Scaling of Workload Traces
Author(s) -
Carsten Ernemann,
Baiyi Song,
Ramin Yahyapour
Publication year - 2003
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
DOI - 10.1007/10968987_9
Subject(s) - workload , computer science , scaling , schedule , scheduling (production processes) , parallel computing , mathematical optimization , operating system , mathematics , geometry
The design and evaluation of job scheduling strategies of- ten require simulations with workload data or models. Usually workload traces are the most realistic data source as they include all explicit and implicit job patterns which are not always considered in a model. In this paper, a method is presented to enlarge and/or duplicate jobs in a given workload. This allows the scaling of workloads for later use on parallel machine congurations with a dieren t number of processors. As quality criteria the scheduling results by common algorithms have been examined. The results show high sensitivity of schedule attributes to modications of the workload. To this end, dieren t strategies of scal- ing number of job copies and/or job size have been examined. The best results had been achieved by adjusting the scaling factors to be higher than the precise relation between the new scaled machine size and the original source conguration.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom