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Universit´ e de Nice - Sophia-Antipolis December 13, 2013 PhD Defense edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher

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Page 1: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Universite de Nice - Sophia-Antipolis December 13, 2013

PhD DefenseCedric Lachat

Design and validation of distributed-memory,parallel remeshing algorithms based on asequential remesher

Page 2: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

SUMMARY

Introduction

Data structures for parallel remeshing

Parallel remeshing

Experiments

Conclusion

Cedric Lachat- PhD Defense December 13, 2013- 2/55

Page 3: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

1Introduction

Page 4: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Introduction

ContextI Numerical simulations are

needed in multiple domainsincluding:

I thermonuclear fusionI aeronauticsI meteorology, . . .

I Problems become bigger andmore and more complex:numerical simulations cannot berun on a single workstation→ Want of parallelizedcomputations→ Need to distribute dataacross the processors: domaindecomposition

Cedric Lachat- PhD Defense December 13, 2013- 4/55

Page 5: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Introduction

Numerical simulation

I Space discretization:I mesh

I Finite number of points onwhich values of theproblem are computed,e.g.:

I temperatureI pressureI speed,. . .

I Solution precision dependson mesh quality:

I need for remeshing

Cedric Lachat- PhD Defense December 13, 2013- 5/55

Page 6: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Introduction

Aim of this PhD thesis

I Achieve parallel remeshing based on a sequential remesherI Devise a scalable method→ distributed memory paradigm→ communication across subdomain boundaries

I Since distributed meshes are considered, need to devise acomplete framework for handling distributed meshes andrelated computations

I Parallel remeshing requires:I to iterate on mesh components to perform local computationsI to associate values with components

→ made available to users through an APII Improve locality of accesses in memory hierarchy:

I proper renumbering of entities on each subdomain

Cedric Lachat- PhD Defense December 13, 2013- 6/55

Page 7: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Introduction

State of the art (1/2)

I Parallel partitioningI spectral [Pothen et al., 1990], combinatorial [Kernighan and

Lin, 1970, Fiduccia and Mattheyses, 1982],evolutionist [Dongarra et al., 1988]

I only multi-level [Chevalier, 2007, Chevalier and Safro, 2009]provides good efficiency and quality on big graph

I Parallel dynamic load balancingI many tools: DRAMA [Maerten et al., 1999], Zoltan [Devine

et al., 1999, 2002], PLUM [Oliker et al., 2000],ParFUM [Lawlor et al., 2006]. . .

Cedric Lachat- PhD Defense December 13, 2013- 7/55

Page 8: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Introduction

State of the art (2/2)

I Parallel remeshingI parallelize remeshing techniques [Castanos and Savage, 1996,

Laemmer, 1997, Oliker et al., 2000, Chrisochoides and Nave,2003, Casagrande et al., 2005, Lawlor et al., 2006]

I re-use of sequential algorithms [Coupez et al., 2000, Cavalloet al., 2005, Dobrzynski and Remacle, 2007, Tremel et al.,2007, Digonnet et al., 2007, Ramadan et al., 2009]

I Renumbering [Lohner, 1993, Burgess and Giles, 1997, Lohner,1998, Amenta et al., 2003, Isenburg et al., 2006, Loseille andAlauzet, 2009]

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Page 9: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

2Data structures

Page 10: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Data structures for parallel remeshing

Definitions

I Mesh:

I NodeI EdgeI Element

I Mesh representation:

I VertexI Entity

I main entity

I RelationI Enriched graph

Cedric Lachat- PhD Defense December 13, 2013- 10/55

Page 11: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Data structures for parallel remeshing

Definitions

I Mesh:I Node

I EdgeI Element

I Mesh representation:

I VertexI Entity

I main entity

I RelationI Enriched graph

Cedric Lachat- PhD Defense December 13, 2013- 10/55

Page 12: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Data structures for parallel remeshing

Definitions

I Mesh:I NodeI Edge

I Element

I Mesh representation:

I VertexI Entity

I main entity

I RelationI Enriched graph

Cedric Lachat- PhD Defense December 13, 2013- 10/55

Page 13: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Data structures for parallel remeshing

Definitions

I Mesh:I NodeI EdgeI Element

I Mesh representation:

I VertexI Entity

I main entity

I RelationI Enriched graph

Cedric Lachat- PhD Defense December 13, 2013- 10/55

Page 14: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Data structures for parallel remeshing

Definitions

I Mesh:I NodeI EdgeI Element

I Mesh representation:

