Offline vs Real-Time Validation and Performance Assessment of Heimdall Detection Pipeline for Fast Radio Bursts

RESUMO

Data rates from current radio telescopes are of $\sim$O(10)PB/y and we expect a growth of an order of magnitude for future radio telescopes, e.g. SKA. Coping with these data flows requires a paradigm change in data management: building pipelines with intense I/O between their modules (offline mode) is becoming unsustainable, leading to a transition to a real-time paradigm, where data are moved to RAM, e.g.,through PSRDADA ring buffers. Our objective is to obtain a compact pipeline to efficiently manage data in the real-time flow, while minimizing HPC resources. We employ Heimdall, an open source detection pipeline that performs incoherent de-dispersion, to detect single pulses in radio astronomy data, such as FRBs, astrophysical signals whose origin has not been completely explained. Heimdall currently processes a single beam on a single GPU and can operate both in offline and real-time modes, reading in input either a SIGPROC filterbank file or a PSRDADA ring buffer. We run a test pipeline with data collected from 16 cylinders of the NS arm of the Northern Cross radio telescope near Medicina, both in offline and real-time modes, to compare the obtained results and performance. To corroborate these tests, we employ different input data and explore the problem's parameter space. PSRDADA and SIGPROC results generally agree within 3% for the most important quantities characterizing a FRB (TOA and DM) and within 10% for the SNR. Execution times in PSRDADA mode stay in the real-time flow for most runs from data containing true FRBs but they are still generally comparable with SIGPROC mode in this testbed setup. This test provides an important preliminary comparison in terms of accuracy and performance: this work is functional and preparatory for the next integration of the beamformer with the Heimdall pipeline, having the same logical structure as the test pipeline, work already in progress.