SIMD

(redirected from data parallel)
Also found in: Wikipedia.

SIMD

(computer science)
A type of multiprocessor architecture in which there is a single instruction cycle, but multiple sets of operands may be fetched to multiple processing units and may be operated upon simultaneously within a single instruction cycle. Acronym for single-instruction-stream, multiple-data-stream.

SIMD

SIMD

(Single Instruction stream Multiple Data stream) The instruction execution architecture of a vector processor (a CPU or GPU that performs one operation on multiple sets of data simultaneously). It is typically used to add or multiply eight or more sets of numbers at the same time for multimedia encoding and rendering as well as scientific applications. Hardware registers are loaded with numbers, and the mathematical operation is performed on all registers simultaneously. Contrast with SISD and MIMD. See GPU.
References in periodicals archive ?
Given the raw power provided by 100s of cores various data parallel applications could now take advantage of this massively parallel hardware.
Field-Programmable Gate Arrays (FPGA), which have the characteristics of both an application-specific integrated circuit (ASIC) and a general chip, have the ability to do data parallel and task parallel computing simultaneously, which allows them to be more efficient in dealing with specific applications.
So, the efforts have made course data parallel program, minimum communication between the data (only for distribution of the data and receiving the results) and nearly equal computational efforts.
GPUs are highly parallel, computationally powerful, very fast floating point number crunchers, designed for data parallel, task parallel or pipelined parallel programming--the sort of programming needed for scientific computing, simulation, animation.
Similarly, C++ data parallel extensions, such as Thrust, are generic enough to provide some degree of comfort that future versions will be implemented for other platforms like OpenCL.
Fujitsu's new software includes a product called Interstage Big Data Parallel Processing Server, which expands on the open-source Apache Hadoop platform for building filesystems across networks of independent servers.
Highly reliable parallel distributed processing - Interstage Big Data Parallel Processing Server V1 (available since February)
A data parallel algorithm can be divided into three phases : data partition, local computation, and result collection.
These guys are highly respected experts in data parallel programming.
He then covers pipeline design and vector processors, data parallel architectures, and multiprocessor systems.
Scientific applications are, in general, large, computationally intensive and data parallel.
This data parallel approach requires the creation and management of data partitions and replicas that are used by the compute nodes.