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Parallel Algorithm Oriented Mesh Datastructure

Parallel Algorithm Oriented Mesh Datastructure. Jean-François Remacle, Joe E. Flaherty and Mark S. Shephard Rensselaer Polytechnic Institute remacle@scorec.rpi.edu. Outline Basics of Mesh Representation Parallel Extensions Software issues Examples http://www.scorec.rpi.edu/AOMD.

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Parallel Algorithm Oriented Mesh Datastructure

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  1. Parallel Algorithm Oriented Mesh Datastructure • Jean-François Remacle, • Joe E. Flaherty and Mark S. Shephard • Rensselaer Polytechnic Institute • remacle@scorec.rpi.edu • Outline • Basics of Mesh Representation • Parallel Extensions • Software issues • Examples • http://www.scorec.rpi.edu/AOMD

  2. AOMD-PAOMD • AOMD and PAOMD deals with meshes • A core for basic mesh representation (topological adjacencies) • Advanced design patterns : Iterator, Observer, Visitor... • Some extensions • Parallel services : message passing, load balancing, partitioning • Meshing Toolbox : quality measures, mesh modifications, cavity mesher,… • Calculus : coordinate systems, integration <> • AOMD supports • Geometry based analysis design, classification • Parasolid, ProE, STL (not open source yet) • Hybrid meshes • Hexes, Tets, Quads … • Non conforming meshes (hanging nodes, AMR) • Curved meshes (Bézier) • AOMD is an Open Source Project

  3. Motivations • Advanced analysis techniques • Are automated with automatic mesh generation from geometric models • Employ variable order elements based on other than Lagrange basis • Use various weak forms that required alternative mesh relationships • Adaptive the mesh as the simulation proceeds • To meet these needs the mesh data structure must • Understand the relationship of mesh entities with the geometric model - ensure mesh validity and associate physical parameters with the mesh • Understand the interactions of various mesh entities - different relationships used during automatic mesh generation and analysis • Support assignment of independent geometry to the entities in the mesh - must control geometric approximation with higher order methods • Be able to associate dof to various mesh entities - provides flexibility to support variable p-order and different collections of dofs • Effectively maintain relationships during modification - needed in mesh generation, mesh adaptation and mesh modification for evolving geometry

  4. Automated Adaptive Analysis MEGA RPM Trellis AOMD-MeshSim AOMD-MeshSim AOMD Trellis FEM PUM

  5. Topological Mesh Data Structure • Classic node point coordinates / element connectivities do not meet this need • Mesh representations based on topological entities and their adjacencies fill the need: • Can be proven to be complete and unique - can effectively support all relationships and associations needed by any mesh generation or analysis procedure • Provide a shape independent abstraction for associating geometry • Effectively supports the linkage to the geometric model since systems maintain a model topology • Various approaches to support meshtopology have been taken • A new approach considered here curved mesh forp-version analysis

  6. Modern Geometric Modeling Systems • Employ non-manifold boundary representation • Provide access to model and its geometry through a geometric modeling kernel driven by topological entities • Simulation processes (mesh generation, p-version analysis...) can directly interact with the modeler

  7. Basics of mesh representation • A geometrical domain G • Is the highest level representation of the domain • is composed of geometrical entities Gid • A Mesh M • is a discrete representation of G • is composed of mesh entities Mid, i=1,… Nd(M) together with their adjacencies Mid {M q } • Mesh entities Mid • 4 different topological kinds • Vertices (d=0), edges (d=1), faces (d=2) and regions (d=3) • The unique association of a mesh entity, Midi, to a geometric model entity, Gjdj, where di<dj is denoted by • Midi Gjdj

  8. Adjacencies sets Examples of complete adjacencies sets Circular One-Level Upward Adjacenties Downward Adjacenties Face to Edge Incomplete Complete

