computational science at the renaissancecomputational...

Computational Science at the RenaissanceComputational Science at the Renaissance Computing Institute (RENCI)

Jeffrey L. TilsonResearch Scientist

Jeffrey L. Tilson, RENCI, 2008

Outline / Scopep

• RENCI and examples of collaborationp– Computational science is a team activity– RENCI. Who are we?

( ) RENCI i biliti– (some) RENCI core comp sci. capabilities– Examples of comp. sci. projects

• Close up & QuestionsC ose up & Quest o s


Computational science requires a complex set of skills

• Computational Science is the field of study concerned• Computational Science is the field of study concerned with constructing mathematical models and numerical solutions…..to solve scientific, social, and engineering problems –Wikipedia,2008

• Diverse skills required including– Parallel processing– Parallel processing– Algorithms and applied math– Grid computing/Web computing– Performance issues/monitoringg– Good programming skills– Complex debugging scenarios– etc


Teams are required ford t ti l imodern computational science

• Computational science is at the barycenter p yof many scientific efforts

• “at the edge” the process gets more li t d k l d f th “ i ”complicated - knowledge of the “science”

is needed• In practice, (IMO) intimate familiarity withIn practice, (IMO) intimate familiarity with

Big systems required – Parallel file systems, job managers, accounting

procedures, help systems and “knowing the systemprocedures, help systems and knowing the system vernacular”

• No one person has these skills. Team-based approaches are effective


based approaches are effective

RENCI brings team concept to computational gscience

• RENCI has scientists, comp. scientists & software , pexperts that can facilitate large-scale computational projectsW d thi ith ti i• We can do this with expertise in – Programming (C,C#,C++,Fnn,Java,Python,Perl,IEEE standards….)

– Web/Grid computing (WSDL,SOAP,Globus,Condor…)p g ( , , , )

– Extensive experience in using Big iron (Cray,IBM,clusters…)

– algorithms, parallelism (MPI,openMP…)

d t b t l d t t ( t l t )– databases, portals, data management (ontology, etc.)– and the application of these to different domains

(Physics/Chem/Bio/Climate…)


RENCI addresses state-wide problemsRENCI addresses state-wide problems

Committed teams to ensure success

• Better prediction, planning, and mitigation of disastersI t f th ll h lth f N th• Improvement of the overall health of North Carolinians

These broad areas encompass many computational activities thatThese broad areas encompass many computational activities that also align with national priorities– Mol. structure, weather models, grid computing, software

performance infrastr ct re etcperformance, infrastructure , etc.

• Leverage ideas, people, state & national resources as possible


RENCI has locations around North CarolinaRENCI has locations around North Carolina

• A Virtual Organization with a stated focus on gcomplex, multidisciplinary problems.

• Configured as a set of engagement sites– Coordinates and leverages disparate state-wide expertise

with a common goal of working together to solve problems. – Leverage RENCI physical locality to facilitate state-wide

engagement and outreach


RENCI teams support much more than l i l t ti iclassical computation science

• Arts and Humanities (Spectacular Justice)( p )

• Engineering ( e.g., Flood Sensor Networks)

• Visualization ( e.g., NO3(-) levels in soil )

• Collaboration (e.g., 2nd life, AccessGrid, etc.)

• Education (Summer Institute, tutorials)

• Fast Information mining: Shoah visual history archive

(SRB/parallel IO)

• Weather/climate: SCOOP MMRR• Weather/climate: SCOOP, MMRR

• Etc.


Computational science projects benefit from p p jRENCI team structure

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SpinOrbit CI MotifNetw ork StormSurge Theoretical Melanoma Image Medical


SpinOrbit-CI MotifNetw ork StormSurge TheoreticalChem

Melanoma ImageAnalysis

Medical

RENCI: Application of large computation to l blcomplex problems

Local “Big Iron”

International - gridsNational “Bigger Iron”

Name OpSys Arch State Activity LoadAv Mem ActvtyTime

i i i

UNC-Campus(+)- grids

barite.its.unc.edu LINUX INTEL Unclaimed Idle 0.000 248 0+03:10:05cryolite.its.unc.e LINUX INTEL Backfill Busy 1.000 249 10+19:05:[email protected] LINUX INTEL Backfill Busy 1.000 1011 10+07:45:[email protected] LINUX INTEL Backfill Busy 1.000 1011 10+07:45:27fluorite.its.unc.e LINUX INTEL Backfill Busy 1.000 1772 10+19:10:[email protected] LINUX INTEL Backfill Busy 1.000 1011 10+19:15:[email protected] LINUX INTEL Backfill Busy 1.000 1011 10+19:15:31niter.its.unc.edu LINUX INTEL Unclaimed Idle 0.000 502 0+03:20:04l il i kfill