I VertexI Entity

I main entity

I RelationI Enriched graph

Cedric Lachat- PhD Defense December 13, 2013- 10/55

Page 15: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Data structures for parallel remeshing

Definitions

I Mesh:I NodeI EdgeI Element

I Mesh representation:I Vertex

I Entity

I main entity

I RelationI Enriched graph

Cedric Lachat- PhD Defense December 13, 2013- 10/55

Page 16: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Data structures for parallel remeshing

Definitions

I Mesh:I NodeI EdgeI Element

I Mesh representation:I VertexI Entity

I main entityI RelationI Enriched graph

Cedric Lachat- PhD Defense December 13, 2013- 10/55

Page 17: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Data structures for parallel remeshing

Definitions

I Mesh:I NodeI EdgeI Element

I Mesh representation:I VertexI Entity

I main entity

I RelationI Enriched graph

Cedric Lachat- PhD Defense December 13, 2013- 10/55

Page 18: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Data structures for parallel remeshing

Definitions

I Mesh:I NodeI EdgeI Element

I Mesh representation:I VertexI Entity

I main entityI Relation

I Enriched graph

Cedric Lachat- PhD Defense December 13, 2013- 10/55

Page 19: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Data structures for parallel remeshing

Definitions

I Mesh:I NodeI EdgeI Element

I Mesh representation:I VertexI Entity

I main entityI RelationI Enriched graph

Cedric Lachat- PhD Defense December 13, 2013- 10/55

Page 20: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Data structures for parallel remeshing

Examples

I The same mesh can lead to different enriched graphsI Depending on the requirements of the numerical schemes

Cedric Lachat- PhD Defense December 13, 2013- 11/55

Page 21: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Data structures for parallel remeshing

Distributed mesh

I On three processors

P0 P21P

Cedric Lachat- PhD Defense December 13, 2013- 12/55

Page 22: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Data structures for parallel remeshing

Definitions

I Vertices, locally on P1:I LocalI HaloI Overlap

I Vertices, between P0and P1:

I FrontierI Vertices, globally:

I Internal

P0 P21P

Cedric Lachat- PhD Defense December 13, 2013- 13/55

Page 23: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Data structures for parallel remeshing

Definitions

I Vertices, locally on P1:I LocalI HaloI Overlap

I Vertices, between P0and P1:

I FrontierI Vertices, globally:

I Internal

P0 P21P

Cedric Lachat- PhD Defense December 13, 2013- 13/55

Page 24: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Data structures for parallel remeshing

Definitions

I Vertices, locally on P1:I LocalI HaloI Overlap

I Vertices, between P0and P1:

I FrontierI Vertices, globally:

I Internal

P0 P21P

Cedric Lachat- PhD Defense December 13, 2013- 13/55

Page 25: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Data structures for parallel remeshing

Definitions

I Vertices, locally on P1:I LocalI HaloI Overlap

I Vertices, between P0and P1:

I FrontierI Vertices, globally:

I Internal

P0 P21P

Cedric Lachat- PhD Defense December 13, 2013- 13/55

Page 26: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Data structures for parallel remeshing

Definitions

I Vertices, locally on P1:I LocalI HaloI Overlap

I Vertices, between P0and P1:

I FrontierI Vertices, globally:

I Internal

P0 P21P

Cedric Lachat- PhD Defense December 13, 2013- 13/55

Page 27: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Data structures for parallel remeshing

Global numbering

I Necessary to describe the mesh in its entirety

P0 P21P

5

1

2 9

7

4

3 6 8

10

Cedric Lachat- PhD Defense December 13, 2013- 14/55

Page 28: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Data structures for parallel remeshing

Local numbering

I Local indices are mandatory to address local data arrays

I For all local vertices onevery subdomain, verticesare indexed per entity

P0 P21P

1

1 1

12 2

1

1

1

2

I Local indices are extendedto index halo vertices aswell, e.g. with respect toprocessor P1:

P0 P21P

23

1

1

2 1 3

Cedric Lachat- PhD Defense December 13, 2013- 15/55

Page 29: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

3Parallel remeshing

Page 30: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

State of the art (1/2)

I First class of parallel remeshing techniques:I Parallelization of existing sequential remeshing techniques

I introduced in 1996 [Castanos and Savage, 1996] for 2Dmeshes

I 3D remeshing in 2000 for homogeneous meshes [Oliker et al.,2000]

I Delaunay triangulation in 2003 [Chrisochoides and Nave, 2003]I 3D remeshing for mixed meshes [Lawlor et al., 2006]

