Inhomogeneous sandpile model: Crossover from multifractal scaling to finite size scaling

We study an inhomogeneous sandpile model in which two different toppling rules are defined. For any site only one rule is applied corresponding to either the Bak, Tang and Wiesenfeld model {[}P.Bak, C. Tang, and K. Wiesenfeld, Phys. Rev. Lett. \textbf{59}, 381 (1987){]} or the Manna two-state sandpile model {[}S. S. Manna, J. Phys. A \textbf{24}, L363 (1991){]}. A parameter $c$ is introduced which describes a density of sites which are randomly deployed and where the stochastic Manna rules are applied. The results show that the avalanche area exponent $\tau_{a}$, avalanche size exponent $\tau_{s}$, and capacity fractal dimension $D_{s}$ depend on the density $c$. A crossover from multifractal scaling of the Bak, Tang, and Wiesenfeld model ($c=0$) to finite size scaling was found. The critical density $c$ is found to be in the interval $0<c<0.01$. These results demonstrate that local dynamical rules are important and can change the global properties of the model.Comment: 17 pages, 6 figure

Performance testing of distributed computational resources in the software development phase

A grid software harmonization is possible through adoption of standards i.e. common protocols and interfaces. In the development phase of standard implementation, the performance testing of grid subsystems can detect hidden software issues which are not detectable using other testing procedures. A simple software solution was proposed which consists of a communication layer, resource consumption agents hosted in computational resources (clients or servers), a database of the performance results and a web interface to visualize the results. Communication between agents, monitoring the resources and main control Python script (supervisor) is possible through the communication layer based on the secure XML-RPC protocol. The resource monitoring agent is a key element of performance testing which provides information about all monitored processes including their child processes. The agent is a simple Python script based on the Python psutil library. The second agent, provided after the resource monitored phase, records data from the resources in the central MySQL database. The results can be queried and visualized using a web interface. The database and data visualization scripts could be considered for a service thus the testers do not need install them to run own tests