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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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