This function computes the Kiefer-Wolfowitz modified vector for a HPC model. This vector contains the work left on each of 'm' servers of a cluster for the time of the arival of a task. Two methods are available, one for the case of concurrent server release (all the servers end a single task simultaneously), other for independent release (service times on each server are independent).
Note that this is only a wrapper for the ToSWF command with a dataframe argument. It needs a correctly built dataframe and converts it to a Standart Workload Format used to share the logfiles of High Performance Clusters
This function calculates the constant C that is used in the stability relation of a model, which is basically the following: lambda/mu<C, where lambda is the intensity of task arrivals, and mu is the intensity of service, in this case it is 1/(mean service time). The constant depends only on the number of cores in the model and the distribution of core requirement of tasks. Note that there are three methods of calculation: two of them calculate the exact value ("less-memory" and "more-memory"), and the third one ("monte-carlo") returns the approximate value. The exact value may be calculated up to a number of cores of the order of 100. The constant is valid only for the model with simultaneous task service by cores.
This function calculates the constant C that is used in the stability relation of a model, which is basically the following: lambda/mu<C, where lambda is the intensity of task arrivals, and mu is the intensity of service, in this case it is 1/(mean service time). The constant depends only on the number of cores in the model and the distribution of core requirement of tasks. Note that this method of calculation allows to stop on some depth of dynamics, thus allowing to calculate an approximate value in faster time. The constant is valid only for the model with simultaneous task service by cores.
This is a convertor from a Standart Workload Format (used to share the logfiles of High Performance Clusters) to an internally used in a package dataset format
This package contains several models describing the behavior of workload and queue on a High Performance Cluster and computing GRID under FIFO service discipline basing on modified Kiefer-Wolfowitz recursion. Also sample data for inter-arrival times, service times, number of cores per task and waiting times of HPC of Karelian Research Centre are included, measurements took place from 06/03/2009 to 02/30/2011. The stability condition of the model can be verified either exactly, or approximately.
This is a suggested by Dror Feitelson measure of correlation for dependent variables, that may be successfully used to examine the datasets from a High Performance Cluster logs
providing 
.