Fumihiko Ino, Yusuke Okitsu, Taketo Kishi, S. Ohnishi, K. Hagihara
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引用次数: 4
Abstract
This paper presents a graphics processing unit (GPU) based method capable of accelerating cone-beam reconstruction of large volume data, which cannot be entirely stored in video memory. Our method accelerates the Feldkamp, Davis and Kress (FDK) algorithm in a multi-GPU environment. We present how the entire volume can be efficiently decomposed into small portions to reduce the usage of video memory on each graphics card. Experimental results are also presented to understand the reconstruction throughput on an nVIDIA Tesla S1070 server. It takes approximately three minutes to reconstruct a 20483-voxel volume from 720 20482-pixel projections. The effective bandwidth of video memory reaches 137 GB/s per GPU, demonstrating a higher utilization of texture caches.
本文提出了一种基于图形处理单元(GPU)的方法,能够对不能完全存储在显存中的大容量数据加速锥束重建。我们的方法在多gpu环境下加速了FDK算法。我们介绍了如何有效地将整个卷分解成小部分,以减少每个图形卡上视频内存的使用。通过实验结果了解了在nVIDIA Tesla S1070服务器上的重构吞吐量。从720个20482像素的投影中重建一个20483体素的体积大约需要3分钟。每个GPU的显存有效带宽达到137 GB/s,纹理缓存的利用率更高。