paul alexander, peter hall design issues and implementation challengesaavp 2010 design issues and...
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Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
Design issues and implementation Design issues and implementation challengeschallenges
Paul Alexander and Peter Hall
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
Aim and scopeAim and scope
•Concentrate on the design issues for SKA1
SKA1 AA-low is a (transformational) world leading instrument Essential to design for SKA1
Consider how to transition to SKA2
•Identify issues which are independent of detailed design Then consider issues which drive detailed design
•Aim is to pose questions that we can aim to make progress on during the course of this meeting
Some questions should be answered
•General point: Transition from a research programme to an instrument project
means we need to retire questions with an accountable path of how and why the decision was reached.
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
SKA-lowSKA-low
• Excellent learning platforms in pathfinders– LOFAR, MWA, ...
– Science, engineering, project management, operational lessons
• Why optimize SKA-low?– Evolving science case
• Possible new specification optimization
– Pathfinders not scalable to SKA-1• e.g. LOFAR x10 > SKA-1 budget
– Rapid technology changes• Verify or change long-standing assumptions
– Cost optimization funds new capabilities• More independent FoVs, increased time domain processing, ...
– Actual SKA site conditions impact SKA-low design significantly
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
SKA-low designSKA-low design
• SKA-low is part of bigger SKA system– Specifications flow from (updated) SKA Design Reference
Mission– Performance/cost analysis must be done in SKA design
environment– Cost must reflect “total cost of ownership”– SKA environment must capture key AA-lo issues
• SKA operational model is critical to costing, e.g. – Simultaneity of SKA-low & SKA-mid operations
• Data transmission, signal + post-processing
– Data archiving– Site infrastructure constraints and costs
• Including energy availability and cost
– Support model, and lifetime costs (“maintenance”)
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
Top level issuesTop level issues
Insensitive to detailed designInsensitive to detailed design
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
Basic specificationsBasic specifications
•A low-frequency sparse aperture array with A/Tsys of up to 2000 m2/K At what frequency is this optimised (100MHz?) ?
•Operating at frequencies between 70 and 450 MHz At what range of frequencies is this optimised How tight are the constraints both scientifically and technically?
•Array will be centrally condensed but some of the collecting area will be in stations located out to a maximum baseline length of 100 km from the core
What fraction of the collector is on longer baselines? How large is the core?
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
Possible trade-offs Possible trade-offs (cost constrained design)(cost constrained design)
• Built area vs FoV– More area, or more accessible and/or processed FoV?
• Accessible bandwidth vs sensitivity– Fewer compromises in a narrower band array
• Accessible bandwidth vs polarization capability, polarimetry performance
• Processed FoV, bandwidth vs other parameters– Optimum investment in data transmission, DSP, computing– Investment level as a function of time
• U-V coverage vs other parameters– More stations are costly (e.g. infrastructure, correlation)– Station numbers and size related to calibration strategy (esp.
ionospheric)
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
Frequency range 6.5:1Frequency range 6.5:1
What frequency range must the array elements be designed/optimised for?
• Approach 1: Observatory
• Aim for best “average” or “uniform” response across the frequency range
• Approach 2: Observatory, but prioritising EoR
• Design antenna for good performance in EoR frequency range
• What is the EoR frequency range 70 – 200 MHz? What about foregrounds?
• Approach 3: EoR instrument with observatory function
• Optimise design for EoR frequency range
• Approach 4: Identify the technical difficulties and relax frequency range
• 100-450 MHz is only 4.5:1
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
Sky coverageSky coverage
ALMA
45 degree scan
30 degree scan
• Critical design driver for element• Observatory requirement – large sky coverage lower gain antenna larger
scan angle of 45 degrees. What is largest scan angle we would like?• Dedicated EoR experiment perhaps require smaller scan angle higher
gain antenna possible
Circumpolar limit
GC SKA1
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
AsideAside
SKA1 specification is for an amazing instrument
~ 1 order of magnitude in sensitivity
~ 2-3 orders of magnitude in survey speed
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
Sensitivity requirementSensitivity requirement
Design specification: 2000 m2/K
f Tsky (K) Aeff (km2)
100 MHz 988 2.1
150 MHz 350 0.70
• We will be building approximately a square kilometre of collecting area
• What sensitivity do we require across the band?
