An object‐oriented bulk synchronous parallel library for multicore programming

Yzelman, Albert-Jan N.; Bisseling, Rob H.

doi:10.1002/cpe.1843

Cited by 20 publications

(22 citation statements)

References 30 publications

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“…Besides libraries in native code, we can describe some interpreted initiatives in Java. JBSP [10], MulticoreBSP [11] and PUBWCL [12] appear as the most significant ones. JBSP is a NOW-based system and provides both DRMA and BSMP communication methods.…”

Section: Related Workmentioning

confidence: 97%

jMigBSP: Object Migration and Asynchronous One-Sided Communication for BSP Applications

Graebin

Righi

2011

2011 12th International Conference on Parallel and Distributed Computing, Applications and Technologies

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This paper describes the rationale for developing jMigBSP -a Java programming library that offers object rescheduling. It was designed to work on grid computing environments and offers an interface that follows the BSP (Bulk Synchronous Parallel) style. jMigBSP's main contribution focuses on the rescheduling facility in two different ways: (i) by using migration directives on the application code directly and (ii) through automatic load balancing at middleware level. Especially, this second idea is feasible thanks to the Java's inheritance feature, in which transforms a simple jMigBSP application in a migratable one only by changing a single line of code. In addition, the presented library makes the object interaction easier by providing one-sided message passing directives and hides network latency through asynchronous communications. Finally, a BSP-based FFT application was developed and its execution shows jMigBSP as a competitive library when comparing performance with a C-based library called BSPlib. Besides its user-friendly Java interface, the strengths of jMigBSP also considers the migration tests where it outperforms the time spent with BSPlib.

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Section: Related Workmentioning

confidence: 97%

jMigBSP: Object Migration and Asynchronous One-Sided Communication for BSP Applications

Graebin

Righi

2011

2011 12th International Conference on Parallel and Distributed Computing, Applications and Technologies

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“…Valiant's BSP model [95] unifies the measurement of platform parameters with program analysis, providing a coherent set of parameters to describe their interaction. This has been extended both in refinements of the theoretical side [38,93,96] and practical efforts to realize it, from realizing the programming primitives in library form [45,46,55,102], to describing transformations of programs into other programming models [19,90]. Bilardi et al [18] compare the LogP and BSP models, establishing that they can mutually simulate one another with small overheads in asymptotic terms, and noting that BSP provides a more convenient programming abstraction.…”

Section: Research Contextmentioning

confidence: 99%

Performance modeling of heterogeneous systems

Meyer

Elster

2010

2010 IEEE International Symposium on Parallel &Amp; Distributed Processing, Workshops and PHD Forum (IPDPSW)

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As the complexity of parallel computers grows, constraints posed by the construction of larger systems require both greater, and increasingly non-linear, parameter sets to model their behavior realistically. These heterogeneous characteristics create a trade-off between the complexity and accuracy of performance models, creating challenges in utilizing them for design decisions.In this thesis, we take a bottom-up approach to realistically model software and hardware interactions, by composing system models from simpler, linear models, which allow parts of the analysis to be automated. We associate empirically benchmarked platform performance metrics with the core elements in a variant of bulk-synchronous execution, aiming to quantify application performance, and associated potential for computation and communication overlap on SMP clusters.The original bulk-synchronous performance model is introduced, and we identify areas of computation and communication where its abstractions impede realistic models of contemporary hardware. These are addressed independently, using experimental evidence to develop a representation collecting computation kernel characteristics and pairwise communications in matrices, to combine into a system model. As bulk-synchronous execution strongly depends on periodic, global synchronization, we develop a cost model for it by combining latency measurements with a parametric representation of signalling patterns, and experimentally verify the resulting predictions for three common algorithms.We describe a design to implement the BSPLib programming interface, combining threads and message-passing parallelism to achieve overlap on commodity cluster platforms, implementing its one-sided communication primitives using out-of-band control messages. We augment and validate the cost model of one adapted synchronization algorithm with the corresponding bandwidth requirement, completing a framework for modeling BSPLib program performance.Finally, we test the utility of this framework as a proof-of-concept for guiding software performance adaptations, using two cases. First, we use the latency terms to automatically generate synchronization operations, using model predictions to generate customized patterns with respect to platform topology, showing that the resulting algorithms equal or outperform the system defaults. Second, the strong scaling characteristics of a 5-point stencil code is compared for three implementations. Experiments show the performance overhead of our implementation, but also its capability for predicting program cost, including parameter values to optimize for balanced overlapping of computation and communication.ii Preface

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“…The Pregel was based on BSP computational models . The BSP exhibits a phase‐based computational behavior . A BSP application is composed of a set of rounds or supersteps.…”

Section: Introductionmentioning

confidence: 99%

Scalable and optimal planning based on Pregel

Jiang

Rao

2018

Concurrency and Computation

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Summary Automated planning generates plans for specific tasks. Optimal planning aims at generating optimal plans under global constraints. As a result, the divide‐and‐conquer method is not applicable for optimal planning. Therefore, engineering applications of optimal planning face the scalability issue. Fortunately, cloud computing tools are on the shelf. For example, the Apache Spark is an engine for big data processing. It supports the Pregel for scalable computing. Therefore, we proposed an optimal Planning method based on the Pregel, called the PbP. Unlike classical planning, the PbP method uses the Pregel as the computation model, instead of the traditional state‐space searching. The core idea is to transform planning problems into graph processing problems. Specifically, actions are mapped into vertices, partial orders between actions are mapped into edges between vertices, and states are mapped into messages. Furthermore, the planning is viewed as message propagating in the graph, and plan traces are stored as attributes of vertices. Experimental results showed the feasibility of the proposed method PbP. Moreover, compared with state‐of‐the‐art optimal planners, our approach is more scalable and faster.

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An object‐oriented bulk synchronous parallel library for multicore programming

Cited by 20 publications

References 30 publications

jMigBSP: Object Migration and Asynchronous One-Sided Communication for BSP Applications

jMigBSP: Object Migration and Asynchronous One-Sided Communication for BSP Applications

Performance modeling of heterogeneous systems

Scalable and optimal planning based on Pregel

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