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A Coarse-grained Stream Architecture for Cryo-electron Microscopy Images 3D Reconstruction

机译:低温电子显微镜图像3D重构的粗粒度流架构

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The wide acceptance and the data deluge in the bioinfor-rnatics and medical imaging processing require more efficient and application-specific systems to be built. Due to the recent advances in FPGAs technologies, there has been a resurgence in research aimed at the design of special-purpose accelerators for standard computer architectures. In this paper, we exploit this trend towards FPGA-based accelerator design and provide a proof-of-concept and comprehensive case study on FPGA-based accelerator design for a single-particle 3D reconstruction application in single-precision floating-point format. The proposed stream architecture is built by first offloading computing-intensive software kernels to dedicated hardware modules, which emphasizes the importance of optimizing computing dominated data access patterns. Then configurable computing streams are constructed by arranging the hardware modules and bypass channels to form a linear deep pipeline. The efficiency of the proposed stream architecture is justified by the reported 2.54 times speedup over a 4-cores CPU. In terms of power efficiency, our FPGA-based accelerator introduces a 7.33 and 3.4 times improvement over a 4-cores CPU and an up-to-date GPU device, respectively.
机译:生物信息学和医学成像处理技术的广泛接受和数据泛滥需要构建更加高效和针对特定应用的系统。由于FPGA技术的最新进展,针对针对标准计算机体系结构的专用加速器设计的研究重新兴起。在本文中,我们探索了这种基于FPGA的加速器设计的趋势,并为单精度3D重构应用中的单精度浮点格式的基于FPGA的加速器设计提供了概念验证和全面的案例研究。通过首先将计算密集型软件内核卸载到专用硬件模块来构建提出的流体系结构,这强调了优化计算为主的数据访问模式的重要性。然后,通过布置硬件模块和旁路通道来构建可配置的计算流,以形成线性深层流水线。据报道,在4核CPU上的2.54倍加速,证明了所提出的流架构的效率。在功率效率方面,我们的基于FPGA的加速器分别比4核CPU和最新的GPU器件提高了7.33和3.4倍。

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