Processors

Data Regression With Normal Equation on GPU Using CUDA

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Executive Summary

Demand in the consumer market for graphics hardware that accelerates rendering of 3D images has resulted in Graphic Cards that are capable of delivering astonishing levels of performance. These results were achieved by specifically tailoring the hardware for the target domain. As graphics accelerators become increasingly programmable however, this performance has made them an attractive target for other domains. Graphic processing units provide a low-cost parallel computing architecture. It is possible to achieve massive parallelism by SIMD (Single Instruction Multiple Data) on General Purpose Graphics Processing Unit (GPGPU) integrated with Central Processing Unit (CPU).

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