Castaño Díez Daniel, Mueller Hannes, Frangakis Achilleas S
European Molecular Biology Laboratory, Meyerhofstr. 1, 69117 Heidelberg, Germany.
J Struct Biol. 2007 Jan;157(1):288-95. doi: 10.1016/j.jsb.2006.08.010. Epub 2006 Sep 1.
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.
电子断层扫描和单颗粒分析中的高通量需求推动了在计算集群上并行实施多种重建算法和软件包。在此，我们报告了在通用图形处理器（GPU）上实现流行的重建算法，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）。与单个中央处理器（CPU）的性能相比，在GPU上实现的速度提升约为60到80倍，这与在中程计算集群上实现的加速效果相当。这种重建加速是由GPU高度专业化的架构所导致的。此外，我们表明在GPU上重建的质量与CPU相当。我们展示了实现的详细流程图。除了市售的图形卡外，该重建软件不需要特殊硬件，并且可以轻松集成到如SPIDER、XMIPP、TOM-Package等软件包中。
