Astrophysical Applications on Superclusters Matthew Bailes Swinburne Centre for Astrophysics and Supercomputing.

Slides:



Advertisements
Similar presentations
Clusters, Grids and their applications in Physics David Barnes (Astro) Lyle Winton (EPP)
Advertisements

The Australian Virtual Observatory e-Science Meeting School of Physics, March 2003 David Barnes.
♦ Commodity processor with commodity inter- processor connection Clusters Pentium, Itanium, Opteron, Alpha GigE, Infiniband, Myrinet, Quadrics, SCI NEC.
Beowulf Supercomputer System Lee, Jung won CS843.
Low-Frequency Pulsar Surveys and Supercomputing Matthew Bailes.
Performance Analysis of Virtualization for High Performance Computing A Practical Evaluation of Hypervisor Overheads Matthew Cawood University of Cape.
ASKAP Central Processor: Design and Implementation Calibration and Imaging Workshop 2014 ASTRONOMY AND SPACE SCIENCE Ben Humphreys | ASKAP Software and.
History of Distributed Systems Joseph Cordina
IBM RS6000/SP Overview Advanced IBM Unix computers series Multiple different configurations Available from entry level to high-end machines. POWER (1,2,3,4)
The Transient Radio Sky to be Revealed by the SKA Jim Cordes Cornell University AAS Meeting Washington, DC 8 January 2002.
A Comparative Study of Network Protocols & Interconnect for Cluster Computing Performance Evaluation of Fast Ethernet, Gigabit Ethernet and Myrinet.
SUMS Storage Requirement 250 TB fixed disk cache 130 TB annual increment for permanently on- line data 100 TB work area (not controlled by SUMS) 2 PB near-line.
An Introduction to Princeton’s New Computing Resources: IBM Blue Gene, SGI Altix, and Dell Beowulf Cluster PICASso Mini-Course October 18, 2006 Curt Hillegas.
MASPLAS ’02 Creating A Virtual Computing Facility Ravi Patchigolla Chris Clarke Lu Marino 8th Annual Mid-Atlantic Student Workshop On Programming Languages.
Hitachi SR8000 Supercomputer LAPPEENRANTA UNIVERSITY OF TECHNOLOGY Department of Information Technology Introduction to Parallel Computing Group.
PARALLEL PROCESSING The NAS Parallel Benchmarks Daniel Gross Chen Haiout.
The Transient Universe: AY 250 Spring 2007 Existing Transient Surveys: Radio I: Pulsars Geoff Bower.
IBM RS/6000 SP POWER3 SMP Jari Jokinen Pekka Laurila.
Real Parallel Computers. Background Information Recent trends in the marketplace of high performance computing Strohmaier, Dongarra, Meuer, Simon Parallel.
Gordon: Using Flash Memory to Build Fast, Power-efficient Clusters for Data-intensive Applications A. Caulfield, L. Grupp, S. Swanson, UCSD, ASPLOS’09.
CPP Staff - 30 CPP Staff - 30 FCIPT Staff - 35 IPR Staff IPR Staff ITER-India Staff ITER-India Staff Research Areas: 1.Studies.
1b.1 Types of Parallel Computers Two principal approaches: Shared memory multiprocessor Distributed memory multicomputer ITCS 4/5145 Parallel Programming,
Aus-VO: Progress in the Australian Virtual Observatory Tara Murphy Australia Telescope National Facility.
Cluster computing facility for CMS simulation work at NPD-BARC Raman Sehgal.
1 Lecture 7: Part 2: Message Passing Multicomputers (Distributed Memory Machines)
Better answers Compaq HPTC Solutions Bruce Foster, Ph.D., MBA
Current LBA Developments Chris Phillips CSIRO ATNF 13/7/2005.
9/16/2000Ian Bird/JLAB1 Planning for JLAB Computational Resources Ian Bird.
1b.1 Types of Parallel Computers Two principal approaches: Shared memory multiprocessor Distributed memory multicomputer ITCS 4/5145 Parallel Programming,
Cluster Computers. Introduction Cluster computing –Standard PCs or workstations connected by a fast network –Good price/performance ratio –Exploit existing.
Taking the Complexity out of Cluster Computing Vendor Update HPC User Forum Arend Dittmer Director Product Management HPC April,
Amy Apon, Pawel Wolinski, Dennis Reed Greg Amerson, Prathima Gorjala University of Arkansas Commercial Applications of High Performance Computing Massive.
