论文标题
迈向自动HPC管道，用于处理大型电子显微镜数据
Toward an Automated HPC Pipeline for Processing Large Scale Electron Microscopy Data
论文作者
论文摘要
我们提出了一个完全可扩展的软件管道，用于处理脑切片的电子显微镜（EM）图像，以分为单个神经元的3D可视化，并使用超级计算机展示了大EM体积的端到端分割。我们的管道缩放了EM社区使用的多个软件包，对原始源代码的变化很小。我们在工作站，群集和超级计算机上单独测试管道的每个步骤。此外，我们可以使用可以在数据采集期间或使用不同前端触发的BALSAM数据库中从这些操作中撰写工作流程，并控制管道执行的粒度。我们描述了我们的管道的实现以及整合和扩展现有代码所需的修改。我们环境的模块化性质使多样化的研究小组能够为管道做出贡献而不会破坏工作流程，即，可以在管道上的每个步骤都可以轻松地集成新的单个代码。
We present a fully modular and scalable software pipeline for processing electron microscope (EM) images of brain slices into 3D visualization of individual neurons and demonstrate an end-to-end segmentation of a large EM volume using a supercomputer. Our pipeline scales multiple packages used by the EM community with minimal changes to the original source codes. We tested each step of the pipeline individually, on a workstation, a cluster, and a supercomputer. Furthermore, we can compose workflows from these operations using a Balsam database that can be triggered during the data acquisition or with the use of different front ends and control the granularity of the pipeline execution. We describe the implementation of our pipeline and modifications required to integrate and scale up existing codes. The modular nature of our environment enables diverse research groups to contribute to the pipeline without disrupting the workflow, i.e. new individual codes can be easily integrated for each step on the pipeline.