I Problems:I Difficulties to parallelize each operator of the remesherI Remeshing some element requires neighborhood informationI Too much communication between subdomains is required to

achieve quality as high as in sequential processing→ This class of parallel remeshing methods cannot handlelarge-size meshes distributed across a large number ofprocessors

Cedric Lachat- PhD Defense December 13, 2013- 17/55

Page 31: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

State of the art (2/2)

I Second class of parallel remeshing:I Re-use sequential remeshers in a parallel framework:

I introduced in 2000 [Coupez et al., 2000, Dobrzynski andRemacle, 2007]

I 3D remeshing for mixed meshes [Cavallo et al., 2005]I remeshing with hierarchical transport [Digonnet et al., 2007]I multi-grid remeshing [Ramadan et al., 2009]

→ Our approach is to generalize this class of parallelremeshing techniques so as to allow for plugging-in anysequential remesher

Cedric Lachat- PhD Defense December 13, 2013- 18/55

Page 32: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Requirements (1/2)

I How to remesh in parallel on distributed meshes?I Subdomain size could be greater than mesh size allowed by the

sequential remesher→ Need to identify in parallel non-overlapping zones ofprescribed size / workload

I Zone frontiers must be left unmodified so as to easereintegration of remeshed zones into the distributed mesh

Cedric Lachat- PhD Defense December 13, 2013- 19/55

Page 33: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Global scheme:Iterative process until all tagged elements are remeshed

1b Tagging

2 Identification

3 Extraction 4 Remeshing

5 Reintegration

1a Tagging

Cedric Lachat- PhD Defense December 13, 2013- 20/55

Page 34: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Global scheme:

1b Tagging

2 Identification

3 Extraction 4 Remeshing

5 Reintegration

1a Tagging

Cedric Lachat- PhD Defense December 13, 2013- 20/55

Page 35: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Global scheme:Tag elements which need to be remeshed

1a Tagging

Cedric Lachat- PhD Defense December 13, 2013- 20/55

Page 36: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Global scheme:

1b Tagging

2 Identification

3 Extraction 4 Remeshing

5 Reintegration

1a Tagging

Cedric Lachat- PhD Defense December 13, 2013- 20/55

Page 37: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Global scheme:

Identify non overlapping zones in parallel

2 Identification

Cedric Lachat- PhD Defense December 13, 2013- 20/55

Page 38: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Global scheme:

1b Tagging

2 Identification

3 Extraction 4 Remeshing

5 Reintegration

1a Tagging

Cedric Lachat- PhD Defense December 13, 2013- 20/55

Page 39: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Global scheme:

Extract the zones which will be remeshed

3 Extraction

Cedric Lachat- PhD Defense December 13, 2013- 20/55

Page 40: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Global scheme:

1b Tagging

2 Identification

3 Extraction 4 Remeshing

5 Reintegration

1a Tagging

Cedric Lachat- PhD Defense December 13, 2013- 20/55

Page 41: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Global scheme:Remesh in sequential each zone

4 Remeshing

Cedric Lachat- PhD Defense December 13, 2013- 20/55

Page 42: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Global scheme:

1b Tagging

2 Identification

3 Extraction 4 Remeshing

5 Reintegration

1a Tagging

Cedric Lachat- PhD Defense December 13, 2013- 20/55

Page 43: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Global scheme:

Reintegrate the remeshed zones in the distributed mesh

5 Reintegration

Cedric Lachat- PhD Defense December 13, 2013- 20/55

Page 44: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Global scheme:

1b Tagging

2 Identification

3 Extraction 4 Remeshing

5 Reintegration

1a Tagging

Cedric Lachat- PhD Defense December 13, 2013- 20/55

Page 45: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Global scheme:Tag again elements which need to be remeshed

1b Tagging

Cedric Lachat- PhD Defense December 13, 2013- 20/55

Page 46: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Global scheme:

1b Tagging

2 Identification

3 Extraction 4 Remeshing

5 Reintegration

1a Tagging

Cedric Lachat- PhD Defense December 13, 2013- 20/55

Page 47: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Requirements (2/2)

I How to determine which elements need to be remeshed?I Isotropic or anisotropic metric on verticesI Avoid elements of bad quality

I Which criteria on identified zones?I Measure zone skin size compared to zone volume:

I compute the isoperimetric quotient of the elementI value between 0 and 1I 0: worst quotient possibleI 1: optimal quotient, in the case of sphere and the

corresponding ball

Cedric Lachat- PhD Defense December 13, 2013- 21/55

Page 48: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Tagging (1/3)

