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FEM with Parallel SQL Server: A Case Study

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Presentation on theme: "FEM with Parallel SQL Server: A Case Study"— Presentation transcript:

1 FEM with Parallel SQL Server: A Case Study
Gerd Heber Cornell Theory Center Cornell Fracture Group

2 Thank You Dan Fay (MSR) Jim Gray (MSR) Todd Needham (MSR)
Alexander Szalay (JHU)

3 Outline Parallel SQL Server Context Examples Issues Conclusions
Infrastructure Application Examples Complexity Issues Conclusions

4 Parallel SQL Server Hardware Software SMP Distributed memory
Query level parallelism Partitioned views (LDPV) Linked servers Distributed partitioned views (DPV)

5 When to Use DPV Scale-out (DPV) vs. scale-up (SMP)
Good performance on commodity hardware Data (and queries) must be suitable for partitioning Increased application complexity Go to the server with most, or all, of the data For reliability consider failover clustering No support for parallel (bulk) inserts

6 CTC’s Infrastructure Today

7 Basic FEM Analysis Preprocessing Solution Post processing
Topology/Geometry generation Mesh generation Apply boundary conditions Material properties Solution Equation solving Error analysis Post processing Data analysis Visualization

8 How We Used To Do Things 100% file-based Monolithic (brittle) code
Disconnected No data-sharing, except copy Hard to debug Plenty of non problem oriented code

9 Where We Use SQL Server Data storage Checkpoint / restart
Analysis Debugging Visualization Processing Checkpoint / restart Web service state management Data virtualization XML repository

10 Input 100 MB - 1 GB (today) Input may or may not be partitioned
Files ASCII (incl. XML), binary Topology, geometry, mesh Initial / boundary conditions Material properties Input may or may not be partitioned

11 Output Physical fields Produce 10 - 1000 times the input size
Temperature (1x double per node) Displacement (3x double per node) Stress, strain (6x double per Gauss point) Tetrahedron: 5 / 11 Gauss points Hexahedron: 27 / 64 Gauss points State variables Mises plasticity (13x double per Gauss point) Polycrystal plasticity (>= 30x double per GP) Produce times the input size

12 Datasets 10-3 10-6 10-9 m | s

13 Examples Pictures provided by Paul Wawrzynek, Cornell Fracture Group
Cracked Closed l Pictures provided by Paul Wawrzynek, Cornell Fracture Group

14 Visual SQL

15 DDSim ES7000 Pictures provided by John Emery, Cornell Fracture Group

16 Spatial Search Jim Gray et al., There Goes the Neighborhood: Relational Algebra for Spatial Data Search, MSR-TR

17 Web Services

18 Adaptive Software Project
NSF-ITR # : Adaptive Software for Field-driven Simulations (09/01/00) Implement a system for multi-physics multi-scale adaptive CSE simulations Computational fracture mechanics Chemically-reacting flow simulation Understand principles of implementing adaptive software systems

19 Adaptivity in CSE Simulations
Application-level adaptivity Change in modeling / governing equations Example: Elasticity PDE’s vs. molecular-scale interactions, symmetry Algorithm-level adaptivity Change in solution method for governing equations Example: Finite-element vs. wavelet bases System-level adaptivity Response to changing resource availability Example: Processor / link failure

20 Test Problems

21 (Substantial) Infrastructure
Metadata management State management Event logging Data virtualization Accounting Transactions

22 Yukon NET CLR integration Native XML data type (schema support)
Stored procedures, user-defined functions, and triggers in .NET languages (and T-SQL) Call unmanaged (unsafe) code User defined aggregates and types Native XML data type (schema support) XQuery support Database logic can be invoked as Web service

23 XML Repository

24 Polycrystal Generation

25 Comments / Issues / Wishes
SQL Libraries Better management tools for linked servers Embedded SQL renaissance WSE 2.0 and Yukon WS interface for WMI Template(s) for WS state and event management O’SOAP Visual SQL Virtualization not there (yet) Data grids

26 Conclusion “Language shapes the way we think, and determines what we can think about.” (B.L. Whorf) It’s a slow process Most engineers are conservatives Legacy

27 Sponsors DARPA Intel Microsoft Microsoft Research NASA NSF
Northrop Grumman Unisys


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