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# $Id:$ |
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|
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# |
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# COPYRIGHT ACcESS 2004 - All Rights Reserved |
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# |
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# This software is the property of ACcESS. No part of this code |
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# may be copied in any form or by any means without the expressed written |
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# consent of ACcESS. Copying, use or modification of this software |
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# by any unauthorised person is illegal unless that |
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# person has a software license agreement with ACcESS. |
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# |
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|
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""" |
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some benchmarks for tetsing the finley solver. The idea is to develop a set of standart benchmarks |
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|
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* Laplace2Dorder1_?k |
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* Laplace3Dorder2_?k |
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|
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where ? is approximatively the number of unknowns in 1000. |
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|
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@var __author__: name of author |
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@var __licence__: licence agreement |
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var __url__: url entry point on documentation |
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@var __version__: version |
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@var __date__: date of the version |
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""" |
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|
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__author__="Lutz Gross, l.gross@uq.edu.au" |
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__licence__="contact: esys@access.uq.edu.au" |
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__url__="http://www.iservo.edu.au/esys/escript" |
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__version__="$Revision:$" |
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__date__="$Date:$" |
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|
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from esys.escript import Lsup,whereZero,kronecker |
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from esys.escript.benchmark import BenchmarkProblem, Options, BenchmarkFilter |
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import esys.finley |
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from esys.escript.linearPDEs import LinearPDE |
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import os |
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|
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class FinleyFilter(BenchmarkFilter): |
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""" |
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defines a filter for L{FinleyProblem} characteristics |
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""" |
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TIME="t [sec]" |
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ERROR="rel. error" |
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|
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|
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def __init__(self,args=None): |
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""" |
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sets up the filter |
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|
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@param args: list of value names to be filtered |
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@type args: C{list} of L{TIME}, L{ERROR} |
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""" |
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if args==None: args=[FinleyFilter.TIME,FinleyFilter.ERROR] |
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super(FinleyFilter,self).__init__() |
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self.__args=args |
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|
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def getResultNames(self): |
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""" |
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return the names of the results produced when run() is called. |
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|
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@return: names the list of the names to be used when the results of the run() call are printed |
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@rtype: C{list} of C{str} |
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""" |
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return self.__args |
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|
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def __call__(self,result): |
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""" |
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filters out the characteristic values |
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|
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@param result: characteristics rturned by a L{FinleyProblem} run |
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@type result: C{dict} |
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@return: filtered values |
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@rtype: C{list} of C{str} |
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""" |
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out=[] |
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for a in self.__args: |
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out.append(result[a]) |
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return out |
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|
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class FinleyOptions(Options): |
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""" |
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finley solver options to be handed over to paso |
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|
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""" |
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def __init__(self,solver_method=None, |
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preconditioner=None, |
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package=None, |
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tolerance=None, |
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verbose=False): |
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self.strmap={ |
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LinearPDE.DIRECT : "DIRECT", |
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LinearPDE.PCG: "PCG", |
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LinearPDE.CR: "CR", |
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LinearPDE.CGS: "CGS", |
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LinearPDE.BICGSTAB: "BICGSTAB", |
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LinearPDE.SSOR: "SSOR", |
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LinearPDE.ILU0: "ILU0", |
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LinearPDE.ILUT: "ILUT", |
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LinearPDE.JACOBI: "JACOBI", |
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LinearPDE.GMRES: "GMRES", |
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LinearPDE.PRES20: "PRES20", |
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LinearPDE.LUMPING: "LUMPIMG", |
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LinearPDE.NO_REORDERING: "NO_REORDERING", |
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LinearPDE.MINIMUM_FILL_IN: "MINIMUM_FILL_IN", |
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LinearPDE.NESTED_DISSECTION: "NESTED_DISSECTION", |
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LinearPDE.SCSL: "SCSL", |
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LinearPDE.MKL: "MKL", |
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LinearPDE.UMFPACK: "UMFPACK", |
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LinearPDE.PASO: "PASO" |
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} |
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name="" |
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if solver_method==None: |
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solver_method==LinearPDE.PRES20 |
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else: |
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name+=self.strmap[solver_method] |
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if preconditioner==None: |
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preconditioner==LinearPDE.JACOBI |
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else: |
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if not name=="": name+="+" |
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name+=self.strmap[preconditioner] |
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if package==None: |
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package==LinearPDE.PASO |
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else: |
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if not name=="": name+=" with " |
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name+=self.strmap[package] |
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if tolerance==None: |
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tolerance=1.e-8 |
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else: |
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if not name=="": name+=", " |
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name+="tol = %s"%tolerance |
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self.solver_method=solver_method |
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self.preconditioner=preconditioner |
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self.tolerance=tolerance |
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self.package=package |
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self.verbose=verbose |
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super(FinleyOptions,self).__init__(name=name) |
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|
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|
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|
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class FinleyProblem(BenchmarkProblem): |
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""" |
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The general benchmark problem for Finley |
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""" |
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def run(self,options): |
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""" |
