/* Implements the Kokkos kernel */ #define PETSC_SKIP_CXX_COMPLEX_FIX #include #include /*I "petscdmplex.h" I*/ #include #include #include #include typedef Kokkos::TeamPolicy<>::member_type team_member; #define PETSC_DEVICE_FUNC_DECL KOKKOS_INLINE_FUNCTION #include "../land_tensors.h" namespace landau_inner_red { // namespace helps with name resolution in reduction identity template< class ScalarType, int Nf > struct array_type { ScalarType gg2[Nf][LANDAU_DIM]; ScalarType gg3[Nf][LANDAU_DIM][LANDAU_DIM]; KOKKOS_INLINE_FUNCTION // Default constructor - Initialize to 0's array_type() { for (int i = 0; i < Nf; i++){ for (int j = 0; j < LANDAU_DIM; j++){ gg2[i][j] = 0; for (int k = 0; k < LANDAU_DIM; k++){ gg3[i][j][k] = 0; } } } } KOKKOS_INLINE_FUNCTION // Copy Constructor array_type(const array_type & rhs) { for (int i = 0; i < Nf; i++){ for (int j = 0; j < LANDAU_DIM; j++){ gg2[i][j] = rhs.gg2[i][j]; for (int k = 0; k < LANDAU_DIM; k++){ gg3[i][j][k] = rhs.gg3[i][j][k]; } } } } KOKKOS_INLINE_FUNCTION // add operator array_type& operator += (const array_type& src) { for (int i = 0; i < Nf; i++){ for (int j = 0; j < LANDAU_DIM; j++){ gg2[i][j] += src.gg2[i][j]; for (int k = 0; k < LANDAU_DIM; k++){ gg3[i][j][k] += src.gg3[i][j][k]; } } } return *this; } KOKKOS_INLINE_FUNCTION // volatile add operator void operator += (const volatile array_type& src) volatile { for (int i = 0; i < Nf; i++){ for (int j = 0; j < LANDAU_DIM; j++){ gg2[i][j] += src.gg2[i][j]; for (int k = 0; k < LANDAU_DIM; k++){ gg3[i][j][k] += src.gg3[i][j][k]; } } } } }; typedef array_type ValueType; // used to simplify code below } namespace Kokkos { //reduction identity must be defined in Kokkos namespace template<> struct reduction_identity< landau_inner_red::ValueType > { KOKKOS_FORCEINLINE_FUNCTION static landau_inner_red::ValueType sum() { return landau_inner_red::ValueType(); } }; } extern "C" { PetscErrorCode LandauKokkosJacobian(DM plex, const PetscInt Nq, PetscReal nu_alpha[], PetscReal nu_beta[], PetscReal invMass[], PetscReal Eq_m[], PetscReal * const IPDataGlobal, PetscReal wiGlobal[], PetscReal invJ[], const PetscInt num_sub_blocks, const PetscLogEvent events[], PetscBool quarter3DDomain, Mat JacP) { PetscErrorCode ierr; PetscInt *Nbf,Nb,cStart,cEnd,Nf,dim,numCells,totDim,nip; PetscTabulation *Tf; PetscDS prob; PetscSection section, globalSection; PetscLogDouble flops; PetscReal *BB,*DD; LandauCtx *ctx; PetscFunctionBegin; ierr = DMGetApplicationContext(plex, &ctx);CHKERRQ(ierr); if (!ctx) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_PLIB, "no context"); ierr = DMGetDimension(plex, &dim);CHKERRQ(ierr); if (dim!