6/26/01High Throughput Linux Clustering at Fermilab--S. Timm 1 High Throughput Linux Clustering at Fermilab Steven C. Timm--Fermilab.
APSR: digital signal processing at Parkes Willem van Straten, Andrew Jameson and Matthew Bailes Centre for Astrophysics & Supercomputing Third ATNF Gravitational.
ARGONNE NATIONAL LABORATORY Climate Modeling on the Jazz Linux Cluster at ANL John Taylor Mathematics and Computer Science & Environmental Research Divisions.
Finding Fast Pulsars Today andTomorrow Pulsar Timing Array - A Nanohertz Gravitational Wave Telescope July 21-23, 2005 Jason Hessels McGill University.
Large Scale Parallel File System and Cluster Management ICT, CAS.
ITEP computing center and plans for supercomputing Plans for Tier 1 for FAIR (GSI) in ITEP  8000 cores in 3 years, in this year  Distributed.
THEORETICAL ASTROPHYSICS AND THE US-NVO INITIATIVE D. S. De Young National Optical Astronomy Observatory.
Pulsar surveys at Arecibo and Green Bank David Champion Gravity Wave Meeting, Marsfield, Dec 2007.
An FX software correlator for VLBI Adam Deller Swinburne University Australia Telescope National Facility (ATNF)
Looking at What We Can’t See: Pulsar Radio Observations ST 562 Radio Astronomy For Teachers By: Cecilia Huang and Joleen Welborn.
EVLA Data Processing PDR Scale of processing needs Tim Cornwell, NRAO.
Large Area Surveys - I Large area surveys can answer fundamental questions about the distribution of gas in galaxy clusters, how gas cycles in and out.
by Arjun Radhakrishnan supervised by Prof. Michael Inggs
1 SOS7: “Machines Already Operational” NSF’s Terascale Computing System SOS-7 March 4-6, 2003 Mike Levine, PSC.
A real-time software backend for the GMRT : towards hybrid backends CASPER meeting Capetown 30th September 2009 Collaborators : Jayanta Roy (NCRA) Yashwant.
APSR Matthew Bailes Swinburne University Of Technology.
Coherent Dedispersion Pulsar Timing Machines Matthew Bailes + Swinburne, Caltech, ATNF, CASPER.
COMP381 by M. Hamdi 1 Clusters: Networks of WS/PC.
Randy MelenApril 14, Stanford Linear Accelerator Center Site Report April 1999 Randy Melen SLAC Computing Services/Systems HPC Team Leader.
A Scalable Distributed Datastore for BioImaging R. Cai, J. Curnutt, E. Gomez, G. Kaymaz, T. Kleffel, K. Schubert, J. Tafas {jcurnutt, egomez, keith,
Computer Hardware & Processing Inside the Box CSC September 16, 2010.
Cluster Computers. Introduction Cluster computing –Standard PCs or workstations connected by a fast network –Good price/performance ratio –Exploit existing.
Computer Performance. Hard Drive - HDD Stores your files, programs, and information. If it gets full, you can’t save any more. Measured in bytes (KB,
Background Computer System Architectures Computer System Software.
A Practical Evaluation of Hypervisor Overheads Matthew Cawood Supervised by: Dr. Simon Winberg University of Cape Town Performance Analysis of Virtualization.
Constructing a system with multiple computers or processors 1 ITCS 4/5145 Parallel Programming, UNC-Charlotte, B. Wilkinson. Jan 13, 2016.
11 October 2000Iain A Bertram - Lancaster University1 Lancaster Computing Facility zStatus yVendor for Facility Chosen: Workstations UK yPurchase Contract.
CNAF - 24 September 2004 EGEE SA-1 SPACI Activity Italo Epicoco.
The search for those elusive gravitational waves
Berkeley Cluster Projects
Part-time pulsarS on behalf of PALFA Collaboration
Experimental tests of the no-hair theorems of black holes
Searching FRB with Jiamusi-66m Radio Telescope
BlueGene/L Supercomputer
The High Time Resolution Universe Survey Backend
TeraScale Supernova Initiative
Types of Parallel Computers
Cluster Computers.
Presentation transcript:

Astrophysical Applications on Superclusters Matthew Bailes Swinburne Centre for Astrophysics and Supercomputing

Outline No: –Linpack Mflops –latencies –bandwidths –evangelism Why a Supercluster? What is the Supercluster? How do we use the Supercluster? What does it do?

