scholarly journals Using Combined Static Analysis and Profiling for Logic Program Execution Time Estimation

2006 ◽  
pp. 431-432 ◽  
Author(s):  
Edison Mera ◽  
Pedro López-García ◽  
Germán Puebla ◽  
Manuel Carro ◽  
Manuel Hermenegildo
Keyword(s):  
Static Analysis ◽  
Execution Time ◽  
Logic Program ◽  
Time Estimation ◽  
Program Execution

Exploiting non-uniform program execution time to evade record/replay forensic analysis

2020 ◽  
Vol 88 ◽  
pp. 101516
Author(s):  
Yang Hu ◽  
Mingshen Sun ◽  
John C.S. Lui
Keyword(s):  
Execution Time ◽  
Forensic Analysis ◽  
Program Execution

Generalized Execution Time Estimation

2018 ◽  
Author(s):  
Andreas Rechberger ◽  
Eugen Brenner
Keyword(s):  
Execution Time ◽  
Time Estimation

scholarly journals THE EFFECT ON PROGRAM EXECUTION TIME OF THE USE OF FORTRAN MULTISUBSCRIPTED VARIABLES.

1967 ◽  
Author(s):  
J.G. Sullivan
Keyword(s):  
Execution Time ◽  
Program Execution

Use of Measurements in Worst-Case Execution Time Estimation for Real-Time Systems

2021 ◽  
Author(s):  
Jessica Junia Santillo Costa ◽  
Romulo Silva de Oliveira ◽  
Luis Fernando Arcaro
Keyword(s):  
Real Time ◽  
Execution Time ◽  
Time Estimation ◽  
Real Time Systems ◽  
Worst Case ◽  
Worst Case Execution Time ◽  
Time Systems

SYMBOLIC PERFORMANCE ESTIMATION OF SPECULATIVE PARALLEL PROGRAMS

2003 ◽  
Vol 13 (04) ◽  
pp. 513-524 ◽  
Author(s):  
H. GAUTAMA ◽  
A. J. C. VAN GEMUND
Keyword(s):  
Performance Prediction ◽  
Execution Time ◽  
Time Distribution ◽  
Prediction Accuracy ◽  
Analytical Approach ◽  
Parallel Programs ◽  
Performance Estimation ◽  
Program Execution ◽  
Empirical Distributions ◽  
Measurement Results

Speculative parallelism refers to searching in parallel for a solution, such as finding a pattern in a data base, where finding the first solution terminates the whole parallel process. Different performance prediction methods are required as compared to traditional parallelism. In this paper we introduce an analytical approach to predict the execution time distribution of data-dependent parallel programs that feature N-ary and binary speculative parallel compositions. The method is based on the use of statistical moments which allows program execution time distribution to be approximated at O(1) solution complexity. Measurement results for synthetic distributions indicate an accuracy that lies in the percent range while for empirical distributions on internet search engines the prediction accuracy is acceptable, provided sufficient workload unimodality.

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