=LANDAU_DIM) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_PLIB, "LANDAU_DIM != dim"); ierr = DMPlexGetHeightStratum(plex,0,&cStart,&cEnd);CHKERRQ(ierr); numCells = cEnd - cStart; nip = numCells*Nq; ierr = DMGetDS(plex, &prob);CHKERRQ(ierr); ierr = PetscDSGetNumFields(prob, &Nf);CHKERRQ(ierr); ierr = PetscDSGetDimensions(prob, &Nbf);CHKERRQ(ierr); Nb = Nbf[0]; if (Nq != Nb) SETERRQ2(PETSC_COMM_SELF, PETSC_ERR_PLIB, "Nq != Nb. %D %D",Nq,Nb); ierr = PetscDSGetTotalDimension(prob, &totDim);CHKERRQ(ierr); ierr = PetscDSGetTabulation(prob, &Tf);CHKERRQ(ierr); BB = Tf[0]->T[0]; DD = Tf[0]->T[1]; ierr = DMGetLocalSection(plex, §ion);CHKERRQ(ierr); ierr = DMGetGlobalSection(plex, &globalSection);CHKERRQ(ierr); flops = (PetscLogDouble)numCells*Nq*(5*dim*dim*Nf*Nf + 165); if (!Kokkos::is_initialized()){ int argc = 1; char string[1][32], *argv[1] = {string[0]}; ierr = PetscStrcpy(string[0],"landau");CHKERRQ(ierr); Kokkos::initialize(argc, argv); } #if defined(KOKKOS_ENABLE_CXX11_DISPATCH_LAMBDA) #else SETERRQ(PETSC_COMM_WORLD, PETSC_ERR_PLIB, "no KOKKOS_ENABLE_CXX11_DISPATCH_LAMBDA"); #endif { using scr_mem_t = Kokkos::DefaultExecutionSpace::scratch_memory_space; using g2_scr_t = Kokkos::View; using g3_scr_t = Kokkos::View; const int scr_bytes = g2_scr_t::shmem_size(Nf,Nq,dim) + g3_scr_t::shmem_size(Nf,Nq,dim,dim); ierr = PetscLogEventBegin(events[3],0,0,0,0);CHKERRQ(ierr); Kokkos::View d_elem_mats("element matrices", numCells, totDim*totDim); Kokkos::View::HostMirror h_elem_mats = Kokkos::create_mirror_view(d_elem_mats); const Kokkos::View > h_alpha (nu_alpha, Nf); Kokkos::View d_alpha ("nu_alpha", Nf); const Kokkos::View > h_beta (nu_beta, Nf); Kokkos::View d_beta ("nu_beta", Nf); const Kokkos::View > h_invMass (invMass,Nf); Kokkos::View d_invMass ("invMass", Nf); const Kokkos::View > h_Eq_m (Eq_m,Nf); Kokkos::View d_Eq_m ("Eq_m", Nf); const Kokkos::View > h_BB (BB,Nq*Nb); Kokkos::View d_BB ("BB", Nq*Nb); const Kokkos::View > h_DD (DD,Nq*Nb*dim); Kokkos::View d_DD ("DD", Nq*Nb*dim); const Kokkos::View > h_wiGlobal (wiGlobal,nip); Kokkos::View d_wiGlobal ("wiGlobal", nip); const Kokkos::View > h_ipdata (IPDataGlobal,nip*(dim + Nf*(dim+1))); Kokkos::View d_ipdata ("ipdata", nip*(dim + Nf*(dim+1))); const Kokkos::View > h_invJ (invJ,nip*dim*dim); Kokkos::View d_invJ ("invJ", nip*dim*dim); Kokkos::deep_copy (d_alpha, h_alpha); Kokkos::deep_copy (d_beta, h_beta); Kokkos::deep_copy (d_invMass, h_invMass); Kokkos::deep_copy (d_Eq_m, h_Eq_m); Kokkos::deep_copy (d_BB, h_BB); Kokkos::deep_copy (d_DD, h_DD); Kokkos::deep_copy (d_wiGlobal, h_wiGlobal); Kokkos::deep_copy (d_ipdata, h_ipdata); Kokkos::deep_copy (d_invJ, h_invJ); ierr = PetscLogEventEnd(events[3],0,0,0,0);CHKERRQ(ierr); ierr = PetscLogEventBegin(events[4],0,0,0,0);CHKERRQ(ierr); #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_VIENNACL) ierr = PetscLogGpuFlops(flops*nip);CHKERRQ(ierr); if (ctx->deviceType == LANDAU_CPU) PetscInfo(plex, "Warning: Landau selected CPU but no support for Kokkos using GPU\n"); #else ierr = PetscLogFlops(flops*nip);CHKERRQ(ierr); #endif #define KOKKOS_SHARED_LEVEL 1 //PetscInfo2(plex, "shared memory size: %D kB in level %d\n",Nf*Nq*dim*(dim+1)*sizeof(PetscReal)/1024,KOKKOS_SHARED_LEVEL); int conc = Kokkos::DefaultExecutionSpace().concurrency(), team_size = conc > Nq ? Nq : 