static char help[] = "Newton methods to solve u'' + u^{2} = f in parallel. Uses Kokkos\n\\n"; #include #include /* User-defined application context */ typedef struct { DM da; /* distributed array */ Vec F; /* right-hand side of PDE */ PetscReal h; /* mesh spacing */ } ApplicationCtx; /* ------------------------------------------------------------------- */ /* FormInitialGuess - Computes initial guess. Input/Output Parameter: . x - the solution vector */ PetscErrorCode FormInitialGuess(Vec x) { PetscScalar pfive = .50; PetscFunctionBeginUser; PetscCall(VecSet(x, pfive)); PetscFunctionReturn(PETSC_SUCCESS); } /* ------------------------------------------------------------------- */ /* CpuFunction - Evaluates nonlinear function, F(x) on CPU Input Parameters: . snes - the SNES context . x - input vector . ctx - optional user-defined context, as set by SNESSetFunction() Output Parameter: . r - function vector Note: The user-defined context can contain any application-specific data needed for the function evaluation. */ PetscErrorCode CpuFunction(SNES snes, Vec x, Vec r, void *ctx) { ApplicationCtx *user = (ApplicationCtx *)ctx; DM da = user->da; PetscScalar *X, *R, *F, d; PetscInt i, M, xs, xm; Vec xl; PetscFunctionBeginUser; PetscCall(DMGetLocalVector(da, &xl)); PetscCall(DMGlobalToLocal(da, x, INSERT_VALUES, xl)); PetscCall(DMDAVecGetArray(da, xl, &X)); PetscCall(DMDAVecGetArray(da, r, &R)); PetscCall(DMDAVecGetArray(da, user->F, &F)); PetscCall(DMDAGetCorners(da, &xs, NULL, NULL, &xm, NULL, NULL)); PetscCall(DMDAGetInfo(da, NULL, &M, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL)); if (xs == 0) { /* left boundary */ R[0] = X[0]; xs++; xm--; } if (xs + xm == M) { /* right boundary */ R[xs + xm - 1] = X[xs + xm - 1] - 1.0; xm--; } d = 1.0 / (user->h * user->h); for (i = xs; i < xs + xm; i++) R[i] = d * (X[i - 1] - 2.0 * X[i] + X[i + 1]) + X[i] * X[i] - F[i]; PetscCall(DMDAVecRestoreArray(da, xl, &X)); PetscCall(DMDAVecRestoreArray(da, r, &R)); PetscCall(DMDAVecRestoreArray(da, user->F, &F)); PetscCall(DMRestoreLocalVector(da, &xl)); PetscFunctionReturn(PETSC_SUCCESS); } using DefaultExecutionSpace = Kokkos::DefaultExecutionSpace; using DefaultMemorySpace = Kokkos::DefaultExecutionSpace::memory_space; using PetscScalarKokkosOffsetView = Kokkos::Experimental::OffsetView; using ConstPetscScalarKokkosOffsetView = Kokkos::Experimental::OffsetView; PetscErrorCode KokkosFunction(SNES snes, Vec x, Vec r, void *ctx) { ApplicationCtx *user = (ApplicationCtx *)ctx; DM da = user->da; PetscScalar d; PetscInt M; Vec xl; PetscScalarKokkosOffsetView R; ConstPetscScalarKokkosOffsetView X, F; PetscFunctionBeginUser; PetscCall(DMGetLocalVector(da, &xl)); PetscCall(DMGlobalToLocal(da, x, INSERT_VALUES, xl)); d = 1.0 / (user->h * user->h); PetscCall(DMDAGetInfo(da, NULL, &M, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL)); PetscCall(DMDAVecGetKokkosOffsetView(da, xl, &X)); /* read only */ PetscCall(DMDAVecGetKokkosOffsetViewWrite(da, r, &R)); /* write only */ PetscCall(DMDAVecGetKokkosOffsetView(da, user->F, &F)); /* read only */ Kokkos::parallel_for( Kokkos::RangePolicy<>(R.begin(0), R.end(0)), KOKKOS_LAMBDA(int i) { if (i == 0) R(0) = X(0); /* left boundary */ else if (i == M - 1) R(i) = X(i) - 1.0; /* right boundary */ else R(i) = d * (X(i - 1) - 2.0 * X(i) + X(i + 1)) + X(i) * X(i) - F(i); /* interior */ }); PetscCall(DMDAVecRestoreKokkosOffsetView(da, xl, &X)); PetscCall(DMDAVecRestoreKokkosOffsetViewWrite(da, r, &R)); PetscCall(DMDAVecRestoreKokkosOffsetView(da, user->F, &F)); PetscCall(DMRestoreLocalVector(da, &xl)); PetscFunctionReturn(PETSC_SUCCESS); } PetscErrorCode StubFunction(SNES snes, Vec x, Vec r, void *ctx) { ApplicationCtx *user = (ApplicationCtx *)ctx; DM da = user->da; Vec rk; PetscReal norm = 0; PetscFunctionBeginUser; PetscCall(DMGetGlobalVector(da, &rk)); PetscCall(CpuFunction(snes, x, r, ctx)); PetscCall(KokkosFunction(snes, x, rk, ctx)); PetscCall(VecAXPY(rk, -1.0, r)); PetscCall(VecNorm(rk, NORM_2, &norm)); PetscCall(DMRestoreGlobalVector(da, &rk)); PetscCheck(norm <= 1e-6, PETSC_COMM_SELF, PETSC_ERR_PLIB, "KokkosFunction() different from CpuFunction() with a diff norm = %g", (double)norm); PetscFunctionReturn(PETSC_SUCCESS); } /* ------------------------------------------------------------------- */ /* FormJacobian - Evaluates Jacobian matrix. Input Parameters: . snes - the SNES context . x - input vector . dummy - optional user-defined context (not used here) Output Parameters: . jac - Jacobian matrix . B - optionally different preconditioning matrix . flag - flag indicating matrix structure */ PetscErrorCode FormJacobian(SNES snes, Vec x, Mat jac, Mat B, void *ctx) { ApplicationCtx *user = (ApplicationCtx *)ctx; PetscScalar *xx, d, A[3]; PetscInt i, j[3], M, xs, xm; DM da = user->da; PetscFunctionBeginUser; /* Get pointer to vector data */ PetscCall(DMDAVecGetArrayRead(da, x, &xx)); PetscCall(DMDAGetCorners(da, &xs, NULL, NULL, &xm, NULL, NULL)); /* Get range of locally owned matrix */ PetscCall(DMDAGetInfo(da, NULL, &M, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL)); /* Determine starting and ending local indices for interior grid points. Set Jacobian entries for boundary points. */ if (xs == 0) { /* left boundary */ i = 0; A[0] = 1.0; PetscCall(MatSetValues(jac, 1, &i, 1, &i, A, INSERT_VALUES)); xs++; xm--; } if (xs + xm == M) { /* right boundary */ i = M - 1; A[0] = 1.0; PetscCall(MatSetValues(jac, 1, &i, 1, &i, A, INSERT_VALUES)); xm--; } /* Interior grid points - Note that in this case we set all elements for a particular row at once. */ d = 1.0 / (user->h * user->h); for (i = xs; i < xs + xm; i++) { j[0] = i - 1; j[1] = i; j[2] = i + 1; A[0] = A[2] = d; A[1] = -2.0 * d + 2.0 * xx[i]; PetscCall(MatSetValues(jac, 1, &i, 3, j, A, INSERT_VALUES)); } /* Assemble matrix, using the 2-step process: MatAssemblyBegin(), MatAssemblyEnd(). By placing code between these two statements, computations can be done while messages are in transition. Also, restore vector. */ PetscCall(MatAssemblyBegin(jac, MAT_FINAL_ASSEMBLY)); PetscCall(DMDAVecRestoreArrayRead(da, x, &xx)); PetscCall(MatAssemblyEnd(jac, MAT_FINAL_ASSEMBLY)); PetscFunctionReturn(PETSC_SUCCESS); } int main(int argc, char **argv) { SNES snes; /* SNES context */ Mat J; /* Jacobian matrix */ ApplicationCtx ctx; /* user-defined context */ Vec x, r, U, F; /* vectors */ PetscScalar none = -1.0; PetscInt its, N = 5, maxit, maxf; PetscReal abstol, rtol, stol, norm; PetscBool viewinitial = PETSC_FALSE; PetscFunctionBeginUser; PetscCall(PetscInitialize(&argc, &argv, (char *)0, help)); PetscCall(PetscOptionsGetInt(NULL, NULL, "-n", &N, NULL)); ctx.h = 1.0 / (N - 1); PetscCall(PetscOptionsGetBool(NULL, NULL, "-view_initial", &viewinitial, NULL)); /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Create nonlinear solver context - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ PetscCall(SNESCreate(PETSC_COMM_WORLD, &snes)); /* Create distributed array (DMDA) to manage parallel grid and vectors */ PetscCall(DMDACreate1d(PETSC_COMM_WORLD, DM_BOUNDARY_NONE, N, 1, 1, NULL, &ctx.da)); PetscCall(DMSetFromOptions(ctx.da)); PetscCall(DMSetUp(ctx.da)); /* Extract global and local vectors from DMDA; then duplicate for remaining vectors that are the same types */ PetscCall(DMCreateGlobalVector(ctx.da, &x)); PetscCall(PetscObjectSetName((PetscObject)x, "Approximate Solution")); PetscCall(VecDuplicate(x, &r)); PetscCall(VecDuplicate(x, &F)); ctx.F = F; PetscCall(PetscObjectSetName((PetscObject)F, "Forcing