By : Arjun RadhakrishnanSupervisor : Prof. M. Inggs

Pulsars and pulsar dispersion

Graphics Processing Units (GPUs)

Research method and Results

Conclusion and Future Work

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Pulsars are highly magnetised rotating neutron stars

They emit beams of electromagnetic radiation from their poles

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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: Dedispersion2 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

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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

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Worked at UIUC on the QP GPU cluster

Implemented the following coherent pulsar dedispersion algorithm4: Fourier transform input signal Apply a phase rotation Inverse Fourier transform

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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)

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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

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1. Cordes & McLaughlin (2003), “Searches for Fast Radio Transients”, The Astronomical Journal, vol. 596, pp. 1142-1154

2. Jim Cordes, “The SKA as a Radio Synoptic Survey Telescope: Widefield Surveys for Transients, Pulsars and ETI”, SKA Memo 97

3. NVIDIA, NVIDIA CUDA Programming Guide4. Walter Brisken, “Real-time Digital Signal

Processing for Radio Astronomy” AstroGPU

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