Infrastructure as a Service (IaaS) cloud computing has revolutionized the way we think of acquiring resources by introducing a simple change: allowing users to lease computational resources from the cloud provider's datacenter for a short time by deploying virtual machines (VMs) on these resources. This new model raises new challenges in the design and development of IaaS middleware. One of those challenges is the need to deploy a large number (hundreds or even thousands) of VM instances simultaneously. Once the VM instances are deployed, another challenge is to simultaneously take a snapshot of many images and transfer them to persistent storage to support management tasks, such as suspend-resume and migration. With datacenters growing rapidly and configurations becoming heterogeneous, it is important to enable efficient concurrent deployment and snapshotting that are at the same time hypervisor independent and ensure a maximum compatibility with different configurations. This paper addresses these challenges by proposing a virtual file system specifically optimized for virtual machine image storage. It is based on a lazy transfer scheme coupled with object versioning that handles snapshotting transparently in a hypervisor-independent fashion, ensuring high portability for different configurations. Large-scale experiments on hundreds of nodes demonstrate excellent performance results: speedup for concurrent VM deployments ranges from a factor of 2 up to 25, with a reduction in bandwidth utilization of as much as 90%.

In preparation for the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report, the climate community will run the Coupled Model Intercomparison Project phase 5 (CMIP-5) experiments, which are designed to answer crucial questions about future regional climate change and the results of carbon feedback for different mitigation scenarios. The CMIP-5 experiments will generate petabytes of data that must be replicated seamlessly, reliably, and quickly to hundreds of research teams around the globe. As an end-to-end test of the technologies that will be used to perform this task, a multi-disciplinary team of researchers moved a small portion (10 TB) of the multimodel Coupled Model Intercomparison Project, Phase 3 data set used in the IPCC Fourth Assessment Report from three sources---the Argonne Leadership Computing Facility (ALCF), Lawrence Livermore National Laboratory (LLNL) and National Energy Research Scientific Computing Center (NERSC)---to the 2009 Supercomputing conference (SC09) show floor in Portland, Oregon, over circuits provided by DOE's ESnet. The team achieved a sustained data rate of 15 Gb/s on a 20 Gb/s network. More important, this effort provided critical feedback on how to deploy, tune, and monitor the middleware that will be used to replicate the upcoming petascale climate datasets. We report on obstacles overcome and the key lessons learned from this successful bandwidth challenge effort.

The nature of grid and distributed computing implies communication between heterogeneous systems over a wide and ever-changing variety of network environments. Often large amounts of data are stored in remote locations and must be transmitted in bulk. It is desirable to have the bulk data transfers be as fast as possible; however, because of the dynamic networks involved, it is often hard to predict what protocol will provide the fastest service for a given situation. In this paper we present XlOPerf, a network protocol testing and evaluation tool. XlOPerf is a command line program written on top of Globus XIO with a simple and well-defined interface to many different protocol implementations. XlOPerf was created to give users a way to quickly and easily experiment with an open-ended set of protocols over real networks to determine which will best suit their needs. We present a brief study of the overhead introduced by XlOPerf and the performance when using a variety of protocols.

The GridFTP extensions to the File Transfer Protocol define a general-purpose mechanism for secure, reliable, high-performance data movement. We report here on the Globus striped GridFTP framework, a set of client and server libraries designed to support the construction of data-intensive tools and applications. We describe the design of both this framework and a striped GridFTP server constructed within the framework. We show that this server is faster than other FTP servers in both single-process and striped configurations, achieving, for example, speeds of 27.3 Gbit/s memory-to-memory and 17 Gbit/s disk-to-disk over a 60 millisecond round trip time, 30 Gbit/s network. In another experiment, we show that the server can support 1800 concurrent clients without excessive load. We argue that this combination of performance and modular structure make the Globus GridFTP framework both a good foundation on which to build tools and applications, and a unique testbed for the study of innovative data management techniques and network protocols.

Grid computing is concerned with the sharing and coordinated use of diverse resources in distributed "virtual organizations." The dynamic and multiinstitutional nature of these environments introduces challenging security issues that demand new technical approaches. In particular, one must deal with diverse local mechanisms, support dynamic creation of services, and enable dynamic creation of trust domains. We describe how these issues are addressed in two generations of the Globus Toolkit/spl reg/. First, we review the Globus Toolkit version 2 (GT2) approach; then we describe new approaches developed to support the Globus Toolkit version 3 (GT3) implementation of the Open Grid Services Architecture, an initiative that is recasting Grid concepts within a service-oriented framework based on Web services. GT3's security implementation uses Web services security mechanisms for credential exchange and other purposes, and introduces a tight least-privilege model that avoids the need for any privileged network service.

Grid applications can combine the use of computation, storage, network, and other resources. These resources are often geographically distributed, adding to application complexity and thus the difficulty of understanding application performance. We present GridMapper, a tool for monitoring and visualizing the behavior of such distributed systems. GridMapper builds on basic mechanisms for registering, discovering, and accessing performance information sources, as well as for mapping from domain names to physical locations. The visualization system itself then supports the automatic layout of distributed sets of such sources and animation of their activities. We use a set of examples to illustrate how the system can provide valuable insights into the behavior and performance of a range of different applications.

The efficient implementation of collective communication operations has received much attention. Initial efforts modeled network communication and produced "optimal" trees based on those models. However, the models used by these initial efforts assumed equal point-to-point latencies between any two processes. This assumption is violated in heterogeneous systems such as clusters of SMPs and wide-area "computational grids", and as a result, collective operations that utilize the trees generated by these models perform suboptimally. In response, more recent work has focused on creating topology-aware trees for collective operations that minimize communication across slower channels (e.g., a wide-area network). While these efforts have significant communication benefits, they all limit their view of the network to only two layers. We present a strategy based upon a multilayer view of the network. By creating multilevel topology trees we take advantage of communication cost differences at every level in the network. We used this strategy to implement topology-aware versions of several MPI collective operations in MPICH-G, the Globus-enabled version of the popular MPICH implementation of the MPI standard. Using information about topology discovered by Globus, we construct these topology-aware trees automatically during execution, thus freeing the MPI application programmer from having to write special files or functions to describe the topology to the MPICH library. We present results demonstrating the advantages of our multilevel approach by comparing it to the default (topology-unaware) implementation provided by MPICH and a topology-aware two-layer implementation.