1b Tagging

2 Identification

3 Extraction 4 Remeshing

5 Reintegration

1a Tagging

Cedric Lachat- PhD Defense December 13, 2013- 22/55

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Parallel remeshing

Tagging (2/3)

I User-provided mesh:I Corresponding element

graph:

Cedric Lachat- PhD Defense December 13, 2013- 23/55

Page 50: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Tagging (3/3)I Tag elements which need to be remeshed:

P0

P2

P1

P3

Cedric Lachat- PhD Defense December 13, 2013- 24/55

Page 51: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Identification (1/9)

1b Tagging

2 Identification

3 Extraction 4 Remeshing

5 Reintegration

1a Tagging

Cedric Lachat- PhD Defense December 13, 2013- 25/55

Page 52: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Identification (2/9)I Identify non-overlapping zones in parallel:

I each zone will be given to a sequential remesherI a weight is determined on each element according to the

dedicated work of the remesher→ Want of a good evaluation of the remesher work

P0

P2

P1

P3

Cedric Lachat- PhD Defense December 13, 2013- 26/55

Page 53: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Identification (3/9)

I How to compute efficiently non-overlapping zones in parallelon a distributed mesh?

I By using a graph multilevel scheme which provides very goodpartitions when combined to local optimization algorithms

Initialpartitioning

Coarsening Uncoarsening

Cedric Lachat- PhD Defense December 13, 2013- 27/55

Page 54: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Identification (3/9)

I Algorithm 1: parallel graph coarseningI without local refinement during uncoarsening so as to save

time

Cedric Lachat- PhD Defense December 13, 2013- 28/55

Page 55: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Identification (3/9)

I Algorithm 1: parallel graph coarseningI without local refinement during uncoarsening so as to save

time

Cedric Lachat- PhD Defense December 13, 2013- 28/55

Page 56: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Identification (3/9)

I Algorithm 1: parallel graph coarseningI without local refinement during uncoarsening so as to save

time

Cedric Lachat- PhD Defense December 13, 2013- 28/55

Page 57: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Identification (3/9)

I Algorithm 1: parallel graph coarseningI without local refinement during uncoarsening so as to save

time

I Pros:

I Number of zones does not depend on the number of processorsI Cons:

I Zones are not compact and have small isoperimetric quotient

Cedric Lachat- PhD Defense December 13, 2013- 28/55

Page 58: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Identification (3/9)

I Algorithm 1: parallel graph coarseningI without local refinement during uncoarsening so as to save

time

I Pros:I Number of zones does not depend on the number of processors

I Cons:

I Zones are not compact and have small isoperimetric quotient

Cedric Lachat- PhD Defense December 13, 2013- 28/55

Page 59: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Identification (3/9)

I Algorithm 1: parallel graph coarseningI without local refinement during uncoarsening so as to save

time

I Pros:I Number of zones does not depend on the number of processors

I Cons:

I Zones are not compact and have small isoperimetric quotient

Cedric Lachat- PhD Defense December 13, 2013- 28/55

Page 60: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Identification (3/9)

I Algorithm 1: parallel graph coarseningI without local refinement during uncoarsening so as to save

time

I Pros:I Number of zones does not depend on the number of processors

I Cons:I Zones are not compact and have small isoperimetric quotient

Cedric Lachat- PhD Defense December 13, 2013- 28/55

Page 61: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Identification (3/9)I Algorithm 1: parallel graph coarsening

I without local refinement during uncoarsening so as to savetime

I Pros:I Number of zones does not depend on the number of processors

I Cons:I Zones are not compact and have small isoperimetric quotient

→ We want to improve isoperimetric quotientCedric Lachat- PhD Defense December 13, 2013- 28/55

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Parallel remeshing

Identification (5/9)

I Algorithm 2: parallel seed growing on a distributed enrichedgraph

I How to choose the seeds?I random positions can lead to zone conflictsI first try: pick one seed by subdomain

P0

P2

P1

P3

Cedric Lachat- PhD Defense December 13, 2013- 29/55

Page 63: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Identification (5/9)

I Algorithm 2: parallel seed growing on a distributed enrichedgraph

I How to choose the seeds?I random positions can lead to zone conflictsI first try: pick one seed by subdomain

P0

P2

P1

P3

I Pros:I Zone isoperimetric quotient becomes reasonably good enough

I Cons:

I Number of zones corresponds to the number of processors

Cedric Lachat- PhD Defense December 13, 2013- 29/55

Page 64: PhD Defense - HAL archive ouverte · PhD Defense C´edric Lachat Design and validation of distributed-memory, parallel remeshing algorithms based on a sequential remesher. SUMMARY

