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Parellel performance modelling using a genetic programming based error correction procedure

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  1. Abstract
  2. Introduction
  3. Model error correction procedure
    1. General approach and case studies
    2. MECP applied to EVH1 communication model
    3. EVH1 model results
  4. Extension of MECP TP second application gyro
    1. Computation timing model
    2. Communication timing model
    3. Gyro model results
  5. Cross platform prediction
  6. Conclusions
  7. Refrences

Performance models of high performance computing (HPC) applications are important for several reasons. First, they provide insight to designers of HPC systems on the role of subsystems such as the processor or the network in determining application performance. Second, they allow HPC centers more accurately to target procurements to resource requirements. Third, they can be used to identify application performance bottlenecks and to provide insights about scalability issues. The suitability of a performance model, however, for a particular performance investigation is a function of both the accuracy and the cost of the model. A semi-empirical model previously published by the authors for an astrophysics application was shown to be inaccurate when predicting communication cost for large numbers of processors. It is hypothesized that this deficiency is due to the inability of the model adequately to capture communication contention (threshold effects) as well as other un-modeled components such as noise and I/O contention. In this paper we present a new approach to capture these unknown features to improve the predictive capabilities of the model. This approach uses a systematic model error-correction procedure that uses evolutionary algorithms to find an error correction term to augment the eXisting model. Four variations of this procedure were investigated and all were shown to produce better results than the original model.

[...] GA/GP parameter settings for MECP Parameters Settings The error correction term is a function of input parameters nx, np, and T. Since the parameters are not fixed in equations and the unknown machine parameters are found by GA for these cases. The ect is not shown here, but includes operators and and input parameters (application and machine parameters). The objective function to be minimized in the GA/GP procedure is a measure of the error between the calculated and measured communication times MECP APPLIED TO EVH1 COMMUNICATION MODEL EVH1 (Enhanced version of Virginia Hydrodynamics) is a finite-difference astrophysics code containing over 6500 lines of Fortran and MPI (Message Passing Interface) In earlier work EVH1 runtime was modeled for 2Dimensional and 3-Dimensional problems on two different architectures. [...]

[...] This approach starts by developing a semi-empirical model and then improving this further by using a genetic programming-based model error correction procedure (MECP). A semi-empirical parallel performance model typically consists of two components: computation time model and communication time model. Earlier work involving standard semi-empirical modeling for an astrophysics code EVH1 (Enhanced Virginia Hydrodynamics code) showed that while the computation model component prediction was satisfactory, the communication model prediction, particularly for large processor counts, was poor. This deficiency is probably due to the inability of a typical semi-empirical model to capture difficult to model components such as message contention and noise. [...]

[...] MODEL ERROR CORRECTION PROCEDURE Parallel performance models typically have several components (e.g., communication contention, non- 2 variables, such as x. The other set, known as the functional set, which contains operators. Symbolic search is performed using these two variable sets. GP explores a large number of possible functional relationships to identify the function that best fits the data. A tree data structure is used to represent each potential solution for ect, which is composed of a subset of the terminal set variables and functional set elements. [...]

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