Add to ORKGWe developed techniques to predict application execution times for instance-based learning with an average error of 33% of average run time. We developed techniques to predict queue wait times that included a simulation of scheduling algorithms and execution time predictions. We implemented these techniques for the NAS Origin cluster
In a Grid computing environment, resources are shared among a large number of applications. Brokers ...
Abstract—Scientific workflows, which capture large compu-tational problems, may be executed on large...
Large-scale distributed computing systems such as grids are serving a growing number of scientists. ...
In large-scale Grids with many possible resources (clus-ters of computing elements) to run applicati...
We present a technique for deriving predictions for the run times of parallel applications from the ...
To make effective job placement policies for a volatile large scale heterogeneous system or in grid ...
We address the problem of performance prediction for parallel programs executed on clusters of heter...
Abstract. When a moldable job is submitted to a space-sharing parallel computer, it must choose whet...
Production parallel systems are space-shared, and resource allocation on such systems is usually per...
Abstract. Response time predictions for workload on new server architectures can enhance Service Lev...
This paper evaluates several main learning and heuris-tic techniques for application run time predic...
International audienceWe propose simple queueing models for predicting response times of application...
These resources accompany the paper entitled "A Machine Learning Approach to Waiting Time Prediction...
Application design has been revolutionized with the adoption of microservices architecture. The abil...
Prediction of queue waiting times of jobs submitted to production parallel batch systems is importan...
In a Grid computing environment, resources are shared among a large number of applications. Brokers ...
Abstract—Scientific workflows, which capture large compu-tational problems, may be executed on large...
Large-scale distributed computing systems such as grids are serving a growing number of scientists. ...
In large-scale Grids with many possible resources (clus-ters of computing elements) to run applicati...
We present a technique for deriving predictions for the run times of parallel applications from the ...
To make effective job placement policies for a volatile large scale heterogeneous system or in grid ...
We address the problem of performance prediction for parallel programs executed on clusters of heter...
Abstract. When a moldable job is submitted to a space-sharing parallel computer, it must choose whet...
Production parallel systems are space-shared, and resource allocation on such systems is usually per...
Abstract. Response time predictions for workload on new server architectures can enhance Service Lev...
This paper evaluates several main learning and heuris-tic techniques for application run time predic...
International audienceWe propose simple queueing models for predicting response times of application...
These resources accompany the paper entitled "A Machine Learning Approach to Waiting Time Prediction...
Application design has been revolutionized with the adoption of microservices architecture. The abil...
Prediction of queue waiting times of jobs submitted to production parallel batch systems is importan...
In a Grid computing environment, resources are shared among a large number of applications. Brokers ...
Abstract—Scientific workflows, which capture large compu-tational problems, may be executed on large...
Large-scale distributed computing systems such as grids are serving a growing number of scientists. ...