Parallel remeshing

Identification (5/9)

I Algorithm 2: parallel seed growing on a distributed enrichedgraph

I How to choose the seeds?I random positions can lead to zone conflictsI first try: pick one seed by subdomain

P0

P2

P1

P3

I Pros:I Zone isoperimetric quotient becomes reasonably good enough

I Cons:

I Number of zones corresponds to the number of processors

Cedric Lachat- PhD Defense December 13, 2013- 29/55

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Parallel remeshing

Identification (5/9)

I Algorithm 2: parallel seed growing on a distributed enrichedgraph

I How to choose the seeds?I random positions can lead to zone conflictsI first try: pick one seed by subdomain

P0

P2

P1

P3

I Pros:I Zone isoperimetric quotient becomes reasonably good enough

I Cons:I Number of zones corresponds to the number of processors

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Parallel remeshing

Identification (6/9)

I Algorithm 3: parallel graph coarsening with parallel seedgrowing on a distributed enriched graph

I Constrain seed selection within prescribed areas

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Parallel remeshing

Identification (6/9)

I Algorithm 3: parallel graph coarsening with parallel seedgrowing on a distributed enriched graph

I Constrain seed selection within prescribed areas

I Pros:

I Yields satisfactory isoperimetric quotientsI Number of zones does not depend on the number of processors

I Cons:

I Two algorithms are used on two different data structures:

I element graph and enriched graphI consumes more time than other algorithms

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Parallel remeshing

Identification (6/9)

I Algorithm 3: parallel graph coarsening with parallel seedgrowing on a distributed enriched graph

I Constrain seed selection within prescribed areas

I Pros:I Yields satisfactory isoperimetric quotients

I Number of zones does not depend on the number of processorsI Cons:

I Two algorithms are used on two different data structures:

I element graph and enriched graphI consumes more time than other algorithms

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Parallel remeshing

Identification (6/9)

I Algorithm 3: parallel graph coarsening with parallel seedgrowing on a distributed enriched graph

I Constrain seed selection within prescribed areas

I Pros:I Yields satisfactory isoperimetric quotientsI Number of zones does not depend on the number of processors

I Cons:

I Two algorithms are used on two different data structures:

I element graph and enriched graphI consumes more time than other algorithms

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Parallel remeshing

Identification (6/9)

I Algorithm 3: parallel graph coarsening with parallel seedgrowing on a distributed enriched graph

I Constrain seed selection within prescribed areas

I Pros:I Yields satisfactory isoperimetric quotientsI Number of zones does not depend on the number of processors

I Cons:

I Two algorithms are used on two different data structures:

I element graph and enriched graphI consumes more time than other algorithms

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Parallel remeshing

Identification (6/9)

I Algorithm 3: parallel graph coarsening with parallel seedgrowing on a distributed enriched graph

I Constrain seed selection within prescribed areas

I Pros:I Yields satisfactory isoperimetric quotientsI Number of zones does not depend on the number of processors

I Cons:I Two algorithms are used on two different data structures:

I element graph and enriched graphI consumes more time than other algorithms

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Parallel remeshing

Identification (6/9)

I Algorithm 3: parallel graph coarsening with parallel seedgrowing on a distributed enriched graph

I Constrain seed selection within prescribed areas

I Pros:I Yields satisfactory isoperimetric quotientsI Number of zones does not depend on the number of processors

I Cons:I Two algorithms are used on two different data structures:

I element graph and enriched graphI consumes more time than other algorithms

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Parallel remeshing

Identification (7/9)

I Algorithm 4: full-featured parallel partitioningI Local optimization is mandatory to obtain good isoperimetric

quotients

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Parallel remeshing

Identification (7/9)

I Algorithm 4: full-featured parallel partitioningI Local optimization is mandatory to obtain good isoperimetric

quotients

I Pros:

I Smooth skin which gives good enough isoperimetric quotientI Number of zones does not depend on number of processors

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Parallel remeshing

Identification (7/9)

I Algorithm 4: full-featured parallel partitioningI Local optimization is mandatory to obtain good isoperimetric

quotients

I Pros:I Smooth skin which gives good enough isoperimetric quotient

I Number of zones does not depend on number of processors

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Parallel remeshing

Identification (7/9)

I Algorithm 4: full-featured parallel partitioningI Local optimization is mandatory to obtain good isoperimetric

quotients

I Pros:I Smooth skin which gives good enough isoperimetric quotientI Number of zones does not depend on number of processors

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Parallel remeshing

Identification (8/9)