  9. Cost of a mesh representation

  10. Memory cost of some mesh representation

  11. Higher order adjacencies • First order adjacencies • Direct access, unit cost • Full representation : only way to have all adjacencies as first order • Higher order adjacencies sets • Regions know faces : Mi3 {M 2 } • Faces know edges : Mi2 {M 1 } • Edges know vertices : Mi2 {M 1 } • Third order adjacencies sets : Mi3 {M 2 } {M 1 } {M 0 }

  12. Functionally complete representation • Minimum information • Equally dimension classified entities must be present • All vertices, all regions, all edges classified on model edgesand all faces classified on model faces • This is a sufficient minimum, not necessary but this choice allow to complete the representation without geometrical checks

  13. Basics of the Algorithm Oriented Mesh Database • Mesh entity description • A mesh entity described by a set of lower dimension entities : Mid {M q } , d > q • All vertices are always required • Vertices are atomic mesh entities, must be differentiated (e.g., using iD (Mi0) • Mesh entities comparison • Two entities are equal if their set of vertices are equal • allows to compare mesh entities (<,>,=) • Not absolutely general but key to practical implementation

  14. Downward adjacencies ordering : templates • Entity described using their boundaries • unique description i.e. non ambiguous shape • Weaker hypothesis • Need for ordering, templates • Used for computing uses • T ev and T fe • Invert templates Same vertices but different entities

  15. Mesh Entity iD • Need of search in AOMD • Add, search and remove operations are crucial • Comparing entities is always possible but ... • std::set<mEntity*, lessThanEntity>log behavior is not acceptable • Hash tables • Elements in a hash table not sorted • complexity : worst is linear, average is constant • std::hash_set<mEntity*, hashEntity, equalEntity> • Hash function needed, deterministic and stateless, a mesh entity iD • iD(M1) = iD(M2)  M1 = M2 true • iD(M1) = iD(M2)  M1 = M2 false • iD is a function of vertices for being independent of the representation • iD(M1) = iD(M2) and M1 M2 should not happen too often, efficiency of the hash table because equalEntity is to be used in this case

  16. Choice if the iD • Efficiency • Neis the number of elements • Nkis the number of keys

  17. Higher order finite elements • Counting of degrees of freedom (Szabo basis) • Stokes problem, tet mesh • Number of dofs, use previous statistics

  18. Basics of the Parallel AOMD • Basics of parallel AOMD • Partition boundaries treated like model boundaries • Equal order mesh entities must exist on partition boundaries (partition faces, edges and vertices) • Mesh vertices must have a unique global label • On processor : serial AOMD • Implementation aspects • Simplicity, no master, no owner • Round of communication standardized, no MPI calls visible, messages automatically packed

  19. Parallel AOMD - Mesh Adaptation • Target is transient applications with thousands of mesh adaptation steps • Want fast and simple adaptation • Need efficient interprocessor communications • Mesh Refinement • Apply templates • Include support of non-conforming meshes • Refined entities with remote copies must be split on all partitions • Round of communication needed to ensure unique vertex ID’s • Mesh Coarsening (will be same for local mesh modifications) • Collect all mesh entities involved onto one partition • Carry out operation using serial operators on processor

  20. Dynamic Load Balancing and Mesh Migration • Need dynamic load balancing after mesh adaptation • Procedures build on balancing procedures in Zoltan (from Sandia) • PAOMD used to provide Zoltan needed entities and connections • Load balancing procedure indicates which mesh entities are to be migrated to which processor • PAOMD only migrates minimum set, unless user specifically asks to migrate other entities classification after load balancing and before migration configuration after migration

  21. Steps in process Collect the mesh entities to be migrated to another partition Determine needed higher order mesh entities to be migrated (use AOMD to determine minimal set needed) Collect entities and any user attached data Perform communications to send entities and update links (following methods of the Rensselaer Partition Model (RPM)) Message passing At PAOMD operator level it appears messages are sent one at a time This would lead to unacceptable communication costs Message packing used - AUTOPACK (from Argonne) Automatically controls message packing process Includes information and tools to optimize message size for network architecture used Communications costs In the examples that follow communications wereon the order of 1% of the total costs Mesh Migration

