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Single-particle 3d reconstruction from cryo-electron microscopy images on GPU

机译:从GPU上的低温电子显微镜图像进行单粒子3d重建

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Single-particle 3D reconstruction from cryo-electron microscopy (cryo-EM) images is a kernel application of biological molecules analysis, as the computational requirement of which is now beyond PetaFlop for a high-resolution 3D structure. In this paper, we quantitatively analyze the workload, computational intensity and memory performance of the application, parallelize it on an emerging multicore architecture GPU-CUDA. Further we apply a percolation technique to decouple computation with memory operations and orchestrate thread-data mapping to reduce the overhead off-chip memory operations. Finally we tested our optimization strategy on a popular open-source package EMAN to GPU-CUDA, which achieves a relative speedup of about 10X to the original CPU-only EMAN. The experimental results also show that the proposed percolation programming greatly improves utilization of memory bandwidth and floating-point units.
机译:低温电子显微镜(cryo-EM)图像的单粒子3D重建是生物分子分析的核心应用,因为对于高分辨率3D结构,其计算要求现已超出PetaFlop。在本文中,我们定量分析了应用程序的工作负载,计算强度和内存性能,并在新兴的多核架构GPU-CUDA上将其并行化。此外,我们应用渗滤技术将计算与内存操作解耦,并编排线程数据映射以减少开销的片外内存操作。最后,我们在流行的开源软件包EMAN到GPU-CUDA上测试了我们的优化策略,与原始的仅CPU的EMAN相比,它的相对速度提高了约10倍。实验结果还表明,提出的渗流编程大大提高了内存带宽和浮点单元的利用率。

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