1; Kokkos::parallel_for("Landau_elements", Kokkos::TeamPolicy<>(numCells, team_size, num_sub_blocks).set_scratch_size(KOKKOS_SHARED_LEVEL, Kokkos::PerTeam(scr_bytes)), KOKKOS_LAMBDA (const team_member team) { const PetscInt myelem = team.league_rank(); g2_scr_t g2(team.team_scratch(KOKKOS_SHARED_LEVEL),Nf,Nq,dim); g3_scr_t g3(team.team_scratch(KOKKOS_SHARED_LEVEL),Nf,Nq,dim,dim); // get g2[] & g3[] Kokkos::parallel_for(Kokkos::TeamThreadRange(team,0,Nq), [=] (int myQi) { using Kokkos::parallel_reduce; const PetscInt jpidx = myQi + myelem * Nq; const PetscReal * const invJj = &d_invJ(jpidx*dim*dim); const PetscInt ipdata_sz = (dim + Nf*(1+dim)); const LandauPointData * const fplpt_j = (LandauPointData*)(&d_ipdata(jpidx*ipdata_sz)); const PetscReal * const vj = fplpt_j->crd, wj = d_wiGlobal[jpidx]; // reduce on g22 and g33 for IP jpidx landau_inner_red::ValueType gg; Kokkos::parallel_reduce(Kokkos::ThreadVectorRange (team, nip), [=] (const int& ipidx, landau_inner_red::ValueType & ggg) { const LandauPointData * const fplpt = (LandauPointData*)(&d_ipdata(ipidx*ipdata_sz)); const LandauFDF * const fdf = &fplpt->fdf[0]; const PetscReal wi = d_wiGlobal[ipidx]; PetscInt fieldA,fieldB,d2,d3; #if LANDAU_DIM==2 PetscReal Ud[2][2], Uk[2][2]; LandauTensor2D(vj, fplpt->crd[0], fplpt->crd[1], Ud, Uk, (ipidx==jpidx) ? 0. : 1.); for (fieldA = 0; fieldA < Nf; ++fieldA) { for (fieldB = 0; fieldB < Nf; ++fieldB) { for (d2 = 0; d2 < 2; ++d2) { for (d3 = 0; d3 < 2; ++d3) { /* K = U * grad(f): g2=e: i,A */ ggg.gg2[fieldA][d2] += d_alpha[fieldA]*d_beta[fieldB] * d_invMass[fieldB] * Uk[d2][d3] * fdf[fieldB].df[d3] * wi; /* D = -U * (I \kron (fx)): g3=f: i,j,A */ ggg.gg3[fieldA][d2][d3] -= d_alpha[fieldA]*d_beta[fieldB] * d_invMass[fieldA] * Ud[d2][d3] * fdf[fieldB].f * wi; } } } } #else PetscReal U[3][3]; LandauTensor3D(vj, fplpt->crd[0], fplpt->crd[1], fplpt->crd[2], U, (ipidx==jpidx) ? 0. : 1.); for (fieldA = 0; fieldA < Nf; ++fieldA) { for (fieldB = 0; fieldB < Nf; ++fieldB) { for (d2 = 0; d2 < 3; ++d2) { for (d3 = 0; d3 < 3; ++d3) { /* K = U * grad(f): g2 = e: i,A */ ggg.gg2[fieldA][d2] += d_alpha[fieldA]*d_beta[fieldB] * d_invMass[fieldB] * U[d2][d3] * fplpt->fdf[fieldB].df[d3] * wi; /* D = -U * (I \kron (fx)): g3 = f: i,j,A */ ggg.gg3[fieldA][d2][d3] -= d_alpha[fieldA]*d_beta[fieldB] * d_invMass[fieldA] * U[d2][d3] * fplpt->fdf[fieldB].f * wi; } } } } #endif }, Kokkos::Sum(gg)); Kokkos::parallel_for(Kokkos::ThreadVectorRange (team, Nf), [&] (const int& fieldA) { gg.gg2[fieldA][dim-1] += d_Eq_m[fieldA]; }); //kkos::single(Kokkos::PerThread(team), [&]() { Kokkos::parallel_for(Kokkos::ThreadVectorRange (team, Nf), [=] (const int& fieldA) { int d,d2,d3,dp; //printf("%d %d %d gg2[][1]=%18.10e\n",myelem,myQi,fieldA,gg.gg2[fieldA][dim-1]); /* Jacobian transform - g2, g3 - per thread (2D) */ for (d = 0; d < dim; ++d) { g2(fieldA,myQi,d) = 0; for (d2 = 0; d2 < dim; ++d2) { g2(fieldA,myQi,d) += invJj[d*dim+d2]*gg.gg2[fieldA][d2]; //printf("\t\t%d %d %d %d %d