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» The tao of parallelism in algorithms
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HPDC
2010
IEEE
15 years 7 months ago
A hybrid Markov chain model for workload on parallel computers
This paper proposes a comprehensive modeling architecture for workloads on parallel computers using Markov chains in combination with state dependent empirical distribution functi...
Anne Krampe, Joachim Lepping, Wiebke Sieben
IJON
2007
83views more  IJON 2007»
15 years 6 months ago
Neurospaces: Towards automated model partitioning for parallel computers
Parallel computers have the computing power needed to simulate biologically accurate neuronal network models. Partitioning is the process of cutting a model in pieces and assignin...
Hugo Cornelis, Erik De Schutter
240
Voted
CORR
2012
Springer
281views Education» more  CORR 2012»
14 years 2 months ago
Belief Propagation by Message Passing in Junction Trees: Computing Each Message Faster Using GPU Parallelization
Compiling Bayesian networks (BNs) to junction trees and performing belief propagation over them is among the most prominent approaches to computing posteriors in BNs. However, bel...
Lu Zheng, Ole J. Mengshoel, Jike Chong
ICPP
2000
IEEE
15 years 11 months ago
Runtime Parallel Incremental Scheduling of DAGs
A runtime parallel incremental DAG scheduling approach is described in this paper. A DAG is expanded incrementally, scheduled, and executed on a parallel machine. A DAG scheduling...
Min-You Wu, Wei Shu, Yong Chen
SPAA
1995
ACM
15 years 10 months ago
Provably Efficient Scheduling for Languages with Fine-Grained Parallelism
Many high-level parallel programming languages allow for fine-grained parallelism. As in the popular work-time framework for parallel algorithm design, programs written in such lan...
Guy E. Blelloch, Phillip B. Gibbons, Yossi Matias