From: Arnaud Giersch Date: Fri, 11 Jan 2013 16:33:58 +0000 (+0100) Subject: Describe the metrics. X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/loba-papers.git/commitdiff_plain/a17baac0d900ec0555cc2002c02c3af3fd38ade7?ds=inline Describe the metrics. --- diff --git a/supercomp11/supercomp11.tex b/supercomp11/supercomp11.tex index 056e185..f41425c 100644 --- a/supercomp11/supercomp11.tex +++ b/supercomp11/supercomp11.tex @@ -526,8 +526,10 @@ nodes: 16, 64, 256, and 1024 nodes. The distributed processes of the application were then logically organized along three possible topologies: a line, a torus or an hypercube. We ran tests where the total load was initially on an only node (at one end for the line topology), -and other tests where the load was initially randomly distributed across all -the participating nodes. +and other tests where the load was initially randomly distributed across all the +participating nodes. The total amount of load was fixed to a number of load +units equal to 1000 times the number of node. The average load is then of 1000 +load units. For each of the preceding configuration, we finally had to choose the computation and communication costs of a load unit. We chose them, such as to @@ -564,16 +566,44 @@ time. \paragraph{Metrics} -In order to evaluate and compare the different load balancing strategies, we -choose to measure the following metrics: +In order to evaluate and compare the different load balancing strategies we had +to define several metrics. Our goal, when choosing these metrics, was to have +something tending to a constant value, i.e. to have a measure which is not +changing anymore once the convergence state is reached. Moreover, we wanted to +have some normalized value, in order to be able to compare them across different +settings. +With these constraints in mind, we defined the following metrics: +% \begin{description} -\item[\textbf{average idle time:}] -\item[\textbf{average convergence date:}] -\item[\textbf{maximum convergence date:}] -\item[\textbf{data transfer amount:}] relative to the total data amount +\item[\textbf{average idle time:}] that's the total time spent, when the nodes + don't hold any share of load, and thus have nothing to compute. This total + time is divided by the number of participating nodes, such as to have a number + that can be compared between simulations of different sizes. + + This metric is expected to give an idea of the ability of the strategy to + diffuse the load quickly, lesser is better. + +\item[\textbf{average convergence date:}] that's the average of the dates when + all nodes reached the convergence state. The dates are measured as a number + of (simulated) seconds since the beginning of the simulation. + +\item[\textbf{maximum convergence date:}] that's the date when the last node + reached the convergence state. + + These two dates give an idea of the time needed by the strategy to reach the + equilibrium state, lesser is doubtlessly better. + +\item[\textbf{data transfer amount:}] that's the sum of the amount of data of + all transfers during the simulation. This sum is then normalized by dividing + it by the total amount of data present in the system. + + This metric is expected to give an idea of the efficiency of the strategy in + terms of data movements, i.e. its ability to reach the equilibrium with fewer + transfers. + \end{description} -\FIXME{dire à chaque fois ce que ça représente, et motiver le choix} + \subsection{Validation of our approaches} \label{Results}