Data Processing forSUBARU Telescope using
GRIDYuji Shirasaki
National Astronomical Observatory of Japan
Astronomy Data Center
on behalf of the JVO Project teamContents
 Subaru Telescope and Instruments
 Virtual Observatory
 CCD Image Reduction
 Subaru GRID Data Analysis System

Subaru Telescope
SubaruTelescope isan opticalinfrared 8.2 m
telescope atHawaii,operated by
NAOJ.

Instruments for Subaru
 CIAO COMICS FOCUS IRCS MOIRCS SuprimeCam
 HDS
 AO/CIAOMOIRCSInstruments’ Field of View
160MB/shot~ tens GB/nightHyper SuprimeCam> 10 x SuprimeCamSuprimeSuprime-Cam
Size: 1035 mm x 960 mmf
Weight: 295 kg
Power: 420 W
F: 1.86
FOV: 30’ f
CCD: MIT/LL CCID20
Format: 4096x2048 per CCD# of CCD: 10 (2 x 5)
Filter: B,V,Rc,Ic,g’,r’,I’,z’SuprimeCam Field of View
SuprimeCam FOV0.2”/pix

160MB/shot~ tens GB/night

Upgrade toHyper SuprimeCam (2011?)> 10 x SuprimeCam
VIMOS/VLTWFPC2/HST

Total amount of public data
as of 2006-10-08• More than 90% of all the requests
are for SuprimeCam

Cumulative Data Volume ofSuprimeCam
Cumulative Data Size (TB)

15 TB/year

1.5 TB/year
Upgrade toHyper-SuprimeCam ?

YearSubaru Data Archive
SkyNode
JVO
Lease LineMASTARS
18 month
SMOKA

Mitaka AdvancedSTARS

Subaru Mitaka Okayama
Kiso Archive

STARS
Subaru Telescope
Archive System

STARS: a sub-system of the Subaru
Telescope, not public
MASTARS: a mirror of STARSSMOKA: public archive system
JVO: Virtual Observatory Web Portal

International Virtual Observatory
Alliance (IVOA)

 2002 Jun ~ 16 VO projects from Armenia, Australia,Canada, China, Europe, France, Germany,
Hungary, India, Italy, Japan, Korea, Russia,
Spain, the United Kingdom, and the UnitedStates.
 Uniform access to the
distributed databases
 Standard of data
access interface

Japanese Virtual Observatory (JVO)
http://jvo.nao.ac.jp/portal

 VO portal service– Federation of the Distributed

Astronomical Databases– > 160 data resources from theworld are available
 Data Analysis Service– Subaru data reduction throughthe Web interface– General astronomical data
analysisCurrent
situation
inManualastronomy （Instr.A）

Manual（Instr.B）

Manual（Instr.C）

Subaru Telescope
Data Archive（10TB）
Downloadby hand

Software for instr. A
Software for instr. B
Software for instr. C

Subaru Data Analysis
and Virtual Observatory
4. Retrieve
reduced data

User disk space

1. Request Data

3. Save thereduced data

2. Reduceraw data
JVO Portal Service

Subaru Telescope
Data Archive（10TB）

Necessity of the Resource Aggregation• Limited Data transfer rate
Bandwidth between the Data Center and each
institute is still below 100 MB/s.
• Improvement of computing power is saturating.
Just upgrading the CPU does not necessarily
shorten the computing time.
• Computing power/cost is still rapidly increasinge.g. Core 2 Quad 2.4GHzx4 US$600 (Now)
Pen4 1.8GHzx1 US$600 (2001)• Progress on the software technology
Computing Grid / Data Grid /…

Pros and Cons of Server Side
Processing● Pros:– User doesn’t need to take care about installation /update of analysis software– User doesn’t need to have a large storage– User doesn’t need to have a high-spec CPU● Cons:– User cannot modify the software

The primary target of this system is for novice user
– If unexpectedly large number of users submit jobs atthe same time, the computing time slow down.

No resolution, be patient. It may be still faster than
preparing all the resource in the local machine ?

Data Analysis in Astronomy
1.

Raw data reduction• Very complex : The reduction procedure depends on
instrument. Require the knowledge on the instrument.
• Time consuming : 10GB of data must be used to get one
image (300MB). It takes half a day to reduce datataken in one night (SuprimeCam).

2. Parameter measures from reduced data
• Relatively easy : Many kinds of open software isavailable• Problem: need to find, install, and know the software
3. Interpretation of the derived parameters• The way of the analysis depends on each science case.

SuprimeCam CCD

CCD gap
Bad pixel /Cosmic Ray
Non-uniformity

CCD Image Calibration / Reduction
Raw
Bias
Flat
Raw
Bias
CCD
Subtracted
Flat
Frame
Raw
Bias
CCD
Subtracted
Frame Raw Frame Bias
Flat
Frame
CCD
Subtracted
Frame Raw Frame Bias
Flat
Frame
CCD
Subtracted
100~1,000
Frame Raw Frame Bias
Flat
Frame
CCD
Subtracted
100~1,000 Frame
Frame
Flat
Frame
CCD
Subtracted
100~1,000Frame
Frame
1 Frame30min
100~1,000
FrameFrame130 100~1,000
min Flatfield
130 100~1,000min Frame
Flatfield
130 min Frame
Flatfield
130 minFlatfield
40~400minFrame
1Flatfield
Frame
Flatfield
Frame
Frame

10xN (N=3~100)

120 ~660 min

Mosaic Frame

One day for each observation nightComponents of the Grid system● Computing resource management– Monitoring and Discovery Service (MDS)● Data transfer– FTP or HTTP get● Remote Job execution– Web service (Tomcat + AXIS)● All the components were developed byourselves– Plan to introduce NAREGI GRID middleware

Subaru Data Analysis GRID system
5. Data Transfer FTP~30 CPU Cores

DAS
Data Analysis Service

0. DAS server periodically report
its status (load average…)

MDS
Monitoring andDiscovering
Service

1 Gbps x 11ports

JVO
Portal48 Gbps

1 Gbps x 5 ports

SRS

2. Query an available
DAS server.

DSS

3. Job submit
6. Data Transfer FTP

Storage Service
30 TB

4. Search data location on SRS

1. DataRequestFlat--field frame calculation GUIFlat

SuprimeCam Mosaic Service

MDS Service Snap Shot
Host NameHeart Beat Status
Load Average

Number of Submitted Job

Experiment (58mosaic/12CPU Core)

Raw Data6872 files (120 GB)

All the archivedDatadata（～2000 fields） can Flat-field
581 files (20 GB)
be analyzed in 4 days !
（３０CPU Cores）

Summary We developed GRID computing system for

Subaru data analysis– One night observation

One day (1CPU)  One hour
– All the archived data (6 years)

More than one year (1CPU)  One week
– Accessible from Web browser.

 Operation System will be completed nextyear.
 Experimental use of NAREGI Grid
middleware is underway