  22. Implementation issues • Orientation of entities computed on the fly • Language • C++ and generic programming • STL, significant new feature of the language • Programming with concepts • C++ and OO programming • generic and OO are complementary • Trade off efficiency vs. flexibility • We believe not • Templates, functors… generic programming is efficient • Classical example, quick sort • stl::sort is 4 times faster (with VC6) than C qsort • Parallel • Autopack, automatic message packing • Zoltan, dynamic load balancing and partitioning • STL, associative containers, algorithms

  23. Mesh refinement • class AOMD_RefCallback • {public : • virtual int operator () (const meshEntity *) const = 0; • virtual void callback (std::list<meshEntity *> &before, • std::list<meshEntity *> &after • ) const = 0; • }; • Conformal or not (hanging nodes or mixed meshes) • Typically • class myAOMD_RefCallback : public AOMD_RefCallback; • AOMD:: RefUnref(theMesh, myAOMD_RefCallback);

  24. Communications • class AOMD_RoundOfComm • {public : • virtual char * sendBuffer (const meshEntity *, • int dest_proc, • size_t &sizebuf) const = 0; • virtual char * recvBuffer (const meshEntity *, • int src_proc, • size_t sizebuf) const = 0; • }; • Messages are packed (autopack) • Typically • class myAOMD_RoundOfComm : public AOMD_RoundOfComm; • AOMD::roundOfComm(theMesh, myAOMD_RoundOfComm);

  25. Load balancing • class AOMD_LBCallback • {public : • virtualchar * sendBuffer (const meshEntity *, • int dest_proc, • size_t &sizebuf) const = 0; • virtualchar * recvBuffer (const meshEntity *, • int src_proc, • size_t sizebuf) const = 0; • }; • Messages are packed (autopack) • Typically • class myAOMD_LBCallback : public AOMD_LBCallback; • AOMD::LB(theMesh, myAOMD_LBCallback);

  26. Refined to moving level function - non-conforming triangular mesh Demonstration of Load Balancing

  27. http://www.scorec.rpi.edu/DG • Desing specifications • Solve any conservation law, in any dimension, in parallel and adaptively, using any system of curvilinear coordinates, any discretization, any spatial basis and any time stepping scheme class ConservationLaw : fluxes, numerical fluxes fn and g, right hand side r, equation of state, initial and boundary conditions : the physics class Integrator : specialization's for geometrical elements class Metric : Euclidian, axisymmetric class FunctionSpace : Orthogonal or not, class Solver : forward Euler, Runge-Kutta, matrix free GMRES. • Examples • Navier-Stokes, Euler, Burgers, Maxwell-Boltzmann...

  28. Demonstration of Load Balancing

  29. 2-D Examples • 2D Rayleigh Taylor • Red (heavy), blue (light), • On left, 4 levels of refinement,On right, 2 levels of refinement, • Faster growth with more refinement as expected

  30. Linear DG elements, 30,000 to 800,000 dof Atwood Number, A = 1/3 10 fourier modes in “random” distribution time for the bubble to reach top of the window (y = 0.5) : 5 sec This calculation: alpha = 0.06 Experiments: alpha = 0.058 - 0.065 Theory (Glimm, et al) alpha 0.045 = 0.06 2-D Animation of Instability

  31. Refined 3-D Meshes for Rayleigh Taylor Instability non-conforming hexahedron mesh light fluid heavy fluid 24 steps of refinement 104 steps of refinement 72 steps of refinement

  32. Rayleigh Taylor Instability 128 processors of Blue Horizon 108 dof’s 64 processors of the PSC alpha cluster 1 106 to 2.0107 dof’s

  33. The cannon

  34. Conclusions • PAOMD advantages • Quite small piece of software, documented • Focused, mesh management only • Asks for minimum user knowledge about parallel issues • Efficient implementation • Future work • Terascale computers, more than 1000 processors (in progress, ASCI & SciDAC projects) • Anisotropic mesh refinement (in progress, with X Li) • TSTT Mesh component • Hardware heterogeneity, machine and network models have to be added in partitioners (in progress) • Modification of the design, storingless

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