Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Hierarchical Performance Modeling for Ranking Dense Linear Algebra
  Algorithms   A large class of dense linear algebra operations, such as LU decomposition or
inversion of a triangular matrix, are usually performed by blocked algorithms.
For one such operation, typically, not only one but many algorithmic variants
exist; depending on computing architecture, libraries and problem size, each
variant attains a different performances. We propose methods and tools to rank
the algorithmic variants according to their performance for a given scenario
without executing them.
  For this purpose, we identify the routines upon which the algorithms are
built. A first tool - the Sampler - measures the performance of these routines.
Using the Sampler, a second tool models their performance. The generated models
are then used to predict the performance of the considered algorithms. For a
given scenario, these predictions allow us to correctly rank the algorithms
according to their performance without executing them. With the help of the
same tools, algorithmic parameters such as block-size can be optimally tuned.

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The categories of this paper are: chao-dyn
30
The categories of this paper are: q-alg
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The categories of this paper are: alg-geom
33
The categories of this paper are: plasm-ph
18
The categories of this paper are: econ
15
The categories of this paper are: nucl-ex
23
The categories of this paper are: solv-int
32
The categories of this paper are: atom-ph
14
The categories of this paper are: math-ph
34
The categories of this paper are: chem-ph
12
The categories of this paper are: nucl-th
21
The categories of this paper are: adap-org
5
The categories of this paper are: gr-qc
6
The categories of this paper are: astro-ph
10
The categories of this paper are: q-bio
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The categories of this paper are: patt-sol