mirror of https://github.com/fredrikekre/HYPRE.jl
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# Example translated from C to Julia based on this original source (MIT license): |
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# https://github.com/hypre-space/hypre/blob/ac9d7d0d7b43cd3d0c7f24ec5d64b58fbf900097/src/examples/ex5.c |
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# Example 5 |
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# |
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# Interface: Linear-Algebraic (IJ) |
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# |
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# Sample run: mpirun -np 4 julia ex5.jl |
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# |
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# Description: This example solves the 2-D Laplacian problem with zero boundary |
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# conditions on an n x n grid. The number of unknowns is N=n^2. |
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# The standard 5-point stencil is used, and we solve for the |
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# interior nodes only. |
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# |
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# This example solves the same problem as Example 3. Available |
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# solvers are AMG, PCG, and PCG with AMG or Parasails |
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# preconditioners. |
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using MPI |
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using HYPRE.LibHYPRE # LibHYPRE submodule contains the raw C-interface generated by Clang.jl |
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function main() |
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# Initialize MPI |
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# MPI_Init(Ref{Cint}(length(ARGS)), ARGS) |
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MPI.Init() |
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comm = MPI.COMM_WORLD |
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myid = MPI.Comm_rank(comm) |
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num_procs = MPI.Comm_size(comm) |
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# Initialize HYPRE |
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HYPRE_Init() |
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# Default problem parameters |
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n = 33 |
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solver_id = 0 |
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print_system = false |
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# TODO: Parse command line |
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# Preliminaries: want at least one processor per row |
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if n * n < num_procs; n = trunc(Int, sqrt(n)) + 1; end |
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N = n * n # global number of rows |
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h = 1.0 / (n + 1) # mesh size |
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h2 = h * h |
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# Each processor knows only of its own rows - the range is denoted by ilower |
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# and upper. Here we partition the rows. We account for the fact that |
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# N may not divide evenly by the number of processors. |
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local_size = N ÷ num_procs |
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extra = N - local_size * num_procs |
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ilower = local_size * myid |
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ilower += min(myid, extra) |
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iupper = local_size * (myid + 1) |
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iupper += min(myid + 1, extra) |
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iupper = iupper - 1 |
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# How many rows do I have? |
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local_size = iupper - ilower + 1 |
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# Create the matrix. |
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# Note that this is a square matrix, so we indicate the row partition |
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# size twice (since number of rows = number of cols) |
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Aref = Ref{HYPRE_IJMatrix}(C_NULL) |
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HYPRE_IJMatrixCreate(comm, ilower, iupper, ilower, iupper, Aref) |
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A = Aref[] |
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# Choose a parallel csr format storage (see the User's Manual) |
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HYPRE_IJMatrixSetObjectType(A, HYPRE_PARCSR) |
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# Initialize before setting coefficients |
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HYPRE_IJMatrixInitialize(A) |
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# Now go through my local rows and set the matrix entries. |
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# Each row has at most 5 entries. For example, if n=3: |
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# A = [M -I 0; -I M -I; 0 -I M] |
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# M = [4 -1 0; -1 4 -1; 0 -1 4] |
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# Note that here we are setting one row at a time, though |
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# one could set all the rows together (see the User's Manual). |
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let |
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values = Vector{Float64}(undef, 5) |
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cols = Vector{HYPRE_Int}(undef, 5) |
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tmp = Vector{HYPRE_Int}(undef, 2) |
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for i in ilower:iupper |
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nnz = 1 |
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# The left identity block:position i-n |
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if (i - n) >= 0 |
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cols[nnz] = i - n |
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values[nnz] = -1.0 |
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nnz += 1 |
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end |
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# The left -1: position i-1 |
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if i % n != 0 |
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cols[nnz] = i - 1 |
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values[nnz] = -1.0 |
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nnz += 1 |
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end |
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# Set the diagonal: position i |
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cols[nnz] = i |
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values[nnz] = 4.0 |
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nnz += 1 |
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# The right -1: position i+1 |
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if (i + 1) % n != 0 |
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cols[nnz] = i + 1 |
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values[nnz] = -1.0 |
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nnz += 1 |
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end |
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# The right identity block:position i+n |
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if (i + n) < N |
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cols[nnz] = i + n |
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values[nnz] = -1.0 |
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nnz += 1 |
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end |
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# Set the values for row i |
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tmp[1] = nnz - 1 |
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tmp[2] = i |
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HYPRE_IJMatrixSetValues(A, 1, Ref(tmp[1]), Ref(tmp[2]), cols, values) |
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end |
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end |
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# Assemble after setting the coefficients |
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HYPRE_IJMatrixAssemble(A) |
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# Note: for the testing of small problems, one may wish to read |