Algorithm Good IC #Zones Time spentGraph coarsening No Yes YesSeed growing Yes No YesGraph coarsening + seed growing Yes Yes NoGraph partitioning Yes Yes Yes

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Parallel remeshing

Identification (8/9)

Algorithm Good IC #Zones Time spentGraph coarsening No Yes YesSeed growing Yes No YesGraph coarsening + seed growing Yes Yes NoGraph partitioning Yes Yes Yes

→ Chosen algorithm is graph partitioning

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Parallel remeshing

Identification (9/9)I Propagate zone color on other vertices through cells:

P0

P2

P1

P3

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Parallel remeshing

Extraction (1/3)

1b Tagging

2 Identification

3 Extraction 4 Remeshing

5 Reintegration

1a Tagging

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Parallel remeshing

Extraction (2/3)I Extract zones and distribute them throughout the processors:

I zone skins will not be remeshed, except zone skins whichcorrespond to mesh skin

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Parallel remeshing

Extraction (3/3)

I Two criteria must be considered:

I load-balance according to the remesher workloadI minimize communication

P0

P1 P2

P3

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Parallel remeshing

Extraction (3/3)

I Two criteria must be considered:I load-balance according to the remesher workload

I minimize communication

P0

P1 P2

P3 P2 P3P0 P1

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Parallel remeshing

Extraction (3/3)

I Two criteria must be considered:I load-balance according to the remesher workload

I minimize communication

P0

P1 P2

P3

9 7 5 5 3 7 3

P2 P3P0 P1

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Parallel remeshing

Extraction (3/3)

I Two criteria must be considered:I load-balance according to the remesher workload

I minimize communication

P0

P1 P2

P3

9 10 10 10

9 7 5 5 3 7 3

P2 P3P0 P1

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Parallel remeshing

Extraction (3/3)

I Two criteria must be considered:I load-balance according to the remesher workload

I minimize communication

P0

P1 P2

P3

9 10 10 10

9 7 5 5 3 7 3

P2 P3P0 P1

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Parallel remeshing

Extraction (3/3)

I Two criteria must be considered:I load-balance according to the remesher workloadI minimize communication

P0

P1 P2

P3

9 7 5 5 3 7 3

P2 P3P0 P1

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Parallel remeshing

Extraction (3/3)

I Two criteria must be considered:I load-balance according to the remesher workloadI minimize communication

P0

P1 P2

P3

9 10 10 10

9 7 5 5 3 7 3

P2 P3P0 P1

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Parallel remeshing

Remeshing (1/2)

1b Tagging

2 Identification

3 Extraction 4 Remeshing

5 Reintegration

1a Tagging

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Parallel remeshing

Remeshing (2/2)

I Remesh sequentially each zone on separate processors:I Before remeshing: I After remeshing:

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Parallel remeshing

Reintegration (1/2)

1b Tagging

2 Identification

3 Extraction 4 Remeshing

5 Reintegration

1a Tagging

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Parallel remeshing

Reintegration (2/2)I Fixed skin zone permit to reintegrate zones in distributed

mesh:

P0

P2

P1

P3

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Parallel remeshing

Tagging again (1/2)

1b Tagging

2 Identification

3 Extraction 4 Remeshing

5 Reintegration

1a Tagging

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Parallel remeshing

Tagging again (2/2)

I Remove tag on elements which are inside zonesI Yet a band from the skin is needed to remesh zone skin:I Before tagging:

P0

P2

P1

P3

I After tagging:

P0

P2

P1

P3

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4Experiments

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Experiments

Functional test case (1/3)

I Our work implemented in a library: PaMPAI PaMPA integrated in another library: Aerosol (continuous and

discontinuous finite elements library on hybrid meshes)I Comparison of Aerosol with the Aghora library (developed by

ONERA) in the Yee vortex test case:I implemented into Aerosol by Bacchus and Cagire teams

(not including me)I isentropic vortex in a 3D uniform and inviscid flowI 3D discretization with hexahedra on the unit square [0, 1]3

with periodic boundary conditionsI discontinuous Galerkin methodI explicit Runge-Kutta time stepping

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Experiments

Functional test case (2/3)I Comparison of the weak scalabilityI Varying the polynomial degree p:

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Experiments

Functional test case (3/3)

I Anisotropic propagation ofheat in a tokamak

I Unstationary anisotropicdiffusion

I Torus mesh composed ofprisms

I Discontinuous Galerkinmethod

I Implicit schemeI Linear system solved

with PETsCI Integrated by CAGIRE

team

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Experiments

Parallel remeshing (1/5)

