Accelerating electron tomography reconstruction algorithm ICON with GPU.

Accelerating electron tomography reconstruction algorithm ICON with GPU.
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使用 GPU 加速电子断层扫描重建算法 ICON

DOI:
10.1007/s41048-017-0041-z
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发表时间:
2017
期刊:
影响因子:
--
通讯作者:
Zhang F
Zhang F
中科院分区:
其他
文献类型:
--
作者:
Chen Y;Wang Z;Zhang J;Li L;Wan X;Sun F;Zhang F

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电子断层扫描(ET)在三维空间研究原位细胞超微结构方面发挥着重要作用。由于倾斜角度有限,ET重建一直存在“缺楔”问题。通过验证过程,迭代压缩感知优化的NUFFT重建(ICON)在恢复低信噪比生物ET数据集的验证缺失信息方面展示了其能力。然而,巨大的计算需求已经成为ICON应用的主要问题。在本工作中,我们分析了ICON的框架,并将ICON重建的主要步骤分为三种类型。因此,我们设计并行策略并在图形处理单元(GPU)上实现,生成并行程序ICON-GPU。ICON- gpu具有较高的精度,相对于CPU版本有很大的加速,高达83.7倍,大大减轻了ICON对计算资源的依赖。
Electron tomography (ET) plays an important role in studying in situ cell ultrastructure in three-dimensional space. Due to limited tilt angles, ET reconstruction always suffers from the “missing wedge” problem. With a validation procedure, iterative compressed-sensing optimized NUFFT reconstruction (ICON) demonstrates its power in the restoration of validated missing information for low SNR biological ET dataset. However, the huge computational demand has become a major problem for the application of ICON. In this work, we analyzed the framework of ICON and classified the operations of major steps of ICON reconstruction into three types. Accordingly, we designed parallel strategies and implemented them on graphics processing units (GPU) to generate a parallel program ICON-GPU. With high accuracy, ICON-GPU has a great acceleration compared to its CPU version, up to 83.7×, greatly relieving ICON’s dependence on computing resource.