Open Science GridOpen Science Grid


[email protected] LINUX INTEL Backfill Busy 1.010 1013 10+19:20:[email protected] LINUX INTEL Owner Idle 0.240 1012 0+00:00:[email protected] LINUX INTEL Unclaimed Idle 0.000 1012 2+18:41:[email protected]. LINUX X86_64 Backfill Busy 1.000 1950 10+19:05:[email protected]. LINUX X86_64 Backfill Busy 1.000 1950 10+19:05:14

RENCI: Experience integrating, creating & providing information and access

MotifNetwork


RENCI: Support for interpretation of complex d tdata

ImmersionImmersion

Large format a ge o adisplays

Stereo360o viewing


Examples of RENCI Comp. Science Effortsp p

• An incomplete list of computational science p pactivities.

• Cyberinfrastructure (CI)• Biomedical/Image Analysis

S t Bi l (M l )• Systems Biology (Melanoma)• Systems Biology (MotifNetwork)


RENCI cyberinfrastructure (CI) impacts science

• Biology • Video Processing

RENCI cyberinfrastructure (CI) impacts science

• Biology• Biochemistry• Genetics

• Video Processing• Earthquake Simulation• Earth SciencesGenetics

• Information and Library Science

Earth Sciences• Energy Research• Physics

• Coastal Modeling• Economics

• Molecular Dynamics

Actively working with researchers in these domains to utilize CI in their computational work


domains to utilize CI in their computational work

RENCI participates in the Open Science Grid (OSG)(OSG)

A framework for large scale distributed resource sharingaddressing the technology, policy, and social requirements of sharing

• OSG is a consortium of software, service and resource providers and researchersM b f i iti• Members are from universities, national laboratories and computing centers

• Brings computing and storageBrings computing and storage resources into a uniform grid computing environment

• Coordinates computing and t f 50storage resources from over 50

sites


RENCI leads the OSG engagement ti itiactivities

• The engagement activity for OSG has two main goals:g g y g– Help non-HEP scientists take advantage of OSG– Help university campuses deploy the resource sharing

framework for local cyberinfrastructure and connect it toframework for local cyberinfrastructure, and connect it to the national program

• Effort started one year ago, and will continue through March 2011 via new NSF grant

• Leveraged NSF activities benefits collaborators• Leveraged NSF activities benefits collaborators


RENCI/OSG engagement benefits local researchers: Biologyg g gy

• B. Kuhlman: Biology

• Designing proteins that fold into specific• Designing proteins that fold into specific structures and bind target molecules

• Millions of simulations lead to the creation of a One protein can fold in• Millions of simulations lead to the creation of a few proteins to be tested in the wet-lab

One protein can fold in many ways. This computationally designed protein switches between a zinc finger structure and

http://www.isgtw.org/?pid=1000507

a zinc finger structure and a coiled-coil structure, depending on its environment.


…. and emergency management

• B. Blanton: Coastal ModelsB. Blanton: Coastal Models• 50,000 Monte Carlo calculations that

simulate hurricane impacts on the N.C. coast. - Total run was 7 hours

Grid Usage Logs:50K jobs in 7 hours

• The second figure is the max elevation (in meters) at the 489 coastal nodes for 50K trials

• “The main point is that this was fairly easy to do, and this will allow us to explore sensitivities to track selectionsexplore sensitivities to track selections for the Flood Plain Mapping simulations.“ – Brian Blanton


… and information and library science researchy

• C. Blake: Information & Library ScienceC. Blake: Information & Library Science

• Multi-document summarization of scientific literature across disciplines

• Natural language parsing (NLP) of a large sample set (162 000) of biomedical• Natural language parsing (NLP) of a large sample set (162,000) of biomedical research papers from the TREC (Text Retrieval Conference - NIST) Genomics Track document collection.

• “Using the OSG for this task has reduced NLP analysis time for the TREC collection g yfrom weeks to only a few days. The dramatic reduction in running time has allowed us to experiment and to fix problems iteratively in the text preprocessing and NLP that would not have been possible on a multi-week time scale.”


