Aris Karastergiou

Abstract:

Astrophysical radio transients are excellent probes of extreme physical processes originating from compact sources within our Galaxy and beyond. Radio frequency signals emitted from these objects provide a means to study the intervening medium through which they travel. Next generation radio telescopes are designed to explore the vast unexplored parameter space of high time resolution astronomy, but require High Performance Computing (HPC) solutions to process the enormous volumes of data that are produced by these telescopes. We have developed a combined software /hardware solution (code named ARTEMIS) for real-time searches for millisecond radio transients, which uses GPU technology to remove interstellar dispersion and detect millisecond radio bursts from astronomical sources in real-time. Here we present an introduction to ARTEMIS. We give a brief overview of the software pipeline, then focus specifically on the intricacies of performing incoherent de-dispersion. We present results from two brute-force algorithms. The first is a GPU based algorithm, designed to exploit the L1 cache of the NVIDIA Fermi GPU. Our second algorithm is CPU based and exploits the new AVX units in Intel Sandy Bridge CPUs.

Abstract:

The identification and subsequent discovery of fast radio transients using blind-search surveys require a large amount of processing power, in worst cases scaling as. For this reason, survey data are generally processed off-line, using high-performance computing architectures or hardware-based designs. In recent years, graphics processing units (GPUs) have been extensively used for numerical analysis and scientific simulations, especially after the introduction of new high-level application programming interfaces. Here, we show how GPUs can be used for fast transient discovery in real time. We present a solution to the problem of de-dispersion, providing performance comparisons with a typical computing machine and traditional pulsar processing software. We describe the architecture of a real-time, GPU-based transient search machine. In terms of performance, our GPU solution provides a speed-up factor of between 50 and 200, depending on the parameters of the search. © 2011 The Authors Monthly Notices of the Royal Astronomical Society © 2011 RAS.

Abstract:

Flux monitoring of compact radio quasars has revealed dramatic radio-wave lensing events which challenge our understanding of the interstellar medium. However, the data on these events remain very sparse. Here we consider how the Goonhilly radio astronomical facility can make an impact on this problem by dedicating one or more dishes to flux monitoring for a period of one year. Such an experiment would be able to identify \sim6 new events and study them in detail.

Abstract:

The LOw Frequency ARray is the first of the next generation of radio telescopes to be completed. It uses large numbers of small receptors and vast computing and data transport capabilities to achieve a high degree of sensitivity over large fields of view. It uses two different types of receptor to enable it to observe over the frequency range 10-260 MHz. Here we report on some of the capabilities of this telescope for pulsar and fast transient research. We also present some results of the commissioning work that we have been carrying out which highlight the exciting potential of this telescope. These include simultaneous imaging and pulsar observations, simultaneous observations spanning 30-8000 MHz, a large number of known pulsars detected in the high band and the detection of PSR B0809+74 down to a frequency of 16 MHz. © 2011 American Institute of Physics.

Abstract:

The identification, and subsequent discovery, of fast radio transients through blind-search surveys requires a large amount of processing power, in worst cases scaling as $\mathcal{O}(N^3)$. For this reason, survey data are generally processed offline, using high-performance computing architectures or hardware-based designs. In recent years, graphics processing units have been extensively used for numerical analysis and scientific simulations, especially after the introduction of new high-level application programming interfaces. Here we show how GPUs can be used for fast transient discovery in real-time. We present a solution to the problem of de-dispersion, providing performance comparisons with a typical computing machine and traditional pulsar processing software. We describe the architecture of a real-time, GPU-based transient search machine. In terms of performance, our GPU solution provides a speed-up factor of between 50 and 200, depending on the parameters of the search.