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Some Challenges in Signal Processing and Computing in Astrophysics

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Title: Some Challenges in Signal Processing and Computing in Astrophysics


1
Some Challenges in Signal Processing and
Computing in Astrophysics
  • Yashwant Gupta
  • National Centre for Radio Astrophysics
  • Tata Institute of Fundamental Research

Scientific Discovery Through Intensive Data
Exploration JNCASR Bangalore 4th
February 2011
2
Introduction Different Ways of Scientific
Discovery
  • Computational Astrophysics
  • Numerical Simulations
  • Large Volume Data Analysis (offline)
  • Real-time Data Processing (Instrumentation)

3
Numerical Simulations in Astrophysics
  • Examples of simulations
  • Large scale structure of the Universe
  • Formation interaction of galaxies
  • Formation of stars and solar systems
  • Complex structure of the Sun
  • Common features
  • Involve upto 109 or more particles
  • Complex interactions between particles
    gravity, magneto-hydrodynamics etc
  • Long time-scale evolution, many steps

4
Some large cluster computer systems in
astrophysics
  • Swinburne University of Technology, Melbourne,
    Australia
  • The Swinburne Green machine
  • 145 nodes dual processor quad-core Dell 1950 (
    of cores 1160)
  • 10.8 TFLOPS _at_ 46 KWatts
  • Canadian Institute of Theoretical Astrophysics
    (CITA)
  • The CITA cluster
  • 200 nodes dual processor quad-core Dell 1950 (
    of cores 1600)
  • 15 TFlops _at_ 64 KWatts
  • Harish-Chandra Research Institute (HRI),
    Allahabad

5
Computational Astrophysics
  • Computational Astrophysics
  • Numerical Simulations
  • Large Volume Data Analysis (offline)
  • Real-time Data Processing (Instrumentation)
  • Radio Astronomy
  • (study of the Universe at radio wavelengths)

6
A Basic Radio Telescope
  • THE CHALLENGE
  • Celestial radio signals are VERY weak unit of
    flux used is
  • 1 Jy 10 26 W / m2 / Hz
  • Input radio power into a typical telescope is
    -100 dBm !
  • (would take 1000 years of continuous
    operation to collect 1 milliJoule of energy !!)
  • For high sensitivity (to see faint sources
    out to the distant reaches of the Universe)
  • large dishes (several 10s of metres in diameter)
  • high quality, low noise electronics in the
    receivers
  • large bandwidth of observation
  • long integration times of observation

? Large volumes of data
7
Single Dish versus Array Telescopes
  • Resolution and sensitivity depend on the physical
    size (aperture) of the radio telescope
  • Due to practical limits, fully steerable single
    dishes of more than 100 m diameter are very
    difficult to build
    ? resolution (? / D) 0.5
    degree at 1 metre (very poor compared to
    optical telescopes)
  • To synthesize telescopes of larger size, many
    individual dishes spread out over a large area on
    the Earth are used
  • Signals from such array telescopes are combined
    and processed in a particular fashion to generate
    a map of the source structure EARTH ROTATION
    APERTURE SYNTHESIS
    ? resolution ? / Ds , Ds
    largest separation

The new 100-m Greenbank Telescope
The Very Large Array Telescope
8
A typical modern radio telescope The GMRT
  • The Giant Metre-wave Radio Telescope (GMRT) is a
    new, world class instrument for studying
    astrophysical phenomena at low radio frequencies
    (50 to 1450 MHz)
  • Designed and built primarily by NCRA, a national
    centre of TIFR.
  • Array telescope consisting of 30 antennas of 45
    metres diameter, operating at metre wavelengths
    -- the largest in the world at these frequencies

9
Location and Configuration of the GMRT
  • Latitude 19 deg N
  • Longitude 74 deg E
  • About 70 km N of Pune, 160 km E of Mumbai.
  • 30 dishes 45 m diameter
  • 12 dishes in central compact array
  • Remaining along 3 arms of Y-array
  • Total extent 14 km radius ? resolution of a
    28 km size antenna is achieved

10
Radio Interferometry Aperture Synthesis
  • Signals from a pair of antennas are
    cross-correlated (cross-spectrum is obtained)
  • This functions like a Youngs double slit,
    multiplying the sky brightness distribution by a
    sinusoidal response pattern
  • Thus, an interferometer measures one Fourier
    component of the image
  • From measurements using different pairs of
    antennas, several Fourier components of the image
    are obtained
  • Inverse Fourier transform of the combined
    visibilities gives a reconstruction of the
    original image ? aperture synthesis

The signal processing has both real time and
off-line components
11
GMRT Receiver Digital Back-ends
  • Main components
  • FX Correlator
  • Pulsar Receiver
  • can operate simultaneosly
  • Common signal processing stages sampling, delay
    correction, fringe stopping FFT
  • Input data rate 1.9 Gsamples/s
  • Output data rate few Mbytes/s
  • Total Compute power 150 GFlops
    !
  • Uses mostly ASICs some FPGAs