RENCI participates in the TeraGrid: The RENCI Science Gateway


TeraGridTeraGridBioScience ApplicationsBioScience Data Sets

Info Services WS RegistryJob Mgmt, Audit, Acctng, …MetaScheduling

RENCI Hosted Web Services(BioMoby, BioMart, domain specific strong data types available)

2nd Generation Science Gateway

Pre-DevelopedWorkflowsWorkflows

Portal Web Interface Generated Java Swing Client

Taverna


TeraGrid User

RENCI builds tools to access Teragrid:The g“Generator”

• Accessed via hosting platform for scientific applications. C f f ff ’• RENCI maintains all of the IT and infrastructure surrounding the stuff that’s really

important, the scientific application• Given an XML representation of a command line application, it will generate:

– standard WSDL and web servicesstandard WSDL and web services– BioMoby WDSL and web services– Porlet UI for embedding into the web portal– Java Swing client GUI that connects to the WS layerg y

• Enables rapid programmatic and user interfaces to applications that can run on local and national resources

• The hosted web services layer enables researchers to consume the services in the environment of their choice in addition to the generated web portal and client sideenvironment of their choice, in addition to the generated web portal and client side Java UI.


RENCI efforts support Image analysis

Nancy Thomas: UNC DermatologyMelanoma detection in dermapathology imagesG l D t ti /P i f l th h i t d i l i

pp g y

Goal: Detection/Prognosis of melanoma through assisted image analysis.

Status: Just started (images were from initial exploration to assess feasibility using standard image analysis tools)

Collaborators:RENCIMarc Niethammer – Comp SciSteve Marron – Statistics

Funding: Lineberger Cancer

Dye separation

Funding: Lineberger Cancer Research

Cell boundary segmentation

Cell segmentation


RENCI efforts support biomedical efforts

Keith Kocis, MD: PediatricsGoal: Improved online monitoring and prognosis

RENCI efforts support biomedical efforts

Goal: Improved online monitoring and prognosis for patients in intensive care units

Initial algorithms in place. Targetted at 16 beds and integration of lab, patient, and ECG dataand integration of lab, patient, and ECG data

RENCI is currently assisting on scaling the system to handle 100+ beds and extending algorithms to incorporate multiple vital signs.

Collaborators:

a go t s to co po ate u t p e ta s g s

1 2 1 2Collaborators:RENCISteve Quint – Biomed EngDan Kocis – Multivariate, Inc

Funding: NC Competitiveness 0.4

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RENCI efforts support systems biology: Melanoma ResearchRENCI efforts support systems biology: Melanoma Research

William Kaufman: UNC School of Medicine

• Systemic biological models are essential to assess the interactions and complex interplay between environment and basic biological processes

• Seek to study the response of human DNA to exposure to genotoxins, such as di ti f l d tradiation from prolonged exposure to sun

• The goal is to create a biological model of the human systems of response to DNA damage that accounts for all the complex interactions among cell cycle checkpoints following exposure.

Collaborators:RENCIUNC Lineberger Comprehensi eUNC Lineberger Comprehensive

Cancer CenterFunding: NSF


Melanoma work: Several impacts on healthp

• Increase our understanding of cancer chemotherapy, human aging g py, g gand birth defects

• Lead to new strategies for protecting humans from genotoxins that i DNA d i lltrigger a DNA damage response in cells.

• As the complex organization and structure of the systems of response to DNA damage are established more effective therapiesresponse to DNA damage are established, more effective therapies and intervention strategies can be designed.


RENCI efforts support melanoma data interpretationpp p

• RENCI is developing visualization t l t t d th t ttools to study the systems response to DNA damage based on the integrated genomic data.

• Human protein Interactions via homolog mapping.

• Integration of SGD, BIND, BIOGRID, REACTOME, HPRD, CPATH

Yeast protein interactions

Inferred human t i i t ti

Homolog mapping


protein interactions

RENCI makes information accessible:

http://idea renci orghttp://idea.renci.org


RENCI efforts support systems biology: Genome interpretation &

evolution

Eric Jakobsson: UIUC/NCSA

• Evolutionary and functional relationships among biological molecules are typically

expressed as relationships among genes (and the proteins that the genes code for)

Our developments go beyond those relationships to reveal relationships among

functional domains (components of the genes that impart distinctive properties of

structure, regulation, catalysis, and transport)

• Leverages substantial levels of computation to create the data sets

Collaborators:Collaborators:RENCIGloria Rendon (NCSA), Mao-Feng

Ger (UIUC)www.motifnetwork.org


Funding: NSF

Visual Example of Domainsp

• KVAP (pdb-id: 1or2)• K channel voltage sensor (complex)K channel voltage sensor (complex)

• Domains from Interpro/Seg• Modular nature of proteins


RENCI co-develops the MotifNetworkp

Comprehensive transformation of sequenced genomes into “domain space”

– Workflows: A suite of several pre-built workflows that perform sequence – domain

genomes into domain-space

transformations– Services: Created to access

remote applications / Use & Hide GlobusGlobus.

