Empirical Parallel Performance Prediction from Semantics-Based Profiling
نویسندگان
چکیده
The PMLS parallelizing compiler for Standard ML is based upon the automatic instantiation of algorithmic skeletons at sites of higher order function (HOF) use. Rather than mechanically replacing HOFs with skeletons, which in general leads to poor parallel performance, PMLS seeks to predict run-time parallel behaviour to optimise skeleton use. Static extraction of analytic cost models from programs is undecidable, and practical heuristic approaches are intractable. In contrast, PMLS utilises a hybrid approach by combining static analytic cost models for skeletons with dynamic information gathered from the sequential instrumentation of HOF argument functions. Such instrumentation is provided by an implementation independent SML interpreter, based on the language’s Structural Operational Semantics (SOS), in the form of SOS rule counts. PMLS then tries to relate the rule counts to program execution times through numerical techniques. This paper considers the design and implementation of the PMLS approach to parallel performance prediction. The formulation of a general rule count cost model as a set of over-determined linear equations is discussed, and their solution by single value decomposition, and by a genetic algorithm, are presented.
منابع مشابه
Phase-Based Parallel Performance Profiling
Parallel scientific applications are designed based on structural, logical, and numerical models of computation and correctness. When studying the performance of these applications, especially on large-scale parallel systems, there is a strong preference among developers to view performance information with respect to their “mental model” of the application, formed from the model semantics used...
متن کاملA Document Weighted Approach for Gender and Age Prediction Based on Term Weight Measure
Author profiling is a text classification technique, which is used to predict the profiles of unknown text by analyzing their writing styles. Author profiles are the characteristics of the authors like gender, age, nativity language, country and educational background. The existing approaches for Author Profiling suffered from problems like high dimensionality of features and fail to capture th...
متن کاملANN Based Modeling for Prediction of Evaporation in Reservoirs (RESEARCH NOTE)
This paper is an attempt to assess the potential and usefulness of ANN based modeling for evaporation prediction from a reservoir, where in classical and empirical equations failed to predict the evaporation accurately. The meteorological data set of daily pan evaporation, temperature, solar radiation, relative humidity, wind speed is used in this study. The performance of feed forward back pro...
متن کاملPerformance prediction of component-based applications
One of the major problems in building large-scale enterprise systems is anticipating the performance of the eventual solution before it has been built. The fundamental software engineering problem becomes more difficult when the systems are built on component technology. This paper investigates the feasibility of providing a practical solution to this problem. An empirical approach is proposed ...
متن کاملAutomated Experimental Parallel Performance Analysis
Performance is the key issue in parallel processing. We want to investigate how far we can automate experimental performance analysis in order to achieve all necessary performance results for performance prediction, load balancing and algorithm optimisation. This paper describes the approach of generalising the performance analysis and obtaining the specific results by experiments.
متن کامل