1,720,962 research outputs found
Exploring the use of GPGPUs in Constraint Solving
Full text linkThis dissertation presents an experimental study aimed at assessing the feasibility of parallelizing
the constraint solving process using Graphical Processing Units (GPU s). GPUs support a form of data parallelism that appears to be suitable to the type of processing required to cycle through constraints and domain values during consistency checking and propagation. The dissertation also
illustrates an implementation of a constraint solver capable of hybrid propagations (i.e., alternating
CPU and GPU) and parallel search, and demonstrates the potential for competitiveness against
sequential implementations. We consider the Protein Structure Prediction problem as a hard
combinatorial real-world problem as case study to show the advantages of combining parallel search
and parallel constraint propagation on a GPU architecture. We present the formalization and implementation of a novel class of constraints to support a variety of different structural analysis of proteins, such as loop modeling and structure prediction.. We demonstrate the suitability of a GPU approach to implement such MAS infrastructure, with significant performance improvements over the sequential implementation and other methods
A declarative concurrent system for protein structure prediction on GPU
No full textThis paper provides a novel perspective in the protein structure prediction (PSP) problem. The PSP problem focuses on determining putative 3D structures of a protein starting from its primary sequence. The proposed approach relies on a multi-agent system (MAS) perspective, where concurrent agents explore the folding of different parts of a protein. The strength of the approach lies in the agents ability to apply different types of knowledge, expressed in the form of declarative constraints, to prune the search space of folding alternatives. The paper makes also an important contribution in demonstrating the suitability of a general-purpose graphical processing unit approach to implement such MAS infrastructure, with significant performance improvements over the sequential implementation and other method
Large Neighborhood Search with Quality Guarantees for Distributed Constraint Optimization Problems
No full textA GPU Implementation of Large Neighborhood Search for Solving Constraint Optimization Problems.
No full textConstraint programming has gained prominence as an effective and declarative paradigm for modeling and solving complex combinatorial problems. Techniques based on local search have proved practical tosolve real-world problems, providing a good compromise between optimality and efficiency. In spite of the natural presence of concurrency, there has been relatively limited effort to use novel massively parallel architectures, such as those found in modern Graphical Processing Units (GPUs), to speedup local search techniques in constraint programming. This paper describes a novel framework which exploits parallelism from a popular local search method (the Large Neighborhood Search method) using GPUs
GD-Gibbs: A GPU-based sampling algorithm for solving distributed constraint optimization problems
No full textResearchers have recently introduced a promising new class of Distributed Constraint Optimization Problem (DCOP) algorithms that is based on sampling. This paradigm is very amenable to parallelization since sampling algorithms require a lot of samples to ensure convergence, and the sampling process can be designed to be executed in parallel. This paper presents GPU-based D-Gibbs (GD-Gibbs), which extends the Distributed Gibbs (D-Gibbs) sampling algorithm and harnesses the power of parallel computation of GPUs to solve DCOPs. Experimental results show that GD-Gibbs is faster than several other benchmark algorithms on a distributed meeting scheduling problem
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
- …
