Implementation of Variable Preconditioned GCR with mixed precision on GPU using CUDA

S. Ikuno, N. Fujita, Susumu Yamamoto, S. Nakata
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Abstract

The Variable Preconditioned GVR (VPGCR) with mixed precision on Graphics Processing Unit (GPU) using Compute Unified Device Architecture (CUDA) is numerically investigated. The convergence theorem of VPGCR is guaranteed that the residual equation for the preconditioned procedure can be solved in the range of single precision operation. The results of computations show that VPGCR with mixed precision operation on GPU demonstrated significant achievement than that of CPU. Especially, VPGCR on GPU with mixed precision operation is 22.53 times faster than that of Central Processing Unit (CPU).
基于CUDA的混合精度可变预处理GCR在GPU上的实现
采用计算统一设备架构(CUDA)对混合精度的可变预置GVR (VPGCR)进行了数值研究。利用VPGCR的收敛性定理,保证了在单精度运算范围内,预条件过程的残差方程可以得到解。计算结果表明,在GPU上进行混合精度运算的VPGCR比在CPU上取得了显著的效果。特别是在混合精度运算的GPU上,VPGCR比CPU (Central Processing Unit)快22.53倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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