Implementation and performance evaluation of reconstruction algorithms on graphics processors
Implementation and performance evaluation of reconstruction algorithms on graphics processors
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DOI：
10.1016/j.jsb.2006.08.010
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发表时间：
2007-01-01
影响因子：
3
通讯作者：
Frangakis, Achilleas S.
中科院分区：
文献类型：
--
作者：
Diez, Daniel Castano;Mueller, Hannes;Frangakis, Achilleas S.
电子断层成像和单粒子分析的高通量需求推动了几种重建算法和软件包在计算集群上的并行实现。在这里，我们报告了常用的重建算法，如加权反投影，同步迭代重建技术(SIRT)和同步代数重建技术(SART)在通用图形处理器(GPU)上的实现。与单个中央处理器(CPU)的性能相比，在GPU上实现的速度提升大约是60(60倍)到80(80倍)倍，这与在中等范围计算集群上实现的加速相当。这种重建的加速是由GPU高度专业化的架构造成的。此外，我们还证明了在GPU上重建的质量与在CPU上相当。我们给出了实现的详细流程图。该重建软件除了商用显卡外，不需要特殊的硬件，并且可以很容易地集成到SPIDER、XMIPP、TOM-PACKET等软件包中。(C)2006 Elsevier Inc.保留所有权利。
The high-throughput needs in electron tomography and in single particle analysis have driven the parallel implementation of several reconstruction algorithms and software packages on computing Clusters. Here, we report on the implementation of popular reconstruction algorithms as weighted backprojection, simultaneous iterative reconstruction technique (SIRT) and simultaneous algebraic reconstruction technique (SART) on common graphics processors (GPUs). The speed gain achieved on the GPUs is in the order of sixty (60x) to eighty (80x) times, compared to the performance of a single central processing unit (CPU), which is comparable to the acceleration achieved on a medium-range computing cluster. This acceleration of the reconstruction is caused by the highly specialized architecture of the GPU. Further, we show that the quality of the reconstruction on the GPU is comparable to the CPU. We present detailed flow-chart diagrams of the implementation. The reconstruction software does not require special hardware apart from the commercially available graphics cards and could be easily integrated in software packages like SPIDER, XMIPP, TOM-Package and others. (c) 2006 Elsevier Inc. All rights reserved.