Add to ORKGInternational audienceThis article describes some work in the domain ofapplication execution time prediction, which is alwaysnecessary for schedulers. We define a hybrid method of timeprediction that is both profile-based and historic-based. Thisprediction is achieved by combining a program structureanalysis with an instance-based learning method. Wedemonstrate that taking account of an application's profileimproves predictions compared with classical historic-basedprediction method
Timing analysis is the application of one or more well-established predictive methods to derive the ...
Real-time systems need to be time-predictable in order to prove the timeliness of all their time-cri...
Everyday information systems collect a different kind of process instances of a business flow. As ti...
We present a technique for deriving predictions for the run times of parallel applications from the ...
The authors present a technique for deriving predictions for the run times of parallel applications ...
The effectiveness of distributed execution of computationally intensive applications (jobs) largely ...
To make effective job placement policies for a volatile large scale heterogeneous system or in grid ...
This paper evaluates several main learning and heuris-tic techniques for application run time predic...
AbstractIn heterogeneous and distributed environments it is necessary to create schedules for utilis...
grantor: University of TorontoScheduling Algorithms that use application and system knowle...
Process mining allows for the automated discovery of process models from event logs. These models pr...
A method to estimate the execution time of software based on static metrics is proposed in this the...
The increase in the use of parallel distributed architec-tures in order to solve large-scale scienti...
In large-scale Grids with many possible resources (clus-ters of computing elements) to run applicati...
Scheduling techniques based upon worst case execution times, as are commonly used in real-time appli...
Timing analysis is the application of one or more well-established predictive methods to derive the ...
Real-time systems need to be time-predictable in order to prove the timeliness of all their time-cri...
Everyday information systems collect a different kind of process instances of a business flow. As ti...
We present a technique for deriving predictions for the run times of parallel applications from the ...
The authors present a technique for deriving predictions for the run times of parallel applications ...
The effectiveness of distributed execution of computationally intensive applications (jobs) largely ...
To make effective job placement policies for a volatile large scale heterogeneous system or in grid ...
This paper evaluates several main learning and heuris-tic techniques for application run time predic...
AbstractIn heterogeneous and distributed environments it is necessary to create schedules for utilis...
grantor: University of TorontoScheduling Algorithms that use application and system knowle...
Process mining allows for the automated discovery of process models from event logs. These models pr...
A method to estimate the execution time of software based on static metrics is proposed in this the...
The increase in the use of parallel distributed architec-tures in order to solve large-scale scienti...
In large-scale Grids with many possible resources (clus-ters of computing elements) to run applicati...
Scheduling techniques based upon worst case execution times, as are commonly used in real-time appli...
Timing analysis is the application of one or more well-established predictive methods to derive the ...
Real-time systems need to be time-predictable in order to prove the timeliness of all their time-cri...
Everyday information systems collect a different kind of process instances of a business flow. As ti...