Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Parallelized integrated nested Laplace approximations for fast Bayesian
  inference   There is a growing demand for performing larger-scale Bayesian inference
tasks, arising from greater data availability and higher-dimensional model
parameter spaces. In this work we present parallelization strategies for the
methodology of integrated nested Laplace approximations (INLA), a popular
framework for performing approximate Bayesian inference on the class of Latent
Gaussian models. Our approach makes use of nested OpenMP parallelism, a
parallel line search procedure using robust regression in INLA's optimization
phase and the state-of-the-art sparse linear solver PARDISO. We leverage
mutually independent function evaluations in the algorithm as well as advanced
sparse linear algebra techniques. This way we can flexibly utilize the power of
today's multi-core architectures. We demonstrate the performance of our new
parallelization scheme on a number of different real-world applications. The
introduction of parallelism leads to speedups of a factor 10 and more for all
larger models. Our work is already integrated in the current version of the
open-source R-INLA package, making its improved performance conveniently
available to all users.

0
The categories of this paper are: hep-ph
25
The categories of this paper are: patt-sol
6
The categories of this paper are: astro-ph
5
The categories of this paper are: gr-qc
34
The categories of this paper are: chem-ph
28
The categories of this paper are: alg-geom
23
The categories of this paper are: solv-int
11
The categories of this paper are: hep-lat
21
The categories of this paper are: adap-org
22
The categories of this paper are: chao-dyn
13
The categories of this paper are: quant-ph
36
The categories of this paper are: cmp-lg
3
The categories of this paper are: physics
24
The categories of this paper are: dg-ga
27
The categories of this paper are: comp-gas
2
The categories of this paper are: math