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Computational Science and Engineering at Berkeley. Jim Demmel EECS & Math Departments 20 Jan 2009. 4 Big Events. Establishment of a new graduate program in Computational Science and Engineering (CSE) - PowerPoint PPT Presentation


  • Computational Science and Engineering at BerkeleyJim DemmelEECS & Math Jan 2009

  • 4 Big EventsEstablishment of a new graduate program in Computational Science and Engineering (CSE)Multicore revolution, requiring all software (where performance matters!) to changeParLabNew Buildings to house research activitiesCITRIS and CRTCloud computingRadLab

  • OutlineNew Designated Emphasis in CSEGoalsParticipants (112 faculty so far)Resources and OpportunitiesCourse StructureA few research projects

  • Designated Emphasis (DE) in CSENew graduate minor started July 1, 2008MotivationWidespread need to train PhD students in CSEOpportunities for collaboration, across campus and at LBNL18 (20) departments, 85 (112) faculty signed up (so far)Graduate students participate byGetting accepted into existing department/programTaking CSE course requirementsQualifying examination with CSE componentThesis with CSE componentReceive PhD in X with a DE in CSEDetails at

  • Participating Departments (1/2) ( # faculty by primary affiliation, # courses )Astronomy (7,3)Bioengineering (3,1)Biostatistics (2,0)Chemical Engineering (6,0)Chemistry (8,1)Civil and Environmental Engineering (7,8)Earth and Planetary Science (6,3)EECS (19,14)IEOR (5,5)School of Information (1,0)

  • Integrative Biology (1,0)Materials Science and Engineering (2,1)Mathematics (15, 4)Mechanical Engineering (9, 6)Neuroscience (7,1)Nuclear Engineering (2,1)Physics (1,1)Political Science (2,0)Statistics (5, 11)New: Biostatistics, Public HealthParticipating Departments (2/2) ( # faculty by primary affiliation, # courses )

  • Resources (1/4)Executive Director Masoud NikraveshMoneyAnnual for staff supportOne time, for course developmentCITRIS Research initiation fundsAccess to corporate partnersGSI support, broadcast to other campuses

  • Resources (2/4)SpaceCITRIS Building - early 2009staff offices, seminar, machine room (1400 sq ft)LBNL CRT Building - 2011

  • New Building to Support CSEat UC Berkeley and LBNL$112M, 32K ft2 computer room, 45K ft2 office spaceMove in 2011

  • Resources (3/4)Existing computing resourcesEECS clusters - www.millennium.berkeley.eduGetting oldLBNL / NERSCCS267 class accountsStart-up allocations on supercomputersNeeds to be of potential interest to DOEPotential new resourcesYahoo,

  • Resources (4/4)LBNLBesides space and cycles: Expert CSE advice, collaborators, short coursesInternships for students (grad or undergrad)MSRIWorkshops, short courses

  • Course Structure3 kinds of students, course requirementsCS , Math, ApplicationsEach kind of student has 3 course requirements in other two fieldsGoal: enforce cross-disciplinary trainingNon-CS & Non-Math students:1 or 2 Math courses from list1 or 2 EECS courses from listOther classes from Math, Stat, IEORMath & CS students: substitute 1 or 2 courses from applied department for 1 or 2 insideMay distinguish EECS and CS studentsWe have $ to support new course development

  • EECS Courses (so far)CS267 Applications of Parallel ComputersCS270 Combinatorial Algs. & Data StructuresCS274 Computational GeometryCS280 Computer VisionCS281A Statistical Learning TheoryCS281B Learning and Decision MakingCS284 Geometric Design and ModelingCS285 Solid Modeling and FabricationCS294-10 VisualizationEECS225AB Digital Signal and Image ProcessingEECS227A Convex OptimizationEECS228B Convex Approximation

  • Other Computational Courses (1/6)MathematicsMa 221 - Numerical Linear AlgebraMa 228AB - Numerical Solution of Differential EquationsMa 220 - Probabilistic MethodsNew course being developedIndustrial Engineering and Operations Research IEOR 261: Experimenting with Simulated SystemsIEOR 262AB: Mathematical ProgrammingIEOR 264: Computational OptimizationIEOR 269 Integer Programming and Combinatorial Optimization

  • Other Computational Courses (2/6)

    Statistics Stat 215AB: Statistical Models: Theory and ApplicationStat 230A: Linear ModelsStat 232: Experimental DesignStat 240: Nonparametric and Robust MethodsStat 241A: Statistical Learning Theory (same as CS281A)Stat 241B: Advanced Topics in Learning and Decision Making (same as CS281B)Stat 244: Statistical ComputingStat 245AB: Biostatistical MethodsStat 246: Statistical GeneticsStat 248: Time Series Analysis

  • Other Computational Courses (3/6)AstronomyAstro 202: Astrophysical Fluid DynamicsAstro 204: Numerical Techniques in AstronomyAstro 255: Computational Methods in Theoretical AstrophysicsBioengineeringBE 243: Computational Methods in BiologyChemistryChem 220AB: Statistical MechanicsChem 221AB: Advanced Quantum MechanicsChem 295: Molecular Simulation