Isotropic meshAnisotropic mesh

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Experiments

Parallel remeshing (2/5): isotropic meshMMG3D PaMPA-MMG3D

on 1 processor on 24 processors

Number of elements at the start 2 423 029Processor frequency (GHz) 2,40 3,06

Used memory (kb) 27 588 940 51 116 044Elapsed time 17h15m12s 00h21m14s

Elapsed time × number procs 17h15m12s 8h33m36sNumber of elements 108 126 515 115 802 876

Smallest edge length 0.1470 0.1395Largest edge length 6.3309 11.2415

Worst element quality 294.2669 294.2669Element quality between 1 and 2 99.65% 99.38%

Edge length between 0.71 and 1.41 97.25% 97.65%

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Experiments

Parallel remeshing (3/5): isotropic mesh

PaMPA-MMG3Don 120 processors

Number of elements at the start 4 509 655Elapsed time 00h34m54s

Elapsed time × number procs 69h48mNumber of elements 318 027 812

Smallest edge length 0.2862Largest edge length 6.2161

Worst element quality 235.6651Element quality between 1 and 2 99.58%

Edge length between 0.71 and 1.41 97.91%

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Experiments

Parallel remeshing (4/5): isotropic mesh

PaMPA-MMG3Don 240 on 480

processors processorsNumber of elements at the start 27 044 943

Used memory (kb) 651 185 792 542 832 960Elapsed time 00h34m59s 00h29m03s

Elapsed time × number procs 139h56m 232h24mNumber of elements 609 671 387 612 426 645

Smallest edge length 0.2911 0.1852Largest edge length 8.3451 7.3611

Worst element quality 335.7041 190.4122Element quality between 1 and 2 98.92% 98.97%

Edge length between 0.71 and 1.41 97.20% 97.39%

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Experiments

Parallel remeshing (4/5): isotropic mesh

1

10

96

385610

1 2 3 4 5 6 7

Num

ber

of

zones

Number of iteration

Comparison of number of zones at each iteration

240 processors480 processors

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Experiments

Parallel remeshing (5/5): anisotropic meshMMG3D PaMPA-MMG3D

on 1 processor on 5 processors

Number of elements at the start 254 501Elapsed time 00h08m25s 00h06m53s

Elapsed time × number procs 00h08m25s 00h34m25sNumber of elements 11 559 197 11 741 242

Smallest edge length 0.1154 0.1133Largest edge length 11.0161 10.1912

Worst element quality 37.7373 38.2374Element quality between 1 and 2 98.41% 98.10%

Edge length between 0.71 and 1.41 93.29% 93.04%

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Experiments

Parallel remeshing (5/5): anisotropic meshMMG3D PaMPA-MMG3D

on 1 processor on 5 processors

Number of elements at the start 254 501Elapsed time 00h08m25s 00h06m53s

Elapsed time × number procs 00h08m25s 00h34m25sNumber of elements 11 559 197 11 741 242

Smallest edge length 0.1154 0.1133Largest edge length 11.0161 10.1912

Worst element quality 37.7373 38.2374Element quality between 1 and 2 98.41% 98.10%

Edge length between 0.71 and 1.41 93.29% 93.04%

→ The mesh must be bigger in order to cover the overheadinduced by the iterative process

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5Conclusion

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Conclusion

Conclusion

I We have devised an efficient scheme for parallel remeshing ofvery large meshes, which can be coupled with any sequentialremesher

I We can achieve the same quality than sequential remeshersI Several algorithms as parallel zone identification have been

developed and implemented:I graph coarseningI seed / ”crystal” growingI graph partitioning

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Conclusion

Prospects

I Short-term prospects:I Remeshing large-size anisotropic meshesI Testing scalability on parallel remeshingI Renumbering entities in parallel remeshingI Remeshing mesh skin by plugging-in a sequential remesher

which remesh the skin: MMG3D5I Long-term prospects:

I parallel repartitioning during parallel remeshingI Adding more parallel zone identification algorithmsI parallel interpolation coupled with parallel remeshing (PhD

Thesis: Leo Nouveau)

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Thank you for your attention

PhD Defense

pampa.bordeaux.inria.fr

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Conclusion

About functional test caseI p degree means 5 ∗ (p + 1)3 ∗ 200 unknowns by sub-domain:

I p = 1: 8000 unknownsI p = 2: 27000 unknownsI p = 3: 64000 unknownsI p = 4: 125000 unknowns

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Conclusion

Nina Amenta, Sunghee Choi, and Gunter Rote. Incrementalconstructions con brio. In Proceedings of the nineteenth annualsymposium on Computational geometry, pages 211–219. ACM,2003.