function")); PetscCall(VecDuplicate(x, &U)); PetscCall(PetscObjectSetName((PetscObject)U, "Exact Solution")); /* Set function evaluation routine and vector. Whenever the nonlinear solver needs to compute the nonlinear function, it will call this routine. - Note that the final routine argument is the user-defined context that provides application-specific data for the function evaluation routine. At the beginning, one can use a stub function that checks the Kokkos version against the CPU version to quickly expose errors. PetscCall(SNESSetFunction(snes,r,StubFunction,&ctx)); */ PetscCall(SNESSetFunction(snes, r, KokkosFunction, &ctx)); /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Create matrix data structure; set Jacobian evaluation routine - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ PetscCall(DMCreateMatrix(ctx.da, &J)); /* Set Jacobian matrix data structure and default Jacobian evaluation routine. Whenever the nonlinear solver needs to compute the Jacobian matrix, it will call this routine. - Note that the final routine argument is the user-defined context that provides application-specific data for the Jacobian evaluation routine. */ PetscCall(SNESSetJacobian(snes, J, J, FormJacobian, &ctx)); PetscCall(SNESSetFromOptions(snes)); PetscCall(SNESGetTolerances(snes, &abstol, &rtol, &stol, &maxit, &maxf)); PetscCall(PetscPrintf(PETSC_COMM_WORLD, "atol=%g, rtol=%g, stol=%g, maxit=%" PetscInt_FMT ", maxf=%" PetscInt_FMT "\n", (double)abstol, (double)rtol, (double)stol, maxit, maxf)); /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Initialize application: Store forcing function of PDE and exact solution - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ { PetscScalarKokkosOffsetView FF, UU; PetscCall(DMDAVecGetKokkosOffsetViewWrite(ctx.da, F, &FF)); PetscCall(DMDAVecGetKokkosOffsetViewWrite(ctx.da, U, &UU)); Kokkos::parallel_for( Kokkos::RangePolicy<>(FF.begin(0), FF.end(0)), KOKKOS_LAMBDA(int i) { PetscReal xp = i * ctx.h; FF(i) = 6.0 * xp + pow(xp + 1.e-12, 6.0); /* +1.e-12 is to prevent 0^6 */ UU(i) = xp * xp * xp; }); PetscCall(DMDAVecRestoreKokkosOffsetViewWrite(ctx.da, F, &FF)); PetscCall(DMDAVecRestoreKokkosOffsetViewWrite(ctx.da, U, &UU)); } if (viewinitial) { PetscCall(VecView(U, NULL)); PetscCall(VecView(F, NULL)); } /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Evaluate initial guess; then solve nonlinear system - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ /* Note: The user should initialize the vector, x, with the initial guess for the nonlinear solver prior to calling SNESSolve(). In particular, to employ an initial guess of zero, the user should explicitly set this vector to zero by calling VecSet(). */ PetscCall(FormInitialGuess(x)); PetscCall(SNESSolve(snes, NULL, x)); PetscCall(SNESGetIterationNumber(snes, &its)); PetscCall(PetscPrintf(PETSC_COMM_WORLD, "Number of SNES iterations = %" PetscInt_FMT "\n", its)); /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Check solution and clean up - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ /* Check the error */ PetscCall(VecAXPY(x, none, U)); PetscCall(VecNorm(x, NORM_2, &norm)); PetscCall(PetscPrintf(PETSC_COMM_WORLD, "Norm of error %g Iterations %" PetscInt_FMT "\n", (double)norm, its)); /* Free work space. All PETSc objects should be destroyed when they are no longer needed. */ PetscCall(VecDestroy(&x)); PetscCall(VecDestroy(&r)); PetscCall(VecDestroy(&U)); PetscCall(VecDestroy(&F)); PetscCall(MatDestroy(&J)); PetscCall(SNESDestroy(&snes)); PetscCall(DMDestroy(&ctx.da)); PetscCall(PetscFinalize()); return 0; } /*TEST build: requires: kokkos_kernels test: requires: kokkos_kernels !complex !single nsize: 2 args: -dm_vec_type kokkos -dm_mat_type aijkokkos -view_initial -snes_monitor output_file: output/ex3k_1.out TEST*/