| /petsc/src/ts/tutorials/output/ |
| H A D | ex20td_track.out | 10 sensitivity wrt mu1: d[cost]/d[mu1] 19 sensitivity wrt mu2: d[cost]/d[mu2] 28 sensitivity wrt initial conditions: d[cost]/d[u(t=0)]
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| H A D | ex20td_global.out | 10 sensitivity wrt params: d[cost]/d[p], where p refers to 25 sensitivity wrt initial conditions: d[cost]/d[u(t=0)]
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| /petsc/src/ts/impls/implicit/glle/ |
| H A D | glleadapt.c | 185 …Int n, const PetscInt orders[], const PetscReal errors[], const PetscReal cost[], PetscInt cur, Pe… in TSGLLEAdaptChoose() argument 191 PetscAssertPointer(cost, 5); in TSGLLEAdaptChoose() 195 …PetscUseTypeMethod(adapt, choose, n, orders, errors, cost, cur, h, tleft, next_sc, next_h, finish); in TSGLLEAdaptChoose() 226 …Int n, const PetscInt orders[], const PetscReal errors[], const PetscReal cost[], PetscInt cur, Pe… in TSGLLEAdaptChoose_None() argument 254 …Int n, const PetscInt orders[], const PetscReal errors[], const PetscReal cost[], PetscInt cur, Pe… in TSGLLEAdaptChoose_Size() argument 295 …Int n, const PetscInt orders[], const PetscReal errors[], const PetscReal cost[], PetscInt cur, Pe… in TSGLLEAdaptChoose_Both() argument 311 trial.eff = trial.h / cost[i]; in TSGLLEAdaptChoose_Both() 325 PetscReal rat = cost[best.id] / cost[cur]; in TSGLLEAdaptChoose_Both()
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| /petsc/doc/manualpages/MANSECHeaders/ |
| H A D | Sensitivity | 6 The adjoint solvers support gradient calculation for multiple cost functions, and the tangent linea… 7 Adjoint is particularly efficient when the number of cost functions is much less than the number of… 10 Typical cost functions of interest may depend on the final solution to the ODE/DAE or on the whole …
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| H A D | DMLabel | 7 but each bin is then sorted so that extraction into sorted levels is also $O(1)$. The total cost sh…
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| /petsc/src/ts/tutorials/power_grid/output/ |
| H A D | ex3sa_2.out | 8 cost function=11.4129
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| H A D | ex3sa_1.out | 13 cost function=11.4129
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| H A D | ex3sa_3.out | 13 cost function=11.304
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| H A D | ex9adj_1.out | 18 cost function=7.6129
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| H A D | ex3adj_events_1.out | 18 cost function=11.2836
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| /petsc/src/ts/adapt/interface/ |
| H A D | tsadapt.c | 834 … char name[], PetscInt order, PetscInt stageorder, PetscReal ccfl, PetscReal cost, PetscBool inuse) in TSAdaptCandidateAdd() argument 852 adapt->candidates.cost[c] = cost; in TSAdaptCandidateAdd() 879 …onst PetscInt **order, const PetscInt **stageorder, const PetscReal **ccfl, const PetscReal **cost) in TSAdaptCandidatesGet() argument 887 if (cost) *cost = adapt->candidates.cost; in TSAdaptCandidatesGet()
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| /petsc/src/snes/tutorials/network/power/ |
| H A D | case9.m | 58 %% generator cost data
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| /petsc/doc/manual/ |
| H A D | ts.md | 1125 and the cost function(s) 1128 \Psi_i(y_0,p) = \Phi_i(y_F,p) + \int_{t_0}^{t_F} r_i(y(t),p,t)dt \quad i=1,...,n_\text{cost}. 1153 One must create two arrays of $n_\text{cost}$ vectors 1168 where `numcost` denotes $n_\text{cost}$. 1187 If there is an integral term in the cost function, i.e. $r$ is 1212 Since the integral term is additive to the cost function, its gradient 1269 cost function 1292 After `TSAdjointSolve()`, the sensitivity of the cost function w.r.t. 1294 (at time $t_0$) directly. And the sensitivity of the cost function 1319 Theta methods for cost function with an integral term [all …]
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| H A D | ksp.md | 1151 …> stronger the Krylov method the faster the convergence, but with more cost per iteration. See `… 1153 …> , the faster the convergence, but with more cost per multigrid iteration. See `PCMGSetNumberSm… 1156 > stronger the preconditioner the faster the convergence, but with more cost per iteration. 1253 has additional cost, users should indicate the symmetry of the matrices they 1313 increasing the coarsening rate and thereby decreasing the cost of the
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| H A D | vec.md | 1508 …terGetAttributes()` or `hipPointerGetAttributes()`) is not trivial. To avoid the cost of the check,
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| H A D | mat.md | 659 but they try to minimize memory transfer at the cost of storage
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| H A D | tao.md | 1802 predicted versus actual reduction in the cost function. The trust radius
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| /petsc/src/binding/petsc4py/src/petsc4py/PETSc/ |
| H A D | TS.pyx | 2633 """Return a vector of values of the integral term in the cost functions. 2642 cdef Vec cost = Vec() 2643 CHKERR(TSGetCostIntegral(self.ts, &cost.vec)) 2644 CHKERR(PetscINCREF(cost.obj)) 2645 return cost 2651 """Set the cost gradients. 2694 """Return the cost gradients.
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| /petsc/src/ts/tutorials/ |
| H A D | ex11.c | 228 PetscReal x0[DIM], v[DIM], r, cost, sint; in PhysicsSolution_Advect() local 229 cost = PetscCosReal(time); in PhysicsSolution_Advect() 231 x0[0] = cost * x[0] + sint * x[1]; in PhysicsSolution_Advect() 232 x0[1] = -sint * x[0] + cost * x[1]; in PhysicsSolution_Advect()
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| /petsc/include/petsc/private/ |
| H A D | tsimpl.h | 360 … PetscReal cost[16]; /* relative measure of the amount of work required for each scheme */ member
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| /petsc/doc/tutorials/physics/ |
| H A D | guide_to_stokes.md | 194 …A^{-1} B$. We can have PETSc construct that matrix automatically, but the cost rises steeply as th… 837 …p will be to replace the direct solve of the momentum operator, which has cost superlinear in $N$,…
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| /petsc/lib/petsc/bin/maint/abi-compliance-checker/ |
| H A D | LICENSE | 309 than the cost of performing this distribution.
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| /petsc/doc/ |
| H A D | petsc.bib | 1910 % LiteralHTML:Treating fractures of the hip and spine is a major medical cost. 11185 title = {The cost of continuity: A study of the performance of isogeometric finite 21375 title = {Low-cost parallel algorithms for 2: 1 octree balance}, 23730 title = {On the cost of iterative computations}, 26753 methods: cost function minimization and projection onto convex sets}, 30477 title = {Toward a more comprehensive cost measure for {CO2}-reductions},
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