• Very dependent on the frequency at which the array becomes sparse
• Major impact on element design
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
Tailoring the AA systemTailoring the AA system
100
10
1
100
1000
Frequency (MHz)
Sky
Brig
htne
ss T
empe
ratu
re (
K)
Aeff
Aeff/Tsys
Fully sampled AA-hi
Sparse AA-lo
TskyBecoming sparse
Ae
ff / Tsys (m
2 / K)
AA frequency overlap
Dishoperation
f AA f max
10000
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
SKASKA11 sensitivity model sensitivity model
2000 m2/K at 100 MHzTrec = 60 KAA sparse above 150 MHz
2000 m2/K at 100 MHzTrec = 60 KAA sparse above 150 MHz
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
TTsyssys across the band across the band
Matching
f Tsky (K)
100 MHz 988
150 MHz 350
180 MHz 221
210 MHz 150
240 MHz 106
400 MHz 29• Trec important even at 200 MHz
• Dominant at upper end of band
• True low-noise LNAs still important
Challenges: “Matching” across the band to ensure Trec dominated at upper end and Tsky at lower
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
SKASKA11 survey speed survey speed
2000 m2/K at 100 MHzTrec = 60 KAA sparse above 150 MHzNB gives 100 sq degrees across band
2000 m2/K at 100 MHzTrec = 60 KAA sparse above 150 MHzNB gives 100 sq degrees across band
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
Survey speedSurvey speed
• What survey speed do we require at fixed Aeff/Tsys?
• Direct implication for cost of correlator and post-correlator
processing
• See next section for possible trade off
• Upgrade path
• Increasing survey speed is perhaps easiest designed in
upgrade path for AA-low
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
Data rateData rate
• Data rate and survey speed intimately linked
• Review basic design equations
Re-write in terms of FoV and total collecting area
B
D
Ns Stations
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
SKASKA11 data rates and configuration data rates and configuration
• AA Line experiment 50 AA-low stations
• 100 sq degrees, 10000 channels over 380 MHz bandwidth
3.3 GS/s
• Issues
• What data rate can we process?
• Trade UV coverage (Ns) for FoV and hence survey speed ()
• Line vs continuum requirements
• What is the longest baseline
• What temperature sensitivity do we need and on what scales
Defines filling factor in the core
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
SKASKA11 configuration configuration
Ideally – do not design in these trade-offs
Need to consider evolution of processing capability in designing configuration
Or even repositionable antenna positions?!
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
Station and element designStation and element design• One or two elements?
• Many aspects to this – see later
• How sparse can the station be?
• Side lobes even for a random configuration when very sparse
• Complicates imaging, and increases Tsys
• Station size?
• Increasing D reduced UV coverage, reduced
processing load, less complicated ionospheric
model, move DSP from correlator to station B/F
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
Station designStation design
regular triangular sparse
thinned circular random
Embedded element pattern Random
minimum / 2Random
minimum 2
R1
R2
R3
Nima and Eloy
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
Configuration, station design Configuration, station design and SKAand SKA22
• Is SKA1 a subset of SKA2
• Should we compromise the design
(and hence science return) of SKA1
to ease implementation of SKA2?
• Optimum SKA1 AA-low core may have f ~ 0.5 Dcore ~ 1km.
SKA2 AA-low core is larger with f ~ 1
Almost certainly need to reposition elements on SKA1 SKA2
Do not compromise design of SKA1 maximise science return for SKA1 & accept additional cost in SKA2
Inner (20%)
Core (50%)
Mid (30%)
500 m
2500 m
180 km
Not to Scale
SKA Phase 1 Array Distribution
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
SKA information and data systemSKA information and data system
Imaging processor
Visibility processors
Science product archive
Local science
reduction
Science proposal
Data product distribution
Data routing
Col
lect
ors
Grid science reduction and visualisation
Monitor and Control system
M&C database
Global and local sky model
Calibration loop
Observation definition
Ae
Ae
Ae
TileProcessor
- hi
TH_0
TH_1
TH_n
TileProcessor
- lo
TL_0
TL_1
TL_m
StationProcessor
0e/o
e/o
e/o
e/o
…..
…..
o/e
o/e
o/e
o/e
o/e
o/e
o/e
o/e
……
.
e/o
e/o
e/o
e/o
Station Processor n
……
.
Lon
g d
istance drivers
…..
o/e
o/e
o/e
o/e
o/e
o/e
e/o
e/o
e/o
e/o
e/oe/oe/oe/o
Lon
g d
istance drivers
…..
Lon
g d
istance drivers
…..