Why a Supercluster? Swinburne wants reputation. Hypothesis: –30 times the power –Six years of Moore’s law We can do problems 30x as complex as other groups.

Centre Goals: Fundamental Research. Public Outreach and Education. Commercial Supercomputing. –Astrophysical Special Effects –Cluster Monitoring Tools –Commercial Rendering

What is the Supercluster? Supercluster sounds better than Beowulf if you are an astronomer. Design Goals SSI I (1998): –No one component worth more than A10K –Order of magnitude more than single workstation. –Dedicated resource. (dispel various myths) –10 GB scratch/node. –10 MB/s IO node-node. –Decent fortran/C/C++ compiler.

Case Study: CSIRO Astronomy 1984: VAX 11/ : Convex C2 ( > 10 times speed up) 1995: Power Challenge ( 10 processors ) 1999: Linux Boxes Unless package supports parallelism, users won’t use clusters or even SMP/Numa unless their science is obviously constrained.

Theorists: Possess and use clusters effectively. Know what MPI is. Can’t get money.

SSI I (Jan 1998) 16 DEC 500 MHz alphas 2MB cache 192 MB RAM 13 GB disk 24-port CISCO switch MPICH/f77/C++/FFTw/emacs/gcc Zeroeth Law of Cluster Computing: Cluster Computing is inevitable if your budget is finite.

SSI II (Nov 1998). SSI I + 8 x 600 MHz DECs 4 MB cache. Corollary: Your first cluster is your happiest. First Law of Cluster Computing: Your cluster soon becomes hetereogeneous.

SSI III (March 1999) SSI II + – MHz ev6 processors –512 MB RAM/node –18 GB disk/node CISCO 5500 switch –3.2 Gb/s backplane Virtual Reality Theatrette –Seats 37 Second Law of Cluster Computing: MTBF = MTBF 0 /N

How do we use the Supercluster? Linux Workstations. (despite free OS) No batch system (just 3 “power” users). Home-grown MPI programs. C++/fortran/java.

Problems: Distributed TB disk rarely has > 10% free. MPI hangs on FPE or “p4pg” errors. CPUs too powerful for fast ethernet and tape drive on some applications. Difficult to monitor.

Applications. Neutron Star Searches. –Looked at 10% of the Southern Sky –Recorded 1.4 TB in 21 days. –1 ev56 workstation take 7 years. –SSI III took 25 days. Discovered 7 “millisecond” pulsars. –Could scale to 1000 nodes on TCP/IP. 17 MB256MBFFTSearchFoldSave

Discovery Implications: Discovered most relativistic Neutron Star + white dwarf binary known. Emit gravitational waves –Coalesce in 7 Gyr. Population of ultra- relativistic systems.

Problems. Most interesting systems are relativistic. Full sensitivity requires coherent addition. If observation time > 10 minutes, computational penalty becomes very large.

Coherent Dedispersion. Problem: –Cosmic Signals are Weak –Cosmic radio signals propagate at v!=c In 1971 new method proposed: –record electric field –Apply numerical filter to it.

What does this mean? 20 MHz = 20 MB/second. 200 times real time to process (ev6) Gives 50 nanosecond time resolution Need 7*8 hour observations to do science –One node 1.5 yr –50 nodes 9 days –1985 VAX 11/780 (one century)

Discovered? Millisecond pulsars emit short (1us wide) pulses across GHz bandwidths –Implies seed areas of 30 cm or less PSR in a 5.7 day orbit –1 Mkm in radius a-b = mm a b

Future: Search for us wide pulses in SN 1987A –25 day search HIPASS GB in < 12 hours. SSI III + servernet can mimic CSIRO’s correlator SSI IV: –ES40 + TB disk SSI V: –128 nodes + Inifiniband/servernet II?

Conclusions: Clusters are too hard to code for most astronomers. MPIwhat? Breakthroughs are possible with radical increases in computer power.