g2[%d][%d][%d]=%g\n",myelem,myQi,fieldA,d,d2,fieldA,myQi,d,g2(fieldA,myQi,d)); g3(fieldA,myQi,d,d2) = 0; for (d3 = 0; d3 < dim; ++d3) { for (dp = 0; dp < dim; ++dp) { g3(fieldA,myQi,d,d2) += invJj[d*dim + d3]*gg.gg3[fieldA][d3][dp]*invJj[d2*dim + dp]; //printf("\t%d %d %d %d %d %d %d g3=%g wj=%g g3 = %g * %g * %g\n",myelem,myQi,fieldA,d,d2,d3,dp,g3(fieldA,myQi,d,d2),wj,invJj[d*dim + d3],gg.gg3[fieldA][d3][dp],invJj[d2*dim + dp]); } } g3(fieldA,myQi,d,d2) *= wj; } g2(fieldA,myQi,d) *= wj; } }); }); team.team_barrier(); /* assemble - on the diagonal (I,I) */ //Kokkos::single(Kokkos::PerTeam(team), [&]() { { // int fieldA,blk_i; Kokkos::parallel_for(Kokkos::TeamThreadRange(team,0,Nb), [=] (int blk_i) { Kokkos::parallel_for(Kokkos::ThreadVectorRange(team,0,Nf), [=] (int fieldA) { //for (fieldA = 0; fieldA < Nf; ++fieldA) { //for (blk_i = 0; blk_i < Nb; ++blk_i) { int blk_j,qj,d,d2; const PetscInt i = fieldA*Nb + blk_i; /* Element matrix row */ for (blk_j = 0; blk_j < Nb; ++blk_j) { const PetscInt j = fieldA*Nb + blk_j; /* Element matrix column */ const PetscInt fOff = i*totDim + j; for (qj = 0 ; qj < Nq ; qj++) { // look at others integration points const PetscReal *BJq = &d_BB[qj*Nb], *DIq = &d_DD[qj*Nb*dim]; for (d = 0; d < dim; ++d) { d_elem_mats(myelem,fOff) += DIq[blk_i*dim+d]*g2(fieldA,qj,d)*BJq[blk_j]; //printf("\tmat[%d %d %d %d %d]=%g D[%d]=%g g2[%d][%d][%d]=%g B=%g\n",myelem,fOff,fieldA,qj,d,d_elem_mats(myelem,fOff),blk_i*dim+d,DIq[blk_i*dim+d],fieldA,qj,d,g2(fieldA,qj,d),BJq[blk_j]); for (d2 = 0; d2 < dim; ++d2) { d_elem_mats(myelem,fOff) += DIq[blk_i*dim + d]*g3(fieldA,qj,d,d2)*DIq[blk_j*dim + d2]; } } } } }); }); } }); Kokkos::fence(); ierr = PetscLogEventEnd(events[4],0,0,0,0);CHKERRQ(ierr); ierr = PetscLogEventBegin(events[5],0,0,0,0);CHKERRQ(ierr); Kokkos::deep_copy (h_elem_mats, d_elem_mats); ierr = PetscLogEventEnd(events[5],0,0,0,0);CHKERRQ(ierr); ierr = PetscLogEventBegin(events[6],0,0,0,0);CHKERRQ(ierr); #if defined(PETSC_HAVE_OPENMP) { PetscContainer container = NULL; ierr = PetscObjectQuery((PetscObject)JacP,"coloring",(PetscObject*)&container);CHKERRQ(ierr); if (!container) { ierr = PetscLogEventBegin(events[8],0,0,0,0);CHKERRQ(ierr); ierr = LandauCreateColoring(JacP, plex, &container);CHKERRQ(ierr); ierr = PetscLogEventEnd(events[8],0,0,0,0);CHKERRQ(ierr); } ierr = LandauAssembleOpenMP(cStart, cEnd, totDim, plex, section, globalSection, JacP, &h_elem_mats(0,0), container);CHKERRQ(ierr); } #else { PetscInt ej; for (ej = cStart ; ej < cEnd; ++ej) { const PetscScalar *elMat = &h_elem_mats(ej-cStart,0); ierr = DMPlexMatSetClosure(plex, section, globalSection, JacP, ej, elMat, ADD_VALUES);CHKERRQ(ierr); if (ej==-1) { int d,f; printf("Kokkos Element matrix %d/%d\n",1,numCells); for (d = 0; d < totDim; ++d){ for (f = 0; f < totDim; ++f) printf(" %17.9e", PetscRealPart(elMat[d*totDim + f])); printf("\n"); } } } } #endif ierr = PetscLogEventEnd(events[6],0,0,0,0);CHKERRQ(ierr); } PetscFunctionReturn(0); } } // extern "C"