Fat-trees: universal networks for hardware-efficient supercomputing
IEEE Transactions on Computers
Deadlock-Free Message Routing in Multiprocessor Interconnection Networks
IEEE Transactions on Computers
Managing NFS and NIS
Parallel file systems for the IBM SP computers
IBM Systems Journal
Experimental evaluation of the Hewlett-Parkard exemplar file system
ACM SIGMETRICS Performance Evaluation Review
Predictive performance and scalability modeling of a large-scale application
Proceedings of the 2001 ACM/IEEE conference on Supercomputing
k -ary n -trees: High Performance Networks for Massively Parallel Architectures
IPPS '97 Proceedings of the 11th International Symposium on Parallel Processing
Performance Evaluation of the Quadrics Interconnection Network
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
The Quadrics Network (QsNet): High-Performance Clustering Technology
HOTI '01 Proceedings of the The Ninth Symposium on High Performance Interconnects
Hardware- and Software-Based Collective Communication on the Quadrics Network
NCA '01 Proceedings of the IEEE International Symposium on Network Computing and Applications (NCA'01)
PVFS: a parallel file system for linux clusters
ALS'00 Proceedings of the 4th annual Linux Showcase & Conference - Volume 4
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A common trend in the design of large-scale clusters is to use a high-performance data network to integrate the processing nodes in a single parallel computer. In these systems the performance of the interconnect can be a limiting factor for the input/output (I/O), which is traditionally bottlenecked by the disk bandwidth. In this paper we present an experimental analysis on a 64-node AlphaServer cluster based on the Quadrics network (QsNET) of the behavior of the interconnect under I/O traffic, and the influence of the placement of the I/O servers on the overall performance. The effects of using dedicated I/O nodes or overlapping I/O and computation on the I/O nodes are also analyzed. In addition, we evaluate how background I/O traffic interferes with other parallel applications running concurrently. Our experimental results show that a correct placement of the I/O servers can provide upto 20% increase in the available I/O bandwidth. Moreover, some important guidelines for applications and I/O servers mapping on large-scale clusters are given.