| Wld {hpcwld} | R Documentation |
Workload of a High Performance Cluster model
Description
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).
Usage
Wld(T, S, N, m, method = "concurrent")
Arguments
T |
Interarrival times of tasks |
S |
Service times of customers (a vector of length n, or a matrix nrows=n, ncols='m'). |
N |
Number of servers each customer needs |
m |
Number of servers for a supercomputer |
method |
Independent or concurrent |
Value
A dataset is returned, containing 'delay' as a vector of delays exhibited by each task, 'total_cores' as the total busy CPUs in time of arrival of each task, and 'workload' as total work left at each CPU.
Examples
Wld(T=rexp(1000,1), S=rexp(1000,1), round(runif(1000,1,10)), 10)