By : Arjun Radhakrishnan Supervisor : Prof. M. Inggs
Pulsars and pulsar dispersion Graphics Processing Units (GPUs) Research method and Results Conclusion and Future Work 2
Pulsars are highly magnetised rotating neutron stars They emit beams of electromagnetic radiation from their poles 3 Figure 1: A Pulsar with its ‘lighthouse’ beam [hartrao.ac.za]
Pulsar emissions are distorted upon passing through the ionised Interstellar Medium (ISM) Lower frequency components of the pulse are delayed more than higher frequencies
Figure 2: Dedispersion 2 5
Class of consumer parallel processor that has come into use in the last 15 years Use growing exponentially due to demand from billion-dollar video game industry NVIDIA and AMD (ATI) are currently major players in the industry GPUs do not have much on-chip memory – can pack in lots of compute power 6
Justification for SKA Large frequency range 1TB of data per minute SKA needs real-time processing as data storage is not feasible No communication needed between GPU kernels 7
Worked at UIUC on the QP GPU cluster Implemented the following coherent pulsar dedispersion algorithm 4 : Fourier transform input signal Apply a phase rotation Inverse Fourier transform 8
Code testing is still being conducted Some trends noted are: Speedup of up to 5x over CPU implementation Performance improved approximately linearly with the number of GPUs used Best performance for larger datasets (minimises effect of IO bottleneck) 9
GPUs definitely show promise in this application Further speedup may be possible by using an asynchronous data transfer Analyse the network requirements and limitations when deployed 10
1. Cordes & McLaughlin (2003), “Searches for Fast Radio Transients”, The Astronomical Journal, vol. 596, pp Jim Cordes, “The SKA as a Radio Synoptic Survey Telescope: Widefield Surveys for Transients, Pulsars and ETI”, SKA Memo NVIDIA, NVIDIA CUDA Programming Guide 4. Walter Brisken, “Real-time Digital Signal Processing for Radio Astronomy” AstroGPU 11
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