fem with parallel sql server: a case study gerd heber cornell theory center cornell fracture group
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FEM with Parallel SQL FEM with Parallel SQL Server: A Case StudyServer: A Case Study
Gerd HeberGerd HeberCornell Theory CenterCornell Theory CenterCornell Fracture GroupCornell Fracture Group
Thank YouThank You
Dan Fay (MSR)Dan Fay (MSR) Jim Gray (MSR)Jim Gray (MSR) Todd Needham (MSR)Todd Needham (MSR) Alexander Szalay (JHU)Alexander Szalay (JHU)
OutlineOutline
Parallel SQL ServerParallel SQL Server ContextContext
InfrastructureInfrastructure ApplicationApplication
ExamplesExamples ComplexityComplexity
IssuesIssues ConclusionsConclusions
Parallel SQL ServerParallel SQL Server
HardwareHardware SMPSMP Distributed memoryDistributed memory
SoftwareSoftware Query level parallelismQuery level parallelism
Partitioned views (LDPV)Partitioned views (LDPV) Linked serversLinked servers
Distributed partitioned views (DPV)Distributed partitioned views (DPV)
When to Use DPVWhen to Use DPV
Scale-out (DPV) vs. scale-up (SMP)Scale-out (DPV) vs. scale-up (SMP) Good performance on commodity Good performance on commodity
hardwarehardware Data (and queries) must be suitable for Data (and queries) must be suitable for
partitioningpartitioning Increased application complexityIncreased application complexity
Go to the server with most, or all, of the dataGo to the server with most, or all, of the data
For reliability consider failover For reliability consider failover clusteringclustering
No support for parallel (bulk) insertsNo support for parallel (bulk) inserts
CTC’s Infrastructure TodayCTC’s Infrastructure Today
Domain
Active DirectoryDatabase Servers
Web Servers
Certificate Server
Tape Robot
CaveLogin Nodes
Scheduler
Clusters
File Servers
SCTS
Basic FEM AnalysisBasic FEM Analysis PreprocessingPreprocessing
Topology/Geometry generationTopology/Geometry generation Mesh generationMesh generation Apply boundary conditionsApply boundary conditions Material propertiesMaterial properties
SolutionSolution Equation solvingEquation solving Error analysisError analysis
Post processingPost processing Data analysisData analysis
VisualizationVisualization
How We Used To Do ThingsHow We Used To Do Things
100% file-based100% file-based Monolithic (brittle) codeMonolithic (brittle) code DisconnectedDisconnected No data-sharing, except copyNo data-sharing, except copy Hard to debugHard to debug Plenty of non problem oriented codePlenty of non problem oriented code
Where We Use SQL ServerWhere We Use SQL Server
Data storageData storage AnalysisAnalysis
DebuggingDebugging VisualizationVisualization
ProcessingProcessing Checkpoint / restartCheckpoint / restart Web service state managementWeb service state management Data virtualizationData virtualization
XML repositoryXML repository
InputInput
100 MB - 1 GB (today)100 MB - 1 GB (today) Files ASCII (incl. XML), binaryFiles ASCII (incl. XML), binary Topology, geometry, meshTopology, geometry, mesh Initial / boundary conditionsInitial / boundary conditions Material propertiesMaterial properties
Input may or may not be partitionedInput may or may not be partitioned
OutputOutput Physical fieldsPhysical fields
Temperature (1x double per node)Temperature (1x double per node) Displacement (3x double per node)Displacement (3x double per node) Stress, strainStress, strain (6x double per Gauss point) (6x double per Gauss point)
Tetrahedron: 5 / 11 Gauss pointsTetrahedron: 5 / 11 Gauss points Hexahedron: 27 / 64 Gauss pointsHexahedron: 27 / 64 Gauss points
State variablesState variables Mises plasticity (13x double per Gauss point)Mises plasticity (13x double per Gauss point) Polycrystal plasticity (>= 30x double per GP)Polycrystal plasticity (>= 30x double per GP) ……
Produce 10 - 1000 times the input sizeProduce 10 - 1000 times the input size
10-3 10-6 10-9 m | s
