GViM: GPU-accelerated virtual machines
Proceedings of the 3rd ACM Workshop on System-level Virtualization for High Performance Computing
Scientific workflows and clouds
Crossroads - Plugging Into the Cloud
International Journal of Advanced Media and Communication
Data Sharing Options for Scientific Workflows on Amazon EC2
Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis
Experiences using cloud computing for a scientific workflow application
Proceedings of the 2nd international workshop on Scientific cloud computing
State of the Practice Reports
One optimized I/O configuration per HPC application: leveraging the configurability of cloud
Proceedings of the Second Asia-Pacific Workshop on Systems
An Evaluation of the Cost and Performance of Scientific Workflows on Amazon EC2
Journal of Grid Computing
Analysis of I/O Performance on an Amazon EC2 Cluster Compute and High I/O Platform
Journal of Grid Computing
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Virtualization using Xen-based virtual machine environment has yet to permeate the field of high performance computing (HPC). One major requirement for HPC is the availability of scalable and high performance I/O. Conventional wisdom suggests that virtualization of system services must lead to degraded performance. In this presentation, we take on a parallel I/O perspective to study the viability of Xen-based HPC for data-intensive programs. We have analyzed the overheads and migration costs for parallel I/O programs in a Xen-based virtual machine cluster. Our analysis covers PVFS-based parallel I/O over two different networking protocols: TCP-based Gigabit Ethernet and VMM-bypass InfiniBand. Our experimental results suggest that network processing in Xen-based virtualization can significantly impact the performance of Parallel I/O. By carefully tuning the networking layers, we have demonstrated the following for Xen-based HPC I/O: (1) TCP offloading can help achieve low overhead parallel I/O; (2) parallel reads and writes require different network tuning to achieve good I/O bandwidth; and (3) Xen-based HPC environment can support high performance parallel I/O with both negligible overhead and little migration cost.