Performance modeling of communication and computation in hybrid MPI and OpenMP applications

Adhianto, Laksono; Chapman, Barbara

doi:10.1109/icpads.2006.81

Cited by 23 publications

(25 citation statements)

References 31 publications

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“…Assessment of parallel performance and overhead has been extensively studied in the past [4][5][6][7][8][9][10][11][12]. Starting with the logP model [4,5], four parameters, i.e.…”

Section: Introductionmentioning

confidence: 99%

“…A more abstract framework with tuneable complexity but still practical timing requirements has been provided with PERC [9]. More recent trends in hybrid MPI/OpenMP programming were taken care of by a combination of application signature with system profiles [10]. Along similar lines applicationcentric performance modelling [11,13] was described based on characteristics of the application and the target computing platform with the objective of successful largescale extrapolation.…”

Section: Introductionmentioning

confidence: 99%

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Modelling parallel overhead from simple run-time records

Höfinger

Haunschmid

2017

J Supercomput

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A number of scientific applications run on current HPC systems would benefit from an approximate assessment of parallel overhead. In many instances a quick and simple method to obtain a general overview on the subject is regarded useful auxiliary information by the routine HPC user. Here we present such a method using just execution times for increasing numbers of parallel processing cores. We start out with several common scientific applications and measure the fraction of time spent in MPI communication. Forming the ratio of MPI time to overall execution time we obtain a smooth curve that can be parameterized by only two constants. We then use this two-parameter expression and extend Amdahl's theorem with a new term representing parallel overhead in general. Fitting the original data set with this extended Amdahl expression yields an estimate for the parallel overhead closely matching the MPI time determined previously.

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“…Assessment of parallel performance and overhead has been extensively studied in the past [4][5][6][7][8][9][10][11][12]. Starting with the logP model [4,5], four parameters, i.e.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modelling parallel overhead from simple run-time records

Höfinger

Haunschmid

2017

J Supercomput

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“…Examination of the model in Equation (20) indicates that the sensitivity of the floating-point cost is O(M I M J ), while that of the communication parameters is O(P I M J ). For convenience that model is restated here, in a slightly different form…”

Section: Empirical Sensitivitymentioning

confidence: 99%

“…Therefore, data size on each of the compute nodes is the same as that on the single processor. Further, assume that there is one MPI process per node † † † † † , so that local data are square M × M. With p processors allocated as a P × Q grid, the model in Equation (20) becomes…”

Section: Mathematical Sensitivitymentioning

confidence: 99%

Methodology for modelling SPMD hybrid parallel computation

Liebrock¹,

Goudy²

2007

Concurrency and Computation

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SUMMARYThis research defines and analyzes a methodology for deriving a performance model for SPMD hybrid parallel applications. Hybrid parallelism combines shared memory and message passing computing models.This work extends the current practice of application performance modelling by development of a methodology for hybrid applications with these procedures.• Creation of a model based on complexity analysis of an application code and its data structures.• Enhancement of a static complexity model by dynamic factors to capture execution time phenomena, such as memory hierarchy effects.• Quantitative analysis of model characteristics and the effects of perturbations in measured parameters.These research results are presented in the context of a hybrid parallel implementation of a sparse linear algebra kernel. A model for this kernel is derived and analyzed using the methodology. Application of the model on two large parallel computing platforms provides case studies for the methodology. Operating system issues, machine balance factor, and memory hierarchy effects on model accuracy are examined.

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“…Our model also adds two parameters for hybrid modeling instead of four. [21] developed a performance model for hybrid applications based on the parameters in [20]. Their model relies on static analysis of the application being modeled, tying it to codes rather than algorithms.…”

Section: Related Workmentioning

confidence: 99%

Modeling the Performance of an Algebraic Multigrid Cycle Using Hybrid MPI/OpenMP

Gahvari

Gropp

Jordan

et al. 2012

2012 41st International Conference on Parallel Processing

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Abstract-The rise of multicore cluster architectures has led to intense interest in using a combination of MPI and OpenMP to more effectively program these machines. We present a performance model for hybrid implementation of the solve cycle of algebraic multigrid (AMG), a popular iterative solver for large sparse linear systems and a key component of many scientific simulations. We validate the model on two leading parallel platforms, and discuss implications for applications programmed in a hybrid model on future machines.

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Performance modeling of communication and computation in hybrid MPI and OpenMP applications

Cited by 23 publications

References 31 publications

Modelling parallel overhead from simple run-time records

Modelling parallel overhead from simple run-time records

Methodology for modelling SPMD hybrid parallel computation

Modeling the Performance of an Algebraic Multigrid Cycle Using Hybrid MPI/OpenMP

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