....
…..
1.0-1.4GHzanalogue
1.0 GHzanalogue
12 f ibre lanes @10Gb/s each
……
…...
12 f ibre lanes @10Gb/s each
10Gb/s f ibre
…..
Max 4 Station Processors
Local Processinge.g. Cal; pulsars
To C
orre
lato
r
Inputs #: 1296Channel rate: 120Gb/s
(raw)Total i/p rate: 1.5 Pb/s
Typical:AA-hi tiles: 300AA-lo tiles: 45Total: 345I/p data rate: 42Tb/s
Notes:1. No control network shown2. Up to 4 station processor systems can
be implemented in parallel3. Data shown are raw, typ. get 80% data
Hierarchical station beam
former
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
Processing – how much Processing – how much and where?and where?
• For a given sensitivity and survey speed we can decide where and how to
do the processing
Beam forming vs correlation survey speed vs imaging fidelity?
• Physical location of processing
Physically distribute processing only if it leads to a reduction in data
rate
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
Processing – how much Processing – how much and where?and where?
• For a given sensitivity and survey speed we can decide where and how to
do the processing
Beam forming vs correlation survey speed vs imaging fidelity?
• Physical location of processing
Physically distribute processing only if it leads to a reduction in data
rate – e.g. Station beamformer
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
Specific Design and Specific Design and Implementation IssuesImplementation Issues
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
Element and communicationsElement and communications• Can we cover band with a single element?
Where are the compromises?
Can we afford two elements?
• Where do we digitise
Link, power consumption, lightning protection ...
• What is the communication link?
Cost, calibratability and lightning protection
• How is the element powered?
Cost, sustainabilty, manufacturability and deployability
• What is the element assembly and how are they deployed?
Cost, sustainabilty, manufacturability and deployability
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
Station B/F and correlatorStation B/F and correlator• Station B/F
What is, and can we meet the power budget with an all digital
design?
Do we deploy ASICs in the SKA1 design? If so what are the
timescales for development cycle.
Note cost of Station B/F dominated by number of elements not
how they are deployed (e.g. Station size)
Internal station correlation for calibration?
• Correlator
Is a software correlator possible or desirable for SKA1 or
commissioning?
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
Post-correlator processingPost-correlator processing
What is our system concept for SKA1 processing?
o Is the post correlator processing a single Peta-scale
machine or machine designed for our data flow?
Our problem is highly parallel in places and we could
deploy a “UV-processor”
Need to be sure of processing model to
go down this route, but can deliver more
Flops cheaply
Single-pass algorithms will reduce cost do we
want to restrict ourselves in this way?
Subtract current sky model from visibilities using current calibration model
Grid UV data to form e.g. W-projection
Major cycle
Image gridded data
Deconvolve imaged data (minor cycle)
Solve for telescope and image-plane calibration model
Update current sky model
Update calibration model
Astronomicalquality data
UV data store
UV processors
Imaging processors
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
Cost controlCost control
Item Advantage Challenge
One element Single core, one RF chain
Adequate performance across band; sparcity at high f
Larger station size Reduce cost of correlator, infrastructure and post-processor
Loss of UV coverage
ASICs deployed in DSP
Power reduction saves on operating budget
Time to deployment, commissioning harder? Loss of flexibility
Custom processing path
Maximise Flops for cost
Loses flexibility
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
SKA-low implementation SKA-low implementation challengeschallenges
• Low capital cost– N x 100,000 active antennas integrated, reproducible– Strong incentive to incorporate Design for Manufacture early in
development cycle
• Low operating cost– Easily dominates capital cost over life of SKA– Reliability and maintainability are crucial
• Probably dominant aspect of designing “outdoor” portion SKA-low
– Robust system is essential• Damage limitation strategies (lightning etc), intelligent and resilient processing
• Low deployment cost (next slide)
• Data processing and archiving prominent in SKA Observatory plan
• EMC– SKA-low is especially vulnerable to poor EMC practices, or poor site
management with respect to RFI
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010
Deployment challengeDeployment challenge
• 300,000 elements (or tiles) deployed over 2 years – 1 element/tile every minute!
• Connectivity and commissioning need to keep pace with deployment
• Parallel, industrialized deployment needed– … and during pre-construction
• Substantial site specific and environmental issues• “Design for deployment” essential
– Results in highly modular, maintainable design
Paul Alexander, Peter HallDesign Issues and Implementation ChallengesAAVP 2010