/* 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 > struct array_type { ScalarType gg2[LANDAU_DIM]; ScalarType gg3[LANDAU_DIM][LANDAU_DIM]; KOKKOS_INLINE_FUNCTION // Default constructor - Initialize to 0's array_type() { for (int j = 0; j < LANDAU_DIM; j++){ gg2[j] = 0; for (int k = 0; k < LANDAU_DIM; k++){ gg3[j][k] = 0; } } } KOKKOS_INLINE_FUNCTION // Copy Constructor array_type(const array_type & rhs) { for (int j = 0; j < LANDAU_DIM; j++){ gg2[j] = rhs.gg2[j]; for (int k = 0; k < LANDAU_DIM; k++){ gg3[j][k] = rhs.gg3[j][k]; } } } KOKKOS_INLINE_FUNCTION // add operator array_type& operator += (const array_type& src) { for (int j = 0; j < LANDAU_DIM; j++){ gg2[j] += src.gg2[j]; for (int k = 0; k < LANDAU_DIM; k++){ gg3[j][k] += src.gg3[j][k]; } } return *this; } KOKKOS_INLINE_FUNCTION // volatile add operator void operator += (const volatile array_type& src) volatile { for (int j = 0; j < LANDAU_DIM; j++){ gg2[j] += src.gg2[j]; for (int k = 0; k < LANDAU_DIM; k++){ gg3[j][k] += src.gg3[j][k]; } } } }; typedef array_type TensorValueType; // used to simplify code below } namespace Kokkos { //reduction identity must be defined in Kokkos namespace template<> struct reduction_identity< landau_inner_red::TensorValueType > { KOKKOS_FORCEINLINE_FUNCTION static landau_inner_red::TensorValueType sum() { return landau_inner_red::TensorValueType(); } }; } extern "C" { PetscErrorCode LandauKokkosJacobian(DM plex, const PetscInt Nq, PetscReal nu_alpha[], PetscReal nu_beta[], PetscReal invMass[], PetscReal Eq_m[], const LandauIPData *const IPData, PetscReal invJ[], const PetscInt num_sub_blocks, const PetscLogEvent events[], Mat JacP) { PetscErrorCode ierr; PetscInt *Nbf,Nb,cStart,cEnd,Nf,dim,numCells,totDim,ipdatasz; 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); ierr = DMPlexGetHeightStratum(plex,0,&cStart,&cEnd);CHKERRQ(ierr); numCells = cEnd - cStart; 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); if (LANDAU_DIM != dim) SETERRQ2(PETSC_COMM_WORLD, PETSC_ERR_PLIB, "dim %D != LANDAU_DIM %d",dim,LANDAU_DIM); 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); ipdatasz = LandauGetIPDataSize(IPData); ierr = PetscKokkosInitializeCheck();CHKERRQ(ierr); { 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 = 2*(g2_scr_t::shmem_size(dim,Nf,Nq) + g3_scr_t::shmem_size(dim,dim,Nf,Nq)); 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_ipdata_raw (IPData->w_data,ipdatasz); Kokkos::View d_ipdata_raw ("ipdata", ipdatasz); const Kokkos::View > h_invJ (invJ,IPData->nip_*dim*dim); Kokkos::View d_invJ ("invJ", IPData->nip_*dim*dim); Kokkos::deep_copy (d_ipdata_raw, h_ipdata_raw); 