12
The difficulties of pulsar searching
  • Requires large volumes of data to be handled
    processed
  • 10 mins of data from the GMRT is one data file
    4 GBytes in size
  • In one observing session, there may be 100 such
    data files ? 400 GBytes per night !
  • It is a highly compute intensive job
  • Collapsing multi-channel data into a single
    channel data with different dispersion delays ?
    e.g. 4 GB data explodes to 16 GB data
  • Searching each of the above time series data for
    presence of periodic pulsar signals, using
    spectral domain search algorithms ( 4M point FFT
    analysis algorithms)
  • Sorting and classification of results to identify
    the best candidates
  • Full analysis of a 10 min data stretch ( 4
    GBytes) takes 15 hours on a single, 3.6 GHz
    Xeon processor and requires 16 Gbytes of
    intermediate data storage
  • However, the task is highly amenable to
    parallelisation !

13
Moving to real-time data processing
  • Computational Astrophysics
  • Numerical Simulations
  • Large Volume Data Analysis (offline)
  • Real-time Data Processing (Instrumentation)
  • Radio Astronomy
  • (study of the Universe at radio wavelengths)

14
GMRT Receiver Digital Back-ends
  • Main components
  • FX Correlator
  • Pulsar Receiver
  • can operate simultaneosly
  • Common signal processing stages sampling, delay
    correction, fringe stopping FFT
  • Input data rate 1.9 Gsamples/s
  • Output data rate few Mbytes/s
  • Total Compute power 150 GFlops
    !
  • Uses mostly ASICs some FPGAs
  • Can this data processing be done in REAL-TIME on
    a MULTI-CORE COMPUTE CLUSTER ?

15
Software Based Back-ends
  • Computing resources are off-the-shelf components
  • ? can put together as many as needed to meet
    the real-time requirements !
  • Highly flexible Can change parameters (e.g.
    frequency resolution) and algorithms (e.g.
    polyphase filter bank instead of FFT) almost at
    will
  • Can do full floating point calculations ?
    better accuracy, more dynamic range, better
    protection against interference signals
  • Ability to add new, sophisticated algorithms,
    e.g. to filter out interference signals
  • We have recently completed such a software based
    back-end for the GMRT

16
A Software Back-end for the GMRT
Basic Architecture
  • A 32-channel back-end (32 ants, single pol) using
    16 compute nodes, connected over Gigabit ethernet
  • Node configuration
  • Quad core, dual processor Intel Xeon CPUs
  • 2 GB RAM, 1 TB SATA RAID storage
  • Dual Gigabit Ethernet ports
  • 8-bit, 4 Channel, 100 MSPS, PCI-X compliant ADC
    card

Two Modes of Operation
Jayanta Roy et al (2010)
1. Real-time data acquisition correlation
2. Real-time data acquisition writing to
disks (on each node) offline read-back and
correlation
17
Block Diagram of the GMRT Software Back-end
Jayanta Roy et al (2010)
18
A Software Back-end for the GMRT
Basic Methodology
  • Run synchronous sampling on all 8 ADC boards (32
    antennas) 16/32 MHz BW
  • Transfer data from ADC board to CPU unit via
    interrupt driven DMA over PCI bus in large blocks
    (32 MB size ? 8 MB per antenna)
  • Distribute data from all antennas (using time
    division multiplexing) to all nodes -- each node
    handles 1/8 time slice from each block
  • Carry out FFT, fringe stop, MAC and other
    required operations at each node
  • Record integrated visibilities results to local
    disk on each node, or send them to collector
    nodes
  • Optimise all the operations to meet real-time
    processing requirements

19
Offline Computing for Software Back-end
Possibilities for Multi-beaming of the GMRT
Data acquisition Real-time data recording (32
node quad-core dual-CPU cluster at the GMRT)
  • For raw data recording mode, total data rate to
    disk is 1.8 Gsamples / sec ? 500 Mbytes/sec
    (at 2 bits / sample)
  • Transfer recorded data to a large compute cluster
    for off-line analysis e.g. to the cluster at
    Pune campus, using a dedicated 4 Mbps dedicated
    link over fibre from GMRT to Pune
  • Run off-line analysis to do the correlations and
    also to produce multiple phased array beams
    (total required is few hundred beams)
  • Carry out the pulsar search analysis for each
    beam output ? 100 x increase in the
    computation load, for data acquired in the same
    duration !
  • Running this application is a major CHALLENGE
    for High Performance Computing !!