  • Other Computational Courses (4/6)

    Civil and Environmental EngineeringCEE 200A: Environmental Fluid MechanicsCEE 200B: Numerical Modeling of Environmental FlowsCEE 221: Nonlinear Structural AnalysisCEE 222: Finite Element MethodsCEE 224: Computer Aided EngineeringCEE 229: Structural System ReliabilityCEE 233: Computational MechanicsCEE 234: Computational InelasticityEarth and Planetary ScienceEPS 204: Elastic Wave PropagationEPS 206: Geophysical Inverse MethodsEPS 236: Geological Fluid Mechanics

  • Other Computational Courses (5/6)Electrical Engineering and Computer SciencesEECS 219A: Computer-Aided Verification of Electronic Circuits and SystemsEngineeringE 266A: Finite Difference Methods for Fluid DynamicsE 266B: Spectral Methods for Fluid DynamicsMaterial Science and EngineeringMSE 215: Introduction to Computational Materials ScienceMechanical EngineeringME 280A: Introduction to the Finite Element MethodME 280B: Finite Element Methods in Nonlinear ContinuaME 287: Multiscale Modeling the Design of New MaterialsME 290D: Solid Modeling

  • Other Computational Courses (6/6)Molecular and Cell BiologyC 246: Topics in Computational Biology and GenomicsMCB 262: Computational NeuroscienceNuclear EngineeringNUC 255: Numerical Methods for Reactor AnalysisPhysicsC 203 Computational NanosciencePlant and Microbial BiologyPMB 200B: Genomics and Computational Biology

  • More on possible new courses (1/6)Possible obstacles to studentsLong prerequisite chainsImportant material spread over multiple coursesRepetition of basic material in multiple courses23 faculty identified following needs, opportunities:New 3 unit survey course in numerical methods23 new 1-unit classes with this as prerequisiteSegmented courses where one can take subset for fewer

  • More on possible new courses (2/6)Numerical Methods Course (3 units)Boil down Math221, Ma228AB, other material into onePossible text by Heath (UIUC)Linear & nonlinear equationsEigenvalue/vector problemsOptimizationInverse problemsNumerical integration, interpolationFFTODEs, PDEs

  • More on possible new courses (3/6)Possible new 1 unit coursesApplication of spectral methods to fluid flows Boundary element methods Climate modelingCollisionless shock waves and PIC plasma simulationComputational AstrophysicsContact MechanicsFinite ElementsBoundary integral methods for elliptic PDEFinite dimension (control) systems

  • More on possible new courses (4/6)More possible new 1 unit courses Fourier transforms and waveletsImaging, color issues, multidimensional PDFsInterface techniques and level setsLarge eddy simulationsLattice-Boltzmann MethodsMaximum likelihood, least squares, median fittingMesoscale atmospheric boundary layer modelingMonte Carlo methodsMultiscale modeling and design of new materials

  • More on possible new courses (5/6)Still more possible new 1 unit coursesNumerical optimizationPrincipal component analysis of climate dataSparse matrix computationsTurbulence modeling for stratified flowsVisualization

  • More on possible new courses (6/6)Segmented 3-unit courses Parallel Computing (CS267)Numerical solution of differential equations (Ma228AB)

    At least $50K available to support new course development (thanks to Deans Richards & Sastry)

  • Possible Research Topics (1/2)A small selection from among the 112 facultySome require tightly coupled computing, some ok on cloudAstronomy (10 faculty)Some simulations (large scale, many smaller scale), some large data sets (up to terabytes/day) Chemistry and Chemical Engineering (12 faculty)Some large-scale simulations, some less tightly coupledEx: New materials for energy via QMC, chemical database screeningNeuroscience and Cognitive Computing (8 faculty)Some large scale simulations (of brain, auditory system)Some large data set analysis (

  • Possible Research Topics (2/2)Computational systems biology (9 faculty)Digital Human, many layers of simulationEcon/EECS/IEOR/Math/PoliSci/Stat (9 faculty)Statistical analysis and visualization of large scale heterogeneous data bases of economic, financial, social dataEx: for news analysisEconomics (8 faculty, including 1 Nobelist)Econometric and social modelingUltra-efficient Climate Computer (7 faculty + staff)Joint with LBNL 100x lower power than current supercomputers

  • Extra Slides

  • Challenges/opportunities for using Clouds for HPCNeed to gang schedule processorsBatch schedulers for clusters well understood, but need to run in cloud environmentNeed interface to run MPI jobsAutotuningPatterns/Motifs/Dwarfs for CloudsPicking best algorithm no matter which resourcesImpact of likely higher latency, lower bandwidthResearch in novel communication-avoiding algorithmsSome jobs access large databasesUp to terabytes/day generated

  • Managing the DEStandard By-Laws in Sec. E of proposalNominating CommitteeExecutive CommitteeAdmission


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