Towards Proactive Network Load Management for Distributed Parallel Programming.
Sergio Nesmachnow, Antonio López, Carlos López-Vázquez · 1999
In order to increase the overall performance of distributed parallel programs running in a network of non-dedicated workstations, we have researched methods for improving load balancing in loosely coupled heterogeneous distributed systems. Current software designed to handle distributed applications does not focus on the problem of forecasting the computers future load. The software only dispatches the tasks assigning them either to an idle CPU (in dedicated networks) or to the lowest loaded one (in non-dedicated networks). Our approach tries to improve the standard dispatching strategies provided by both parallel languages and libraries, by implementing new dispatching criteria. It will choose the most suitable computer after forecasting the load of the individual machines based on current and historical data. Existing applications could take advantage of this new service with no extra changes but a recompilation. A fair comparison between different dispatching algorithms could only be done if they run over the same external network load conditions. In order to do so, a tool to arbitrarily replicate historical observations of load parameters while running the different strategies was developed. In this environment, the new algorithms are being tested and compared to verify the improvement over the dispatching strategy already available. The overall performance of the system was tested with in-house developed numerical models. The project reported here is connected with other efforts at CeCal devoted to make it easier for scientists and developers to gain advantage of parallel computing techniques using low cost components.