies...
- on how parallelism can be expressed in order to enable more aggressive compiler optimisations. In particular, irregular nested data parallelism is not...
- Encyclopedia Psycho-Physical Parallelism by Leslie Joseph Walker 104966Catholic Encyclopedia — Psycho-Physical ParallelismLeslie Joseph Walker A doctrine
- There is considerable skepticism regarding the viability of massive parallelism; the skepticism centers around Amdahl’s law, an argument put forth by
- parallel data processing, the SIMD (Single Instruction - Many Data) architecture is applied. The implemented method of thread-level parallelism was the