Nonlinear approach for estimating WCET during programming phase

This work aims to estimate the execution time of data processing tasks (specific executions of a program or an algorithm) before their execution. The paper focuses on the estimation of the average-case execution time (ACET). This metric can be used to predict the approximate cost of computations, e.g. when resource consumption in a High-Performance Computing system has to be known in advance. The presented approach proposes to create machine learning models using historical data. The models use program metadata (properties of input data) and parameters of the run-time environment as their explanatory variables. Moreover, the set of these variables can be easily expanded with additional parameters of the specific programs. The program code itself is treated as a black box. The response variable of the model is the execution time. The models have been validated within a Large-Scale Computing system that allows for a unified treatment of programs as computation modules. We present the process of training and validation for several different computation modules and discuss the suitability of the proposed models for ACET estimation in various computing environments.

show abstract

“…Another approach is presented by Meng et al [14]. They estimate the WCET by extracting the program features from object code.…”

Section: Contribution and Related Workmentioning

confidence: 99%

Estimation of execution time for computing tasks

Bielecki

Śmiałek

2022

Cluster Comput

View full text Add to dashboard Cite

show abstract

“…The advantage is that state-explosion problems can be solved. However, since all non-classified cache behaviors are treated as always miss, the fetching time of many instructions is magnified [37]. Consequently, wcet B is overestimated.…”

Section: Overestimation In Micro-architecture Modelingmentioning

confidence: 99%

Reducing WCET Overestimations by Correcting Errors in Loop Bound Constraints

Meng

2017

Energies

Self Cite

View full text Add to dashboard Cite

Abstract:In order to reduce overestimations of worst-case execution time (WCET), in this article, we firstly report a kind of specific WCET overestimation caused by non-orthogonal nested loops. Then, we propose a novel correction approach which has three basic steps. The first step is to locate the worst-case execution path (WCEP) in the control flow graph and then map it onto source code. The second step is to identify non-orthogonal nested loops from the WCEP by means of an abstract syntax tree. The last step is to recursively calculate the WCET errors caused by the loose loop bound constraints, and then subtract the total errors from the overestimations. The novelty lies in the fact that the WCET correction is only conducted on the non-branching part of WCEP, thus avoiding potential safety risks caused by possible WCEP switches. Experimental results show that our approach reduces the specific WCET overestimation by an average of more than 82%, and 100% of corrected WCET is no less than the actual WCET. Thus, our approach is not only effective but also safe. It will help developers to design energy-efficient and safe real-time systems.

show abstract

WCET optimization strategy based on source code refactoring

Meng

2017

Cluster Comput

View full text Add to dashboard Cite

Nonlinear approach for estimating WCET during programming phase

Cited by 4 publications

References 44 publications

Estimation of execution time for computing tasks

Estimation of execution time for computing tasks

Reducing WCET Overestimations by Correcting Errors in Loop Bound Constraints

WCET optimization strategy based on source code refactoring

Contact Info

Product

Resources

About