Search results for "Concurrent computing"

showing 5 items of 5 documents

Concurrent Computing with Shared Replicated Memory

2019

Any concurrent system can be captured by a concurrent Abstract State Machine (cASM). This remains valid, if different agents can only interact via messages. It even permits a strict separation between memory managing agents and other agents that can only access the shared memory by sending query and update requests. This paper is dedicated to an investigation of replicated data that is maintained by a memory management subsystem, where the replication neither appears in the requests nor in the corresponding answers. We specify the behaviour of a concurrent system with such memory management using concurrent communicating ASMs (ccASMs), provide several refinements addressing different replic…

Computer scienceDistributed computing020207 software engineering0102 computer and information sciences02 engineering and technology01 natural sciencesReplication (computing)Consistency (database systems)Memory managementShared memory010201 computation theory & mathematics0202 electrical engineering electronic engineering information engineeringAbstract state machinesConcurrent computingVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550
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A distributed dynamic load balancer and its implementation on multi-transputer systems for molecular dynamics simulation

1990

Abstract A new and efficient approach is described to the dynamic load-balancing problem which is central in concurrent computing. A transputer-based implementation is tested on a molecular dynamics simulation of spinodal phase separation.

Dynamic simulationSpinodalMolecular dynamicsPhase transitionHardware and ArchitectureSpinodal decompositionComputer scienceTransputerGeneral Physics and AstronomyConcurrent computingParallel computingDynamic load testingComputer Physics Communications
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Heterogeneous PBLAS: Optimization of PBLAS for Heterogeneous Computational Clusters

2008

This paper presents a package, called Heterogeneous PBLAS (HeteroPBLAS), which is built on top of PBLAS and provides optimized parallel basic linear algebra subprograms for heterogeneous computational clusters. We present the user interface and the software hierarchy of the first research implementation of HeteroPBLAS. This is the first step towards the development of a parallel linear algebra package for heterogeneous computational clusters. We demonstrate the efficiency of the HeteroPBLAS programs on a homogeneous computing cluster and a heterogeneous computing cluster.

Kernel (linear algebra)ScaLAPACKComputer scienceComputer clusterLinear algebraCluster (physics)Concurrent computingSymmetric multiprocessor systemParallel computingBasic Linear Algebra SubprogramsComputational science2008 International Symposium on Parallel and Distributed Computing
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Experimental Study of Six Different Implementations of Parallel Matrix Multiplication on Heterogeneous Computational Clusters of Multicore Processors

2010

Two strategies of distribution of computations can be used to implement parallel solvers for dense linear algebra problems for Heterogeneous Computational Clusters of Multicore Processors (HCoMs). These strategies are called Heterogeneous Process Distribution Strategy (HPS) and Heterogeneous Data Distribution Strategy (HDS). They are not novel and have been researched thoroughly. However, the advent of multicores necessitates enhancements to them. In this paper, we present these enhancements. Our study is based on experiments using six applications to perform Parallel Matrix-matrix Multiplication (PMM) on an HCoM employing the two distribution strategies.

Multi-core processorParallel processing (DSP implementation)Computer scienceComputationLinear algebraParallel algorithmConcurrent computingMultiplicationParallel computingMatrix multiplication2010 18th Euromicro Conference on Parallel, Distributed and Network-based Processing
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Scalable Dense Factorizations for Heterogeneous Computational Clusters

2008

This paper discusses the design and the implementation of the LU factorization routines included in the Heterogeneous ScaLAPACK library, which is built on top of ScaLAPACK. These routines are used in the factorization and solution of a dense system of linear equations. They are implemented using optimized PBLAS, BLACS and BLAS libraries for heterogeneous computational clusters. We present the details of the implementation as well as performance results on a heterogeneous computing cluster.

ScaLAPACKComputer scienceMathematicsofComputing_NUMERICALANALYSISSymmetric multiprocessor systemParallel computingLU decompositionComputational sciencelaw.inventionMatrix decompositionFactorizationlawScalabilityLinear algebraConcurrent computing2008 International Symposium on Parallel and Distributed Computing
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