High-performance computing for super-resolution microscopy on a cluster of computers

Autor:	Do, Quan, Kristiansen, Jon Ivar, Agarwal, Krishna, Ha, Phuong Hoai
Rok vydání:	2022
Předmět:	Computer Science - Distributed Parallel and Cluster Computing Computer Science - Performance
Druh dokumentu:	Working Paper
Popis:	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. Comment: The requests I have received from my co-authors
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2206.03231 Zobrazit plný text záznamu View this record from Arxiv