Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: trlib: A vector-free implementation of the GLTR method for iterative
  solution of the trust region problem   We describe trlib, a library that implements a variant of Gould's Generalized
Lanczos method (Gould et al. in SIAM J. Opt. 9(2), 504-525, 1999) for solving
the trust region problem.
  Our implementation has several distinct features that set it apart from
preexisting ones. We implement both conjugate gradient (CG) and Lanczos
iterations for assembly of Krylov subspaces. A vector- and matrix-free reverse
communication interface allows the use of most general data structures, such as
those arising after discretization of function space problems. The hard case of
the trust region problem frequently arises in sequential methods for nonlinear
optimization. In this implementation, we made an effort to fully address the
hard case in an exact way by considering all invariant Krylov subspaces.
  We investigate the numerical performance of trlib on the full subset of
unconstrained problems of the CUTEst benchmark set. In addition to this,
interfacing the PDE discretization toolkit FEniCS with trlib using the
vector-free reverse communication interface is demonstrated for a family of
PDE-constrained control trust region problems adapted from the OPTPDE
collection.

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The categories of this paper are: hep-ph
13
The categories of this paper are: quant-ph
10
The categories of this paper are: q-bio
28
The categories of this paper are: alg-geom
22
The categories of this paper are: chao-dyn
24
The categories of this paper are: dg-ga
4
The categories of this paper are: cond-mat
26
The categories of this paper are: bayes-an
1
The categories of this paper are: cs
5
The categories of this paper are: gr-qc
16
The categories of this paper are: stat
32
The categories of this paper are: atom-ph
9
The categories of this paper are: nlin
30
The categories of this paper are: q-alg
27
The categories of this paper are: comp-gas
36
The categories of this paper are: cmp-lg