– Applications: Usually community standard codes


MotifNetwork: Exploits HPC and grid-services


MotifNetwork provides several data productsp p

• Data file– Protein-Motif links– Interpro scoresInterpro scores

• eScore– Sequence locations

• (start and end bps)

• Import into Excel• Sometimes

• Human Matrix ~50,000x5,000x2 elements


Figure 2. Importing a MotifNetwork file into Excel for further quantitative analysis

MotifNetwork generates visual data products llas well

Domain-Domain DApis Mellifera DataApis Mellifera


The resultant Domain-Domain webis scale-free in the number of connections

RENCI enables a multistep MotifNetwork i lipipeline

Scan Step0.5-1K servers Parallel Processing

Step - 1-2K procs

Domain-Domain web

Step 1 2K procs

Computation/Data mining:Identify domains

Protein-Domain network

webSequences /

Genome

One or moredomain webs

Combine multiple

TBD


pDomain-Domain websFinal merging of webs

RENCI leverages HPC/grids for fast Run TimesRENCI leverages HPC/grids for fast Run Times

• On non-dedicated machines• ~128-256 cores – ~1.25-2.5 TFlops/s

– A motif list: 204,308 (small) seqs: 28.3 hrs– Yeast: 6,714 seqs: 6.4 hrs (1049 seqs/hr)– Bee: 25,707 seqs: 13.5 hrs (1904)– Mouse: 34,966 seqs: 21.3 hrs (1642)Mouse: 34,966 seqs: 21.3 hrs (1642)– Human: 70,509 seqs: 32.7 hrs (2156)

• ~ a genome per day per TFlop/s.


RENCI provides expertise in HEP projects:Quantum Chromodynamics (QCD)Quantum Chromodynamics (QCD)

Quark(on Lattice sites)

• Quantum Chromodynamics (QCD) is a

Gluon(on Links)

• Quantum Chromodynamics (QCD) is a theory of the strong force (one of the 4 fundamental forces in nature)

• Mathematically QCD written as set of 4 dim coupled non-linear differential eqnsp q

• Solve by partitioning space-time into increasingly finer 4 dim lattices

• Place the quarks (or quark/anti-quark pair) on lattice sites and gl ons that bind theseon lattice sites and gluons that bind these quarks together on the links between sites

• Let the quarks and gluons interact within the eqns of QCD over many numerical time steps

• Measure various probabilities and expectation values of observables (ex. particle masses)

F di DOE


Funding: DOE

RENCI analyzes performance for QCD Projectsy p j• Performance tuning of HPC codes

– QCD simulations can take years of cpu time– Need high efficiency terascale and petascale level HPC systems– These computational requirements make it essential to understand the run

time characteristics of QCD applications– RENCI is developing new software tools for performance studies within theRENCI is developing new software tools for performance studies within the

QCD environment – Goal is to develop performance tools to tune QCD applications for best

communication, computation, and memory usage

• Visualization of QCD observables and measurements– Data from numerically solving the differential eqns of QCD too complex to

visualize globally from the data itselfg y– Developing new programs to utilize the extensive RENCI visualization

capabilities to visually track and observe how measured quantities in QCD interact and evolve over time


Let’s collaborate• RENCI is involved in many collaborations in

computational science– Only a few examples have been shown

– Computation support– Data/storage support– Visualization support– Performance-centric support

• Physics, Chemistry, Biology, Medical …

RENCI i t l i l d i th ll b ti• RENCI is strongly involved in other collaborations as well

– That is a talk for a different time.

• We welcome discussions on how to collaborate with you


Thank You & Questions

“We are perhaps not far removed from the time when we shall be able to submit the bulk of chemical phenomena to calculation.”p

J.L.Gay-Lussac, Memoires dela Society d’Aroueil 2, 207 (1888)

“The general theor of q ant m mechanics is no almost complete the diffic lt is onl that“The general theory of quantum mechanics is now almost complete…the difficulty is only that the exact application of these laws leads to equations much to complicated to be soluble…”P.A.M. Dirac, Proceedings of the Royal Society, Volume 123A (1929)

Computer-based simulation enables us to predict the behavior of complex systems that are beyond the reach of our most powerful experimental probes or our most sophisticated theories. DOE Office of Science Strategic Plan, 2004. g ,

April, 2008: Where are we now ?


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