2 resultados para FAILURE DETECTION
em CentAUR: Central Archive University of Reading - UK
Resumo:
Future extreme-scale high-performance computing systems will be required to work under frequent component failures. The MPI Forum's User Level Failure Mitigation proposal has introduced an operation, MPI_Comm_shrink, to synchronize the alive processes on the list of failed processes, so that applications can continue to execute even in the presence of failures by adopting algorithm-based fault tolerance techniques. This MPI_Comm_shrink operation requires a fault tolerant failure detection and consensus algorithm. This paper presents and compares two novel failure detection and consensus algorithms. The proposed algorithms are based on Gossip protocols and are inherently fault-tolerant and scalable. The proposed algorithms were implemented and tested using the Extreme-scale Simulator. The results show that in both algorithms the number of Gossip cycles to achieve global consensus scales logarithmically with system size. The second algorithm also shows better scalability in terms of memory and network bandwidth usage and a perfect synchronization in achieving global consensus.
Resumo:
In high speed manufacturing systems, continuous operation is desirable, with minimal disruption for repairs and service. An intelligent diagnostic monitoring system, designed to detect developing faults before catastrophic failure, or prior to undesirable reduction in output quality, is a good means of achieving this. Artificial neural networks have already been found to be of value in fault diagnosis of machinery. The aim here is to provide a system capable of detecting a number of faults, in order that maintenance can be scheduled in advance of sudden failure, and to reduce the necessity to replace parts at intervals based on mean time between failures. Instead, parts will need to be replaced only when necessary. Analysis of control information in the form of position error data from two servomotors is described.