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Register a new userProspects of GPGPU in the Auger Offline Software Framework
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The Pierre Auger Observatory is the currently largest experiment dedicated to unveil the nature and origin of the highest energetic cosmic rays. The software framework Offline has been developed by the Pierre Auger Collaboration for joint analysis of data from different independent detector systems used in one observatory. While reconstruction modules are specific to the Pierre Auger Observatory components of the Offline framework are also used by other experiments. The software framework has recently been extended to incorporate data from the Auger Engineering Radio Array (AERA), the radio extension of the Pierre Auger Observatory. The reconstruction of the data of such radio detectors requires the repeated evaluation of complex antenna gain patterns which significantly increases the required computing resources in the joint analysis. In this contribution we explore the usability of massive parallelization of parts of the Offline code on the GPU. We present the result of a systematic profiling of the joint analysis of the Offline software framework aiming for the identification of code areas suitable for parallelization on GPUs. Possible strategies and obstacles for the usage of GPGPU in an existing experiment framework are discussed.
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The advent of the Auger Engineering Radio Array (AERA) necessitates the development of a powerful framework for the analysis of radio measurements of cosmic ray air showers. As AERA performs radio-hybrid measurements of air shower radio emission in coincidence with the surface particle detectors and fluorescence telescopes of the Pierre Auger Observatory, the radio analysis functionality had to be incorporated in the existing hybrid analysis solutions for fluoresence and surface detector data. This goal has been achieved in a natural way by extending the existing Auger Offline software framework with radio functionality. In this article, we lay out the design, highlights and features of the radio extension implemented in the Auger Offline framework. Its functionality has achieved a high degree of sophistication and offers advanced features such as vectorial reconstruction of the electric field, advanced signal processing algorithms, a transparent and efficient handling of FFTs, a very detailed simulation of detector effects, and the read-in of multiple data formats including data from various radio simulation codes. The source code of this radio functionality can be made available to interested parties on request.
A software system has been developed for the DArk Matter Particle Explorer (DAMPE) mission, a satellite-based experiment. The DAMPE software is mainly written in C++ and steered using Python script. This article presents an overview of the DAMPE offline software, including the major architecture design and specific implementation for simulation, calibration and reconstruction. The whole system has been successfully applied to DAMPE data analysis, based on which some results from simulation and beam test experiments are obtained and presented.
We present a modular framework, the Workload Characterisation Framework (WCF), that is developed to reproducibly obtain, store and compare key characteristics of radio astronomy processing software. As a demonstration, we discuss the experiences using the framework to characterise a LOFAR calibration and imaging pipeline.
The GstLAL library, derived from Gstreamer and the LIGO Algorithm Library, supports a stream-based approach to gravitational-wave data processing. Although GstLAL was primarily designed to search for gravitational-wave signatures of merging black holes and neutron stars, it has also contributed to other gravitational-wave searches, data calibration, and detector-characterization efforts. GstLAL has played an integral role in all of the LIGO-Virgo collaboration detections, and its low-latency configuration has enabled rapid electromagnetic follow-up for dozens of compact binary candidates.
The Polarimetric and Helioseismic Imager (PHI) is the first deep-space solar spectropolarimeter, on-board the Solar Orbiter (SO) space mission. It faces: stringent requirements on science data accuracy, a dynamic environment, and severe limitations on telemetry volume. SO/PHI overcomes these restrictions through on-board instrument calibration and science data reduction, using dedicated firmware in FPGAs. This contribution analyses the accuracy of a data processing pipeline by comparing the results obtained with SO/PHI hardware to a reference from a ground computer. The results show that for the analysed pipeline the error introduced by the firmware implementation is well below the requirements of SO/PHI.
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