Towards Fully Adaptive Pipeline Parallelism for Heterogeneous Distributed Environments

González–Vélez, Horacio; Cole, Murray

doi:10.1007/11946441_82

Cited by 5 publications

(3 citation statements)

References 16 publications

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“…This adaptiveness rests on the resource availability-performance premise, that is to say, the assumption that certain parallel programs can perform more efficiently based on a wise selection from the available system resources. We support our claims concerning performance enhancement by presenting positive empirical results based on two task-parallel skeletons: the task farm-first discussed in [8] and later extended in [9]-and the pipeline-introduced in [10] and generalized in [11]-. For convenience, we have implemented simple skeletal application programmer interfaces (APIs) in C with MPI for both skeletons, but stress that they are merely prototype vehicles to support the investigation of application scheduling schemes, which forms our main contribution.…”

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confidence: 75%

Adaptive structured parallelism for distributed heterogeneous architectures: a methodological approach with pipelines and farms

González–Vélez

Cole

2010

Concurrency and Computation

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SUMMARYAlgorithmic skeletons abstract commonly used patterns of parallel computation, communication, and interaction. Based on the algorithmic skeleton concept, structured parallelism provides a high-level parallel programming technique that allows the conceptual description of parallel programs while fostering platform independence and algorithm abstraction. This work presents a methodology to improve skeletal parallel programming in heterogeneous distributed systems by introducing adaptivity through resource awareness. As we hypothesise that a skeletal program should be able to adapt to the dynamic resource conditions over time using its structural forecasting information, we have developed adaptive structured parallelism (ASPARA). ASPARA is a generic methodology to incorporate structural information at compilation into a parallel program, which will help it to adapt at execution. ASPARA comprises four phases: programming, compilation, calibration, and execution. We illustrate the feasibility of this approach and its associated performance improvements using independent case studies based on two algorithmic skeletons-the task farm and the pipeline-evaluated in a non-dedicated heterogeneous multi-cluster system.

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confidence: 75%

Adaptive structured parallelism for distributed heterogeneous architectures: a methodological approach with pipelines and farms

González–Vélez

Cole

2010

Concurrency and Computation

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“…More recent research from the Edinburgh group has addressed the problem of adaptation on structured parallel programming 85, 86, in particular for the pipe skeleton 87, 88 and the farm 89.Known as adaptive structured parallelism, this methodological approach puts particular emphasis on the automatic scheduling of algorithmic skeletons 90.It instruments a skeletal program with a series of rules, which depend on particular performance thresholds based on the nature of the skeleton, the computation/communication ratio of the program, and the availability of resources in the system.Employing the pipe and farm skeletons as a basis for experimentation, this methodology has been successfully applied to allocate divisible workloads to real multinode configurations 91 and to solve complex parameter sweeps in the biomedical sciences92.…”

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confidence: 99%

A survey of algorithmic skeleton frameworks: high‐level structured parallel programming enablers

2010

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Structured parallel programs ought to be conceived as two separate and complementary entities: computation, which expresses the calculations in a procedural manner, and coordination, which abstracts the interaction and communication. By abstracting commonly used patterns of parallel computation, communication, and interaction, algorithmic skeletons enable programmers to code algorithms without specifying platform‐dependent primitives. This article presents a literature review on algorithmic skeleton frameworks (ASKF), parallel software development environments furnishing a collection of parameterizable algorithmic skeletons, where the control flow, nesting, resource monitoring, and portability of the resulting parallel program is dictated by the ASKF as opposed to the programmer. Consequently, the ASKF can be positioned as high‐level structured parallel programming enablers, as their systematic utilization permits the abstract description of programs and fosters portability by focusing on the description of the algorithmic structure rather than on its detailed implementation. Copyright © 2010 John Wiley & Sons, Ltd.

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“…GRASP currently comprises two algorithmic skeletons, task farm [6] and pipeline [7], programmed as APIs in ANSI C.…”

Section: Introductionmentioning

confidence: 99%

Adaptive structured parallelism for computational grids

González–Vélez

Cole

2007

Proceedings of the 12th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming

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Towards Fully Adaptive Pipeline Parallelism for Heterogeneous Distributed Environments

Cited by 5 publications

References 16 publications

Adaptive structured parallelism for distributed heterogeneous architectures: a methodological approach with pipelines and farms

Adaptive structured parallelism for distributed heterogeneous architectures: a methodological approach with pipelines and farms

A survey of algorithmic skeleton frameworks: high‐level structured parallel programming enablers

Adaptive structured parallelism for computational grids

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