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_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*IPData->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*IPData->nip_);CHKERRQ(ierr); #endif #define KOKKOS_SHARED_LEVEL 1 // PetscInfo2(plex, "shared memory size: %d bytes in level %d\n",scr_bytes,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),dim,Nf,Nq); g3_scr_t g3(team.team_scratch(KOKKOS_SHARED_LEVEL),dim,dim,Nf,Nq); g2_scr_t gg2(team.team_scratch(KOKKOS_SHARED_LEVEL),dim,Nf,Nq); g3_scr_t gg3(team.team_scratch(KOKKOS_SHARED_LEVEL),dim,dim,Nf,Nq); LandauIPData d_IPData; // pack IPData d_IPData.w_data = &d_ipdata_raw[0]; d_IPData.x = &d_ipdata_raw[1*IPData->nip_]; d_IPData.y = &d_ipdata_raw[2*IPData->nip_]; d_IPData.z = &d_ipdata_raw[3*IPData->nip_]; d_IPData.f = &d_ipdata_raw[IPData->nip_*((dim+1) + 0)]; d_IPData.dfx = &d_ipdata_raw[IPData->nip_*((dim+1) + 1*Nf)]; d_IPData.dfy = &d_ipdata_raw[IPData->nip_*((dim+1) + 2*Nf)]; if (dim==2) d_IPData.z = d_IPData.dfz = NULL; else d_IPData.dfz = &d_ipdata_raw[IPData->nip_*((dim+1) + 3*Nf)]; // 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 PetscReal vj[3] = {d_IPData.x[jpidx], d_IPData.y[jpidx], d_IPData.z ? d_IPData.z[jpidx] : 0}, wj = d_IPData.w_data[jpidx]; landau_inner_red::TensorValueType gg_temp; // reduce on part of gg2 and g33 for IP jpidx Kokkos::parallel_reduce(Kokkos::ThreadVectorRange (team, (int)IPData->nip_), [=] (const int& ipidx, landau_inner_red::TensorValueType & ggg) { const PetscReal wi = d_IPData.w_data[ipidx], x = d_IPData.x[ipidx], y = d_IPData.y[ipidx]; PetscReal temp1[3] = {0, 0, 0}, temp2 = 0; PetscInt fieldA,d2,d3; #if LANDAU_DIM==2 PetscReal Ud[2][2], Uk[2][2]; LandauTensor2D(vj, x, y, Ud, Uk, (ipidx==jpidx) ? 0. : 1.); #else PetscReal U[3][3], z = d_IPData.z[ipidx]; LandauTensor3D(vj, x, y, z, U, (ipidx==jpidx) ? 0. : 1.); #endif for (fieldA = 0; fieldA < Nf; ++fieldA) { temp1[0] += d_IPData.dfx[ipidx + fieldA*IPData->nip_]*d_beta[fieldA]*d_invMass[fieldA]; temp1[1] += d_IPData.dfy[ipidx + fieldA*IPData->nip_]*d_beta[fieldA]*d_invMass[fieldA]; #if LANDAU_DIM==3 temp1[2] += d_IPData.dfz[ipidx + fieldA*IPData->nip_]*d_beta[fieldA]*d_invMass[fieldA]; #endif temp2 += d_IPData.f[ipidx + fieldA*IPData->nip_]*d_beta[fieldA]; } temp1[0] *= wi; temp1[1] *= wi; #if LANDAU_DIM==3 temp1[2] *= wi; #endif temp2 *= wi; #if LANDAU_DIM==2 for (d2 = 0; d2 < 2; d2++) { for (d3 = 0; d3 < 2; ++d3) { /* K = U * grad(f): g2=e: i,A */ ggg.gg2[d2] += Uk[d2][d3]*temp1[d3]; /* D = -U * (I \kron (fx)): g3=f: i,j,A */ ggg.gg3[d2][d3] += Ud[d2][d3]*temp2; } } #else for (d2 = 0; d2 < 3; ++d2) { for (d3 = 0; d3 < 3; ++d3) { /* K = U * grad(f): g2 = e: i,A */ ggg.gg2[d2] += U[d2][d3]*temp1[d3]; /* D = -U * (I \kron (fx)): g3 = f: i,j,A */ ggg.gg3[d2][d3] += U[d2][d3]*temp2; } } #endif }, Kokkos::Sum(gg_temp)); //if (myelem==0) printf("\t:%d.