3,466 research outputs found
Parallel local search for solving Constraint Problems on the Cell Broadband Engine (Preliminary Results)
We explore the use of the Cell Broadband Engine (Cell/BE for short) for
combinatorial optimization applications: we present a parallel version of a
constraint-based local search algorithm that has been implemented on a
multiprocessor BladeCenter machine with twin Cell/BE processors (total of 16
SPUs per blade). This algorithm was chosen because it fits very well the
Cell/BE architecture and requires neither shared memory nor communication
between processors, while retaining a compact memory footprint. We study the
performance on several large optimization benchmarks and show that this
achieves mostly linear time speedups, even sometimes super-linear. This is
possible because the parallel implementation might explore simultaneously
different parts of the search space and therefore converge faster towards the
best sub-space and thus towards a solution. Besides getting speedups, the
resulting times exhibit a much smaller variance, which benefits applications
where a timely reply is critical
AI Methods in Algorithmic Composition: A Comprehensive Survey
Algorithmic composition is the partial or total automation of the process of music composition
by using computers. Since the 1950s, different computational techniques related to
Artificial Intelligence have been used for algorithmic composition, including grammatical
representations, probabilistic methods, neural networks, symbolic rule-based systems, constraint
programming and evolutionary algorithms. This survey aims to be a comprehensive
account of research on algorithmic composition, presenting a thorough view of the field for
researchers in Artificial Intelligence.This study was partially supported by a grant for the MELOMICS project
(IPT-300000-2010-010) from the Spanish Ministerio de Ciencia e Innovación, and a grant for
the CAUCE project (TSI-090302-2011-8) from the Spanish Ministerio de Industria, Turismo
y Comercio. The first author was supported by a grant for the GENEX project (P09-TIC-
5123) from the ConsejerÃa de Innovación y Ciencia de AndalucÃa
A Functional Taxonomy of Music Generation Systems
Digital advances have transformed the face of automatic music generation
since its beginnings at the dawn of computing. Despite the many breakthroughs,
issues such as the musical tasks targeted by different machines and the degree
to which they succeed remain open questions. We present a functional taxonomy
for music generation systems with reference to existing systems. The taxonomy
organizes systems according to the purposes for which they were designed. It
also reveals the inter-relatedness amongst the systems. This design-centered
approach contrasts with predominant methods-based surveys and facilitates the
identification of grand challenges to set the stage for new breakthroughs.Comment: survey, music generation, taxonomy, functional survey, survey,
automatic composition, algorithmic compositio
Faculty Excellence
Each year, the University of New Hampshire selects a small number of its outstanding faculty for special recognition of their achievements in teaching, scholarship and service. Awards for Excellence in Teaching are given in each college and school, and university-wide awards recognize public service, research, teaching and engagement. This booklet details the year\u27s award winners\u27 accomplishments in short profiles with photographs and text
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