2,920 research outputs found
Towards Real-Time Detection and Tracking of Spatio-Temporal Features: Blob-Filaments in Fusion Plasma
A novel algorithm and implementation of real-time identification and tracking
of blob-filaments in fusion reactor data is presented. Similar spatio-temporal
features are important in many other applications, for example, ignition
kernels in combustion and tumor cells in a medical image. This work presents an
approach for extracting these features by dividing the overall task into three
steps: local identification of feature cells, grouping feature cells into
extended feature, and tracking movement of feature through overlapping in
space. Through our extensive work in parallelization, we demonstrate that this
approach can effectively make use of a large number of compute nodes to detect
and track blob-filaments in real time in fusion plasma. On a set of 30GB fusion
simulation data, we observed linear speedup on 1024 processes and completed
blob detection in less than three milliseconds using Edison, a Cray XC30 system
at NERSC.Comment: 14 pages, 40 figure
Recent Advances in Graph Partitioning
We survey recent trends in practical algorithms for balanced graph
partitioning together with applications and future research directions
A pattern language for parallelizing irregular algorithms
Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia InformáticaIn irregular algorithms, data set’s dependences and distributions cannot be statically predicted.
This class of algorithms tends to organize computations in terms of data locality instead of parallelizing control in multiple threads. Thus, opportunities for exploiting parallelism vary dynamically, according to how the algorithm changes data dependences. As such, effective parallelization of such algorithms requires new approaches that account for that dynamic nature.
This dissertation addresses the problem of building efficient parallel implementations of irregular algorithms by proposing to extract, analyze and document patterns of concurrency and parallelism present in the Galois parallelization framework for irregular algorithms.
Patterns capture formal representations of a tangible solution to a problem that arises in a well defined context within a specific domain.
We document the said patterns in a pattern language, i.e., a set of inter-dependent patterns that compose well-documented template solutions that can be reused whenever a certain problem arises in a well-known context
QuickCSG: Fast Arbitrary Boolean Combinations of N Solids
QuickCSG computes the result for general N-polyhedron boolean expressions
without an intermediate tree of solids. We propose a vertex-centric view of the
problem, which simplifies the identification of final geometric contributions,
and facilitates its spatial decomposition. The problem is then cast in a single
KD-tree exploration, geared toward the result by early pruning of any region of
space not contributing to the final surface. We assume strong regularity
properties on the input meshes and that they are in general position. This
simplifying assumption, in combination with our vertex-centric approach,
improves the speed of the approach. Complemented with a task-stealing
parallelization, the algorithm achieves breakthrough performance, one to two
orders of magnitude speedups with respect to state-of-the-art CPU algorithms,
on boolean operations over two to dozens of polyhedra. The algorithm also
outperforms GPU implementations with approximate discretizations, while
producing an output without redundant facets. Despite the restrictive
assumptions on the input, we show the usefulness of QuickCSG for applications
with large CSG problems and strong temporal constraints, e.g. modeling for 3D
printers, reconstruction from visual hulls and collision detection
High-Quality Shared-Memory Graph Partitioning
Partitioning graphs into blocks of roughly equal size such that few edges run
between blocks is a frequently needed operation in processing graphs. Recently,
size, variety, and structural complexity of these networks has grown
dramatically. Unfortunately, previous approaches to parallel graph partitioning
have problems in this context since they often show a negative trade-off
between speed and quality. We present an approach to multi-level shared-memory
parallel graph partitioning that guarantees balanced solutions, shows high
speed-ups for a variety of large graphs and yields very good quality
independently of the number of cores used. For example, on 31 cores, our
algorithm partitions our largest test instance into 16 blocks cutting less than
half the number of edges than our main competitor when both algorithms are
given the same amount of time. Important ingredients include parallel label
propagation for both coarsening and improvement, parallel initial partitioning,
a simple yet effective approach to parallel localized local search, and fast
locality preserving hash tables
The Double Hierarchy Method: a parallel 3D contact method for the interaction of spherical particles with rigid FE boundaries using the DEM
The final publication is available at Springer via http://dx.doi.org/10.1007/s40571-016-0109-4In this work, we present a new methodology for the treatment of the contact interaction between rigid boundaries and spherical discrete elements (DE). Rigid body parts are present in most of large-scale simulations. The surfaces of the rigid parts are commonly meshed with a finite element-like (FE) discretization. The contact detection and calculation between those DE and the discretized boundaries is not straightforward and has been addressed by different approaches. The algorithm presented in this paper considers the contact of the DEs with the geometric primitives of a FE mesh, i.e. facet, edge or vertex. To do so, the original hierarchical method presented by Horner et al. (J Eng Mech 127(10):1027–1032, 2001) is extended with a new insight leading to a robust, fast and accurate 3D contact algorithm which is fully parallelizable. The implementation of the method has been developed in order to deal ideally with triangles and quadrilaterals. If the boundaries are discretized with another type of geometries, the method can be easily extended to higher order planar convex polyhedra. A detailed description of the procedure followed to treat a wide range of cases is presented. The description of the developed algorithm and its validation is verified with several practical examples. The parallelization capabilities and the obtained performance are presented with the study of an industrial application example.Peer ReviewedPostprint (author's final draft
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