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creates a domain and a PDE on this domain, solves it (with the given options) and returns the |
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elapsed time and the error. |
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|
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@param options: paso solver options |
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@type options: L{PasoOptions} |
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@return: elapsed time and the error of calculated solution |
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@rtype: pair of C{float} |
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""" |
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domain=self.getDomain() |
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pde,u=self.getTestProblem(domain) |
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pde.setTolerance(options.tolerance) |
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pde.setSolverMethod(options.solver_method,options.preconditioner) |
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pde.setSolverPackage(options.package) |
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a=os.times()[4] |
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uh=pde.getSolution(verbose=options.verbose) |
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a=os.times()[4]-a |
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if u==None: |
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return {FinleyFilter.TIME : a , FinleyFilter.ERROR : None } |
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else: |
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error=Lsup(u-uh)/Lsup(u) |
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return {FinleyFilter.TIME : a , FinleyFilter.ERROR : error } |
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|
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def getTestProblem(self,domain): |
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""" |
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returns a PDEto be solved and an exact solution |
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|
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@param domain: the PDE domain |
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@type domain: L{escript.Domain} |
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@return: a linear PDE to be solved an a reference solution |
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@rtype: L{LinearPDE},L{escript.Data} |
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@remark: must be overwritten by a particular problem |
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""" |
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raise NotImplementedError |
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|
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def getDomain(self): |
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""" |
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returns the domain of the problem |
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|
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@return: a domain |
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@rtype: L{escript.Domain} |
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@remark: must be overwritten by a particular problem |
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""" |
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raise NotImplementedError |
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|
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class RegularFinleyProblem(FinleyProblem): |
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""" |
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base class for finley problem on a rectangular mesh |
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""" |
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def __init__(self,n=1,order=1,dim=2): |
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""" |
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sets up a recangular mesh in finley on a unit cube/square |
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@param n: number of elements in each spactial direction |
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@type n: C{int} |
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@param order: element order |
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@type order: 1 or 2 |
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@param dim: spatial dimension |
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@type n: 2 or 3 |
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""" |
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super(RegularFinleyProblem,self).__init__(name=str((order*n+1)**dim)) |
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self.__n=n |
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self.__order=order |
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self.__dim=dim |
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|
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def getDomain(self): |
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""" |
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returns the unit square/cube with a rectangular mesh |
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@return: a domain |
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@rtype: L{escript.Domain} |
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""" |
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if self.__dim==2: |
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domain=esys.finley.Rectangle(n0=self.__n,n1=self.__n,order=self.__order) |
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else: |
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domain=esys.finley.Brick(n0=self.__n,n1=self.__n,n2=self.__n,order=self.__order) |
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return domain |
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|
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class LaplaceProblem(RegularFinleyProblem): |
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""" |
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base class for the Lapalce eqaution on a rectangular mesh |
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""" |
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def getTestProblem(self,domain): |
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""" |
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returns a PDE and a test solution on the given domain |
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@param doamin: a domain |
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@type domain: L{escript.Domain} |
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@return: the Laplace equation and a test solution |
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@rtype: C{tuple} of C{LinearPDE} and C{escript.Data} |
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""" |
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x=domain.getX() |
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msk=whereZero(x[0])+whereZero(x[0]-1.) |
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u=x[0] |
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for i in range(1,domain.getDim()): |
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msk+=whereZero(x[i])+whereZero(x[i]-1.) |
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u*=(x[i]-i) |
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pde=LinearPDE(domain) |
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pde.setSymmetryOn() |
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pde.setValue(A=kronecker(domain),q=msk,r=u) |
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return pde,u |
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|
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class Laplace2DOrder1_30k(LaplaceProblem): |
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def __init__(self): |
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super(Laplace2DOrder1_30k,self).__init__(n=176,order=1,dim=2) |
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class Laplace2DOrder2_30k(LaplaceProblem): |
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def __init__(self): |
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super(Laplace2DOrder2_30k,self).__init__(n=88,order=2,dim=2) |
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class Laplace2DOrder1_60k(LaplaceProblem): |
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def __init__(self): |
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super(Laplace2DOrder1_60k,self).__init__(n=248,order=1,dim=2) |
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class Laplace2DOrder2_60k(LaplaceProblem): |
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def __init__(self): |
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super(Laplace2DOrder2_60k,self).__init__(n=124,order=2,dim=2) |
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class Laplace2DOrder1_120k(LaplaceProblem): |
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def __init__(self): |
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super(Laplace2DOrder1_120k,self).__init__(n=349,order=1,dim=2) |
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class Laplace2DOrder2_120k(LaplaceProblem): |
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def __init__(self): |
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super(Laplace2DOrder2_120k,self).__init__(n=175,order=2,dim=2) |
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class Laplace2DOrder1_240k(LaplaceProblem): |
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def __init__(self): |
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super(Laplace2DOrder1_240k,self).__init__(n=492,order=1,dim=2) |
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class Laplace2DOrder2_240k(LaplaceProblem): |
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def __init__(self): |
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super(Laplace2DOrder2_240k,self).__init__(n=246,order=2,dim=2) |
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class Laplace2DOrder1_480k(LaplaceProblem): |
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def __init__(self): |
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super(Laplace2DOrder1_480k,self).__init__(n=694,order=1,dim=2) |
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class Laplace2DOrder2_480k(LaplaceProblem): |
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def __init__(self): |
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super(Laplace2DOrder2_480k,self).__init__(n=347,order=2,dim=2) |
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class Laplace2DOrder1_960k(LaplaceProblem): |
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def __init__(self): |
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super(Laplace2DOrder1_960k,self).__init__(n=978,order=1,dim=2) |
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class Laplace2DOrder2_960k(LaplaceProblem): |
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def __init__(self): |
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super(Laplace2DOrder2_960k,self).__init__(n=489,order=2,dim=2) |
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