Dedicated 4 Gbps link
Off-line data read-back Distributed data
analysis (NCRA Pune Main Compute Cluster )
20
Another Software Correlator LOFAR Blue
Gene
The LOFAR Radio Telescope A pan-European
effort
21
LOFAR Blue Gene
The LOFAR Radio Telescope uses an
off-the-shelf supercomputer (The BLUE GENE from
IBM) to implement a correlator !!
The IBM Blue Gene Supercomputer
22
The LOFAR Correlator Layout
23
The LOFAR Correlator Specifications
24
Future Projections The SKA
  • The Square Kilometre Array (SKA) -- next big
    step in Radio Astronomy (an international
    telescope)
  • Total collecting area of 1 million sq. meters
    (about 30 times the GMRT) !
  • Will be spread over a much larger area
    thousand km !! (contintental size)

Wide-angle radio camera
radio fish-eye lens
25
Future Projections The SKA
  • Will have large range of frequencies and
    bandwidths
  • To be completed in 2020
  • estimated cost 1 billion dollars !
  • Will require astronomical signal processing ?
    PETA FLOPS !!

26
HPC for modern Radio Telescopes
The LOFAR Radio Telescope
27
Summary
  • Data Intensive computing is of great importance
    in astrophysics for SIMULATIONS, OFF-LINE DATA
    ANALYSIS and REAL-TIME SIGNAL PROCESSING
  • Multicore compute clusters 10s of TFlops
    capacity for exclusive use by astronomers (for
    off-line processing) are becoming quite common
  • Radio Astronomy involves long duration
    observations of very faint radio signals from
    celestial objects, using sensitive telescopes
    with large bandwidths.
  • It requires significant amounts of real-time
    signal processing and computing to make the
    final images from the telescopes
  • A large, modern radio telescope like the GMRT
    requires 150 GFlops of computing on data
    coming in at 2 Gsamples/sec
  • Doing the real-time signal processing using
    compute clusters has significant advantages, and
    it is now becoming technologically feasible
    e.g. the GMRT software back-end
  • New telescopes being made, will require 500
    TFlops with data rates of 600 Gsamples/s
  • The SKA -- the discovery instrument of the
    future, will ensure that radio astronomy
    requirements for real-time and off-line
    processing remain on the cutting edge of
    technology !

28
Thank You
29
CMB is a tool to study Cosmology on largest scales
30
Ongoing Planck analysis effort Joint estimation
of Cl and BipoSH coefficients using Gibbs
sampling. 90k CPU hours (30 Tflops-days/year) Stor
age 10 Tb/year
Linear transforms Linear Algebra on large
basises For each frequency channel Time ? skyNt
(10 G) ? Npix (10 M) Data compression Sky ?
Harmonic Npix ? lmax (few k)
31
Current Angular power spectrum
Qest (suboptimal)
ML (optimal)
Image Credit NASA / WMAP Science Team
32
GW Astronomy with Intl. Network of GW
Observatories
  • Detection confidence
  • Source direction
  • Polarization info.

Indian Initiative in Gravitational-wave
Observations www.gw-indigo.org
LIGO-India ?
33
IndIGO Data Centre_at_IUCAA Indian Initiative in
Gravitational-wave Observations
  • Primary Science Online Coherent search for GW
    signal from binary mergers using data from global
    detector network
  • Role of IndIGO data centre
  • Large Tier-2 data/compute centre for archival of
    g-wave data and analysis
  • Bring together data-analysts within the Indian
    gravity wave community.
  • Puts IndIGO on the global map for international
    collaboration with LIGO Science Collab. wide
    facility. Part of LSC participation from IndIGO
  • 100 Tflops 8500 cores x 3 GHz/core
  • Need 8500 cores to carry out a half decent
    coherent search for gravitational waves from
    compact binaries.
  • (1 Tflop 250 GHz 85 cores x 3 GHz / core)
  • Storage 4x100TB per year per interferometer.
  • Network gigabit backbone, National Knowledge
    Network.

Courtesy Anand Sengupta, IndIGO
34
Time Domain Astronomy
  • Real-time search in and characterization of 4-D
    data arrays
  • position (x,y), colour (wavelength), time
  • Large surveys are in the offing at many places
    across the world including India. Indian
    interest will include the processing of data from
    local as well as some of the international
    facilities
  • Need both large network bandwidth and high
    compute power
  • Most of the computation will be for automatic
    detection, characterization and classification of
    transient events, on which the decision of
    follow-up operations will be based

35
Theoretical Astrophysics Near and Medium term
projections in India
  • MHD and Hydrodynamic simulations at progressively
    higher resolution (sun, galactic dynamos,
    accretion flows, jets, cosmological structure
    formation)
  • Cosmological and stellar N-body simulations
  • Monte-Carlo and Matrix-based radiative transfer
    problems (comptonization, cyclotron resonant
    scattering, solar and planetary atmospheres)
  • Molecular structure of dust grains and their
    optical properties radiative transfer in dusty
    media astrochemistry
  • A net computational need of a few tens of
    teraflops is envisaged for these problems in
    India over the next few years
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