Estimating computation times of data-intensive applications
- 1 June 2004
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Distributed Systems Online
- Vol. 5 (4), 1-12
- https://doi.org/10.1109/mdso.2004.1301253
Abstract
We present a holistic approach to estimation that uses rough sets theory to determine a similarity template and then compute a runtime estimate using identified similar applications. We tested the technique in two real-life data-intensive applications: data mining and high-performance computing.Keywords
This publication has 6 references indexed in Scilit:
- Predicting queue times on space-sharing parallel computersPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Data miningACM SIGMOD Record, 2002
- Using Run-Time Predictions to Estimate Queue Wait Times and Improve Scheduler PerformanceLecture Notes in Computer Science, 1999
- Predicting application run times using historical informationLecture Notes in Computer Science, 1998
- A historical application profiler for use by parallel schedulersLecture Notes in Computer Science, 1997
- Rough setsInternational Journal of Parallel Programming, 1982