Architecture, implementation and parallelization of the software to search for periodic gravitational wave signals

TL;DR

This paper presents a highly scalable parallel software for searching periodic gravitational wave signals from neutron stars, optimized for supercomputers, enabling large-scale data analysis within feasible time frames.

Contribution

The paper introduces a parallelization and scalability framework for the extsky code, utilizing MPI and parallel I/O, to efficiently analyze gravitational wave data on supercomputers.

Findings

Achieved efficient scaling up to 50,000 cores.

Demonstrated scalability and performance on a Cray XE6 system.

Enabled large-scale gravitational wave data analysis within acceptable time.

Abstract

The parallelization, design and scalability of the \sky code to search for periodic gravitational waves from rotating neutron stars is discussed. The code is based on an efficient implementation of the F-statistic using the Fast Fourier Transform algorithm. To perform an analysis of data from the advanced LIGO and Virgo gravitational wave detectors' network, which will start operating in 2015, hundreds of millions of CPU hours will be required - the code utilizing the potential of massively parallel supercomputers is therefore mandatory. We have parallelized the code using the Message Passing Interface standard, implemented a mechanism for combining the searches at different sky-positions and frequency bands into one extremely scalable program. The parallel I/O interface is used to escape bottlenecks, when writing the generated data into file system. This allowed to develop a highly scalable computation code, which would enable the data analysis at large scales on acceptable time scales. Benchmarking of the code on a Cray XE6 system was performed to show efficiency of our parallelization concept and to demonstrate scaling up to 50 thousand cores in parallel.