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# in a matrix in IJ format (for the format, see the output files |
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# from the -print_system option). |
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# In this case, one would use the following routine: |
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# HYPRE_IJMatrixRead( <filename>, MPI_COMM_WORLD, |
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# HYPRE_PARCSR, &A ); |
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# <filename> = IJ.A.out to read in what has been printed out |
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# by -print_system (processor numbers are omitted). |
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# A call to HYPRE_IJMatrixRead is an *alternative* to the |
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# following sequence of HYPRE_IJMatrix calls: |
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# Create, SetObjectType, Initialize, SetValues, and Assemble |
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# Get the parcsr matrix object to use |
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parcsr_A_ref = Ref{Ptr{Cvoid}}(C_NULL) |
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HYPRE_IJMatrixGetObject(A, parcsr_A_ref) |
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parcsr_A = convert(Ptr{HYPRE_ParCSRMatrix}, parcsr_A_ref[]) |
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# Create the rhs and solution |
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b_ref = Ref{HYPRE_IJVector}(C_NULL) |
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HYPRE_IJVectorCreate(comm, ilower, iupper, b_ref) |
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b = b_ref[] |
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HYPRE_IJVectorSetObjectType(b, HYPRE_PARCSR) |
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HYPRE_IJVectorInitialize(b) |
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x_ref = Ref{HYPRE_IJVector}(C_NULL) |
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HYPRE_IJVectorCreate(comm, ilower, iupper, x_ref) |
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x = x_ref[] |
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HYPRE_IJVectorSetObjectType(x, HYPRE_PARCSR) |
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HYPRE_IJVectorInitialize(x) |
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# Set the rhs values to h^2 and the solution to zero |
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let |
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rhs_values = Vector{Float64}(undef, local_size) |
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x_values = Vector{Float64}(undef, local_size) |
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rows = Vector{HYPRE_Int}(undef, local_size) |
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for i in 1:local_size |
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rhs_values[i] = h2 |
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x_values[i] = 0.0 |
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rows[i] = ilower + i - 1 |
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end |
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HYPRE_IJVectorSetValues(b, local_size, rows, rhs_values) |
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HYPRE_IJVectorSetValues(x, local_size, rows, x_values) |
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end |
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HYPRE_IJVectorAssemble(b) |
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par_b_ref = Ref{Ptr{Cvoid}}(C_NULL) |
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HYPRE_IJVectorGetObject(b, par_b_ref) |
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par_b = convert(Ptr{HYPRE_ParVector}, par_b_ref[]) |
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HYPRE_IJVectorAssemble(x) |
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par_x_ref = Ref{Ptr{Cvoid}}(C_NULL) |
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HYPRE_IJVectorGetObject(x, par_x_ref) |
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par_x = convert(Ptr{HYPRE_ParVector}, par_x_ref[]) |
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# Print out the system - files names will be IJ.out.A.XXXXX |
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# and IJ.out.b.XXXXX, where XXXXX = processor id |
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if print_system |
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HYPRE_IJMatrixPrint(A, "IJ.out.A") |
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HYPRE_IJVectorPrint(b, "IJ.out.b") |
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end |
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# Choose a solver and solve the system |
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solver_ref = Ref{HYPRE_Solver}(C_NULL) |
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# AMG |
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if solver_id == 0 |
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# Create solver |
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HYPRE_BoomerAMGCreate(solver_ref) |
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solver = solver_ref[] |
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# Set some parameters (See Reference Manual for more parameters) |
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HYPRE_BoomerAMGSetPrintLevel(solver, 3) # print solve info + parameters |
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HYPRE_BoomerAMGSetOldDefault(solver) # Falgout coarsening with modified classical interpolaiton |
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HYPRE_BoomerAMGSetRelaxType(solver, 3) # G-S/Jacobi hybrid relaxation |
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HYPRE_BoomerAMGSetRelaxOrder(solver, 1) # uses C/F relaxation |
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HYPRE_BoomerAMGSetNumSweeps(solver, 1) # Sweeeps on each level |
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HYPRE_BoomerAMGSetMaxLevels(solver, 20) # maximum number of levels |
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HYPRE_BoomerAMGSetTol(solver, 1e-7) # conv. tolerance |
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# Now setup and solve! |
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HYPRE_BoomerAMGSetup(solver, parcsr_A, par_b, par_x) |
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HYPRE_BoomerAMGSolve(solver, parcsr_A, par_b, par_x) |
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# Run info - needed logging turned on |
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num_iterations = Ref{HYPRE_Int}() |
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final_res_norm = Ref{Float64}() |
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HYPRE_BoomerAMGGetNumIterations(solver, num_iterations) |
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HYPRE_BoomerAMGGetFinalRelativeResidualNorm(solver, final_res_norm) |
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if myid == 0 |
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println() |
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println("Iterations = $(num_iterations[])") |
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println("Final Relative Residual Norm = $(final_res_norm[])") |
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println() |
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end |
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# Destroy solver |
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HYPRE_BoomerAMGDestroy(solver) |
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else |
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if myid == 0 |
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println("Invalid sovler id specified.") |
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end |
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end |
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# Clean up |
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HYPRE_IJMatrixDestroy(A) |
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HYPRE_IJVectorDestroy(b) |
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HYPRE_IJVectorDestroy(x) |
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# Finalize HYPRE |
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HYPRE_Finalize() |
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# Finalize MPI |
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MPI.Finalize() |
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return 0 |
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end |
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# Run it |
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if abspath(PROGRAM_FILE) == @__FILE__ |
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main() |
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end |
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