D.A. Burgess and M.B. Giles. Renumbering unstructured grids toimprove the performance of codes on hierarchical memorymachines. Advances in Engineering Software, 28(3):189–201,1997.

A Casagrande, P Leyland, L Formaggia, and M Sala. Parallel meshadaptation. Series on Advances in Mathematics for AppliedSciences, 69:201, 2005.

Jose G Castanos and John E Savage. The dynamic adaptation ofparallel mesh-based computation. 1996.

Peter A Cavallo, Neeraj Sinha, and Gregory M Feldman. Parallelunstructured mesh adaptation method for moving bodyapplications. AIAA journal, 43(9):1937–1945, 2005.

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Conclusion

Cedric Chevalier. Conception et mise en oeuvre d’outils efficacespour le partitionnement et la distribution paralleles de problemenumeriques de tres grande taille. PhD thesis, Universite Scienceset Technologies-Bordeaux I, 2007.

Cedric Chevalier and Ilya Safro. Comparison of coarsening schemesfor multilevel graph partitioning. In Learning and IntelligentOptimization, pages 191–205. Springer, 2009.

Nikos Chrisochoides and Demian Nave. Parallel delaunay meshgeneration kernel. International Journal for Numerical Methodsin Engineering, 58(2):161–176, 2003.

Thierry Coupez, Hugues Digonnet, and Richard Ducloux. Parallelmeshing and remeshing. Applied Mathematical Modelling, 25(2):153–175, 2000.

Karen Devine, Bruce Hendrickson, Erik Boman, Matthew St John,Courtenay Vaughan, and WF Mitchell. Zoltan: A dynamicload-balancing library for parallel applications; users guide.Sandia National Laboratories Tech. Rep, 1999.

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Conclusion

Karen Devine, Erik Boman, Robert Heaphy, Bruce Hendrickson,and Courtenay Vaughan. Zoltan data management services forparallel dynamic applications. Computing in Science &Engineering, 4(2):90–96, 2002.

Hugues Digonnet, Marc Bernacki, Luisa Silva, and Thierry Coupez.Adaptation de maillage en parallele, application a la simulationde la mise en forme des materiaux. In Congres Francais deMecanique Grenoble-CFM 2007, page 6 pages, Grenoble,France, 2007. URLhttp://hal-ensmp.archives-ouvertes.fr/hal-00521844.http://hdl.handle.net/2042/16046.

C Dobrzynski and JF Remacle. Parallel mesh adaptation.International Journal for Numerical Methods in Engineering,2007.

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Conclusion

J. J. Dongarra, J. Du Croz, S. Hammarling, and R. J. Hanson. Anextended set of FORTRAN Basic Linear Algebra Subprograms.ACM Transactions on Mathematical Software, 14(1):1–17,March 1988. ISSN 0098-3500. URLhttp://doi.acm.org/10.1145/42288.42291.

C. M. Fiduccia and R. M. Mattheyses. A linear-time heuristic forimproving network partitions. In Proceedings of the 19th DesignAutomation Conference, pages 175–181. IEEE, 1982.

Martin Isenburg, Yuanxin Liu, Jonathan Shewchuk, and JackSnoeyink. Streaming computation of delaunay triangulations. InACM Transactions on Graphics (TOG), volume 25, pages1049–1056. ACM, 2006.

B. W. Kernighan and S. Lin. An efficient heuristic procedure forpartitioning graphs. BELL System Technical Journal, pages291–307, February 1970.

Ing Lutz Laemmer. Parallel mesh generation. In Solving IrregularlyStructured Problems in Parallel, pages 1–12. Springer, 1997.

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Conclusion

Orion Lawlor, Sayantan Chakravorty, Terry Wilmarth, NileshChoudhury, Isaac Dooley, Gengbin Zheng, and Laxmikant Kale.Parfum: a parallel framework for unstructured meshes forscalable dynamic physics applications. Engineering withComputers, 22:215–235, 2006. ISSN 0177-0667. URLhttp://dx.doi.org/10.1007/s00366-006-0039-5.10.1007/s00366-006-0039-5.

Rainald Lohner. Some useful renumbering strategies forunstructured grids. International Journal for Numerical Methodsin Engineering, 36(19):3259–3270, 1993.

Rainald Lohner. Renumbering strategies for unstructured-gridsolvers operating on shared-memory, cache-based parallelmachines. Computer methods in applied mechanics andengineering, 163(1):95–109, 1998.

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Conclusion

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Conclusion

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