Ben barsdell matthew bailes christopher fluke david barnes
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Spotting Radio Transients With the help of GPUs PowerPoint PPT Presentation


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Ben Barsdell Matthew Bailes Christopher Fluke David Barnes. Spotting Radio Transients With the help of GPUs. Background. Goal is to discover new pulsars and radio transients. Survey specs 400 MHz BW @ 1381.8 MHz 1024 freq. channels 64 μ s time resolution 2-bit sampling.

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Spotting Radio Transients With the help of GPUs

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Ben barsdell matthew bailes christopher fluke david barnes

Ben Barsdell

Matthew Bailes

Christopher Fluke

David Barnes

Spotting Radio TransientsWith the help of GPUs


Background

Background

  • Goal is to discover new pulsars and radio transients

Survey specs

400 MHz BW @ 1381.8 MHz

1024 freq. channels

64μs time resolution

2-bit sampling

High Time Resolution Universe (HTRU) survey

Uses the Parkes 64m radio telescope


Spotting radio transients with the help of gpus

Multi-beam receiver

Event

Follow-up

observation

Parkes

Swinburne

Dedispersed time series

Masked data

Filterbank data

Freq.

Freq.

DM

RFI removal

Time

Time

Time

Incoherent dedispersion

List of candidates

Signal search

Ben Barsdell - ADASS 2011


The plan

The Plan

  • Current pipeline takes> 30 mins per 10 min observation

    • Necessitates off-line processing

    • Means transfers, tapes and long waits

  • Would like to speed things up to real-time

    • Instant feedback and follow-up observations

    • Triggered baseband data dumps

  • How to do it?

  • Time to bring out the heavy artillery…

Ben Barsdell - ADASS 2011


Spotting radio transients with the help of gpus

The GPU

Ben Barsdell - ADASS 2011


Spotting radio transients with the help of gpus

Telescope receiver beams

Event

Follow-up

observation

Parkes

Swinburne

Masked data

Dedispersed time series

Filterbank data

Freq.

Freq.

DM

RFI removal

Time

Time

Time

Incoherent dedispersion

List of candidates

Signal search

Ben Barsdell - ADASS 2011


The detection pipeline

RFI mitigation

The detection pipeline

Incoherent dedispersion

Baseline removal

Fourier search

Single pulse search

Fourier transform

Matched filter

Harmonic summing

RFI mitigation

Sigma clip

Report candidates

Ben Barsdell - ADASS 2011


Rfi mitigation

RFI mitigation

www.clker.com

  • Interference is a big problem

  • No easy solution

    • Military radar too important

    • Prime-time TV too popular

  • Some things can be done

    • Sigma clipping

    • Spectral kurtosis

    • Coincidence rejection

Ben Barsdell - ADASS 2011


Coincidence rejection

Coincidence rejection

  • Use multi-beam receiver as reference antennas

    • Assume RFI is not localised

  • Apply simple coincidence criteria:

    • E.g., 3σ in 4+ beams => RFI

  • Or use Eigen-decomposition approach

  • Run on GPU as a straightforward transform

    • RFI_mask[i] = is_RFI(multibeam_data[i])

    • Note: Eigen-decomp method makes is_RFI()trickier

Ben Barsdell - ADASS 2011


Dedispersion

Dedispersion

ISM

Broadband signal

Dispersed signal

Radio

source

e-

Frequency (MHz)

Frequency (MHz)

?

Phase

Phase

Ben Barsdell - ADASS 2011

  • Unknown distance => search through DM space

  • Pick DM, dedisperse, search, repeat

    • ~1200 DM trials


Dedispersion1

Dedispersion

  • Computationally intensive problem

    • Biggest time-consumer

  • Runs really well on a GPU

    • Lots of parallelism

    • High arithmetic intensity

    • Good memory access patterns

    • No branching

Ben Barsdell - ADASS 2011


Other algorithms

Other algorithms

  • Baseline removal

    • Subtract running mean

    • Port to GPU using parallel prefix sum

  • Matched filtering

    • Convolve with 1D boxcar

    • Can also use parallel prefix sum

  • Sigma cut + peak find

    • Threshold and segment

    • Port to GPU using segmented reduction

Ben Barsdell - ADASS 2011


Gpu d edispersion

GPU dedispersion

Ben Barsdell - ADASS 2011


Preliminary results

Preliminary results

  • Dedispersion: 20 mins  < 2.5 mins

    • Using ‘direct’ method on 1 Tesla C2050 GPU

    • Time-binning gives further 2x speed-up

    • Details in Barsdell et al. 2012

  • Other algorithms mostly complete

  • 1 beam / GPU should be easy

    • 2 beams / GPU within reach?

Ben Barsdell - ADASS 2011


Software hardware configuration

Software/hardware configuration

Process

Operation

1

Recv beam

Dedisperse

Send DMs

Recv beams

Continue…

.

.

.

.

.

.

.

.

.

2

Send DMs

Recv beams

.

.

.

3

Recv beams

4

Recv beams

.

.

.

Ben Barsdell - ADASS 2011


Deployment

Deployment

Destined for Parkes

Real-time results

RFI ‘weather report’

Ben Barsdell - ADASS 2011


Looking ahead

Looking ahead

  • Real-time radio transient detection promises to

    • Simplify the data processing procedure

    • Enable immediate follow-up observations

    • Allow capture of high-resolution baseband data for significant events

    • Catch things like the ‘Lorimer burst’ as they happen!

Ben Barsdell - ADASS 2011


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