DatasetsDatasets
Pictures provided by Paul Wawrzynek, Cornell Fracture GroupPictures provided by Paul Wawrzynek, Cornell Fracture Group
ExamplesExamples
Cracked
Closed
Visual SQLVisual SQL
Pictures provided by John Emery, Cornell Fracture GroupPictures provided by John Emery, Cornell Fracture Group
DDSimDDSim
ES7000
Spatial SearchSpatial Search Jim Gray et al., Jim Gray et al., There Goes the Neighborhood: There Goes the Neighborhood:
Relational Algebra for Spatial Data SearchRelational Algebra for Spatial Data Search, MSR-TR-, MSR-TR-
2004-322004-32
Web ServicesWeb Services
Adaptive Software ProjectAdaptive Software Project NSF-ITR #0085969: NSF-ITR #0085969:
Adaptive Software for Adaptive Software for Field-driven Field-driven Simulations (09/01/00)Simulations (09/01/00)
Implement a system Implement a system for multi-physics for multi-physics multi-scale adaptive multi-scale adaptive CSE simulationsCSE simulations Computational fracture Computational fracture
mechanicsmechanics Chemically-reacting Chemically-reacting
flow simulationflow simulation Understand principles Understand principles
of implementing of implementing adaptive software adaptive software systemssystems
Adaptivity in CSE SimulationsAdaptivity in CSE Simulations
Application-level adaptivityApplication-level adaptivity Change in modeling / governing equationsChange in modeling / governing equations Example: Elasticity PDE’s vs. molecular-scale Example: Elasticity PDE’s vs. molecular-scale
interactions, symmetryinteractions, symmetry Algorithm-level adaptivityAlgorithm-level adaptivity
Change in solution method for governing Change in solution method for governing equationsequations
Example: Finite-element vs. wavelet basesExample: Finite-element vs. wavelet bases System-level adaptivitySystem-level adaptivity
Response to changing resource availabilityResponse to changing resource availability Example: Processor / link failureExample: Processor / link failure
Test ProblemsTest Problems
(Substantial) Infrastructure(Substantial) Infrastructure
Metadata managementMetadata management State managementState management Event loggingEvent logging Data virtualizationData virtualization AccountingAccounting TransactionsTransactions
YukonYukon
NET CLR integrationNET CLR integration Stored procedures, user-defined Stored procedures, user-defined
functions, and triggers in .NET languages functions, and triggers in .NET languages (and T-SQL)(and T-SQL)
Call unmanaged (unsafe) codeCall unmanaged (unsafe) code User defined aggregates and typesUser defined aggregates and types
Native XML data type (schema support)Native XML data type (schema support) XQuery supportXQuery support Database logic can be invoked as Web Database logic can be invoked as Web
serviceservice
XML RepositoryXML Repository
Polycrystal GenerationPolycrystal Generation
Comments / Issues / WishesComments / Issues / Wishes SQL LibrariesSQL Libraries Better management tools for linked serversBetter management tools for linked servers Embedded SQL renaissanceEmbedded SQL renaissance WSE 2.0 and YukonWSE 2.0 and Yukon WS interface for WMIWS interface for WMI Template(s) for WS state and event Template(s) for WS state and event
managementmanagement O’SOAPO’SOAP
Visual SQLVisual SQL Virtualization not there (yet)Virtualization not there (yet) Data gridsData grids
ConclusionConclusion
““Language shapes the way we Language shapes the way we think, and determines what we think, and determines what we can think about.”can think about.” (B.L. Whorf)(B.L. Whorf)
It’s a slow processIt’s a slow process Most engineers are conservativesMost engineers are conservatives LegacyLegacy
SponsorsSponsors
DARPADARPA IntelIntel MicrosoftMicrosoft Microsoft ResearchMicrosoft Research NASANASA NSFNSF Northrop GrummanNorthrop Grumman Unisys Unisys
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