%d) temp gg3=%e %e %e %e\n",myelem,myQi,gg_temp.gg3[0][0],gg_temp.gg3[1][0],gg_temp.gg3[0][1],gg_temp.gg3[1][1]); // add alpha and put in gg2/3 Kokkos::parallel_for(Kokkos::ThreadVectorRange (team, (int)Nf), [&] (const int& fieldA) { PetscInt d2,d3; for (d2 = 0; d2 < dim; d2++) { gg2(d2,fieldA,myQi) = gg_temp.gg2[d2]*d_alpha[fieldA]; //if (myelem==0 && fieldA==1) printf("\t\t:%d.%d) gg2[%d]=%e (+= %e)\n",myelem,myQi,d2,gg2(d2,fieldA,myQi),gg_temp.gg2[d2]*d_alpha[fieldA]); //gg2[d2][myQi][fieldA] += gg_temp.gg2[d2]*d_alpha[fieldA]; for (d3 = 0; d3 < dim; d3++) { //gg3[d2][d3][myQi][fieldA] -= gg_temp.gg3[d2][d3]*d_alpha[fieldA]*s_invMass[fieldA]; gg3(d2,d3,fieldA,myQi) = -gg_temp.gg3[d2][d3]*d_alpha[fieldA]*d_invMass[fieldA]; //if (myelem==0 && fieldA==1) printf("\t\t\t:%d.%d) gg3[%d][%d]=%e\n",myelem,myQi,d2,d3,gg3(d2,d3,fieldA,myQi)); } } }); /* add electric field term once per IP */ Kokkos::parallel_for(Kokkos::ThreadVectorRange (team, (int)Nf), [&] (const int& fieldA) { //gg.gg2[fieldA][dim-1] += d_Eq_m[fieldA]; gg2(dim-1,fieldA,myQi) += d_Eq_m[fieldA]; }); // Kokkos::single(Kokkos::PerThread(team), [&]() { Kokkos::parallel_for(Kokkos::ThreadVectorRange (team, (int)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(d,fieldA,myQi) = 0; for (d2 = 0; d2 < dim; ++d2) { g2(d,fieldA,myQi) += invJj[d*dim+d2]*gg2(d2,fieldA,myQi); //if (myelem==0 && myQi==0) printf("\t:g2[%d][%d][%d]=%e. %e %e\n",(int)myQi,(int)fieldA,(int)d,g2(fieldA,myQi,d),invJj[d*dim+d2],gg.gg2[fieldA][d2]); g3(d,d2,fieldA,myQi) = 0; for (d3 = 0; d3 < dim; ++d3) { for (dp = 0; dp < dim; ++dp) { g3(d,d2,fieldA,myQi) += invJj[d*dim + d3]*gg3(d3,dp,fieldA,myQi)*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(d,d2,fieldA,myQi) *= wj; } g2(d,fieldA,myQi) *= wj; } }); }); // Nq team.team_barrier(); /* assemble - on the diagonal (I,I) */ //Kokkos::single(Kokkos::PerTeam(team), [&]() { Kokkos::parallel_for(Kokkos::TeamThreadRange(team,0,Nb), [=] (int blk_i) { Kokkos::parallel_for(Kokkos::ThreadVectorRange(team,0,(int)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(d,fieldA,qj)*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(d,d2,fieldA,qj)*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; PetscPrintf(PETSC_COMM_SELF,"Kokkos Element matrix %d/%d\n",1,(int)numCells); for (d = 0; d < totDim; ++d){ for (f = 0; f < totDim; ++f) PetscPrintf(PETSC_COMM_SELF," %12.5e", PetscRealPart(elMat[d*totDim + f])); PetscPrintf(PETSC_COMM_SELF,"\n"); } } } } #endif ierr = PetscLogEventEnd(events[6],0,0,0,0);CHKERRQ(ierr); } PetscFunctionReturn(0); } } // extern "C"