Security Implications of Typical Grid Computing Usage Scenarios
Cluster Computing
HPDC '03 Proceedings of the 12th IEEE International Symposium on High Performance Distributed Computing
A Case For Grid Computing On Virtual Machines
ICDCS '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
Executing and visualizing high energy physics simulations with grid technologies
ISPDC'03 Proceedings of the Second international conference on Parallel and distributed computing
Design of GridGIS architecture
ISPA'06 Proceedings of the 2006 international conference on Frontiers of High Performance Computing and Networking
| Hi-index | 0.00 |
The simulations used in the field of high energy physics are compute intensive and exhibit a high level of data parallelism. These features make such simulations ideal candidates for Grid computing. We are taking as an example the GEANT4 detector simulation used for physics studies within the ATLAS experiment at CERN. One key issue in Grid computing is that of network and system security, which can potentially inhibit the widespread use of such simulations. Virtualization provides a feasible solution because it allows the creation of virtual compute nodes in both local and remote compute clusters, thus providing an insulating layer which can play an important role in satisfying the security concerns of all parties involved. However, it has performance implications. This study provides quantitative estimates of the virtualization and hyper-threading overhead for GEANT on commodity clusters. Results show that virtualization has less than 15% run time overhead, and that the best run time (with the non-SMP license of ESX VMware) is achieved by using one virtual machine per CPU. We also observe that hyper-threading does not provide an advantage in this application. Finally, the effect of virtualization on run time, throughput, mean response time and utilization is estimated using simulations.