Multiple signal classification algorithm (MUSICAL) provides a super-resolution microscopy method. In the previous research, MUSICAL has enabled data-parallelism well on a desktop computer or a Linux-based server. However, the running time needs to be shorter. This paper will develop a new parallel MUSICAL with high efficiency and scalability on a cluster of computers. We achieve the purpose by using the optimal speed of the cluster cores, the latest parallel programming techniques, and the high-performance computing libraries, such as the Intel Threading Building Blocks (TBB), the Intel Math Kernel Library (MKL), and the unified parallel C++ (UPC++) for the cluster of computers. Our experimental results show that the new parallel MUSICAL achieves a speed-up of 240.29x within 10 seconds on the 256-core cluster with an efficiency of 93.86%. Our MUSICAL offers a high possibility for real-life applications to make super-resolution microscopy within seconds.
翻译：多信号分类算法(Musical)提供了一种超分辨率显微镜法。 在以前的研究中, Musical 使台式计算机或基于 Linux 的服务器上的数据光谱钻井。 但是,运行时间需要缩短。 本文将开发出一个新的平行的Musical, 在一组计算机上的效率和可缩放性较高。 我们通过使用集群核心的最佳速度、最新的平行编程技术以及高性能的计算图书馆,如 Intel Threading 建筑块、 Intel Math Kernel 图书馆和计算机集群的统一平行 C++ (UPC+++ ) 来实现这一目标。 我们的实验结果显示,新的平行MUSical 在256 核心集群上在10秒内实现240.29x的加速, 效率为93.86%。 我们的MUSical为实时应用在几秒内进行超分辨率显微镜检查提供了很大的可能性。
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