John Bresnahan

Data management and transfer in high-performance computational grid environments

Abstract An emerging class of data-intensive applications involve the geographically dispersed extraction of complex scientific information from very large collections of measured or computed data. Such applications arise, for example, in experimental physics, where the data in question is generated by accelerators, and in simulation science, where the data is generated by supercomputers. So-called Data Grids provide essential infrastructure for such applications, much as the Internet provides essential services for applications such as e-mail and the Web. We describe here two services that we believe are fundamental to any Data Grid: reliable, high-speed transport and replica management. Our high-speed transport service, GridFTP, extends the popular FTP protocol with new features required for Data Grid applications, such as striping and partial file access. Our replica management service integrates a replica catalog with GridFTP transfers to provide for the creation, registration, location, and management of dataset replicas. We present the design of both services and also preliminary performance results. Our implementations exploit security and other services provided by the Globus Toolkit.

The Globus Striped GridFTP Framework and Server

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.

Secure, Efficient Data Transport and Replica Management for High-Performance Data-Intensive Computing

An emerging class of data-intensive applications involve the geographically dispersed extraction of complex scientific information from very large collections of measured or computed data. Such applications arise, for example, in experimental physics, where the data in question is generated by accelerators, and in simulation science, where the data is generated by supercomputers. So-called Data Grids provide essential infrastructure for such applications, much as the Internet provides essential services for applications such as e-mail and the Web. We describe here two services that we believe are fundamental to any Data Grid: reliable, high-speed transport and replica management. Our high-speed transport service, GridFTP, extends the popular FTP protocol with new features required for Data Grid applications, such as striping and partial file access. Our replica management service integrates a replica catalog with GridFTP transfers to provide for the creation, registration, location, and management of dataset replicas. We present the design of both services and also preliminary performance results. Our implementations exploit security and other services provided by the Globus Toolkit.

A high-throughput x-ray microtomography system at the Advanced Photon Source

~Received 14 November 2000; accepted for publication 23 January 2001!A third-generation synchrotron radiation source provides enough brilliance to acquire completetomographic data sets at 100 nm or better resolution in a few minutes. To take advantage of suchhigh-brilliance sources at the Advanced Photon Source, we have constructed a pipelined dataacquisition and reconstruction system that combines a fast detector system, high-speed datanetworks, and massively parallel computers to rapidly acquire the projection data and perform thereconstruction and rendering calculations. With the current setup, a data set can be obtained andreconstructed in tens of minutes. A specialized visualization computer makes renderedthree-dimensional~3D! images available to the beamline users minutes after the data acquisition iscompleted. This system is capable of examining a large number of samples at sub-mm 3D resolutionor studying the full 3D structure of a dynamically evolving sample on a 10 min temporal scale. Inthe near future, we expect to increase the spatial resolution to below 100 nm by using zone-platex-ray focusing optics and to improve the time resolution by the use of a broadband x-raymonochromator and a faster detector system.

Software as a service for data scientists

Globus Online manages fire-and-forget file transfers for big-data, high-performance scientific collaborations.

Going back and forth: efficient multideployment and multisnapshotting on clouds

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 providers 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%.

The globus extensible input/output system (XIO): a protocol independent IO system for the grid

In distributed heterogeneous grid environments the protocols used to exchange bits are crucial. As researchers work hard to discover the best new protocol for the grid, application developers struggle with ways to use these new protocols. A stable, consistent, and intuitive framework is needed to aid in the implementation and use of these protocols. While the application must not be burdened with the protocol details some of it may need to be exposed to take advantage of potential optimizations. In this paper we examine how the Globus XIO API provides this framework. We explore the performance implications of using this abstraction layer and the benefits gained in application as well as protocol development.

GridMapper: a tool for visualizing the behavior of large-scale distributed systems

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.

High-resolution remote rendering of large datasets in a collaborative environment

In a time when computational and data resources are distributed around the globe, users need to interact with these resources and each other easily and efficient. The Grid, by definition, represents a connection of distributed resources that can be used regardless of the users location. We have built a prototype visualization system using the Globus Toolkit, MPICH-G2, and the Access Grid in order to explore how future scientific collaborations may occur over the Grid. We describe our experience in demonstrating our system at iGrid2002, where the United States and the Netherlands were connected via a high-latency, high-bandwidth network. In particular, we focus on issues related to a Grid-based application that couples a collaboration component (including a user interface to the Access Grid) with a high-resolution remote rendering component.

Managing appliance launches in infrastructure clouds

Infrastructure cloud computing introduces a significant paradigm shift that has the potential to revolutionize how scientific computing is done. However, while it is actively adopted by a number of scientific communities, it is still lacking a well-developed and mature ecosystem that will allow the scientific community to better leverage the capabilities it offers. This paper introduces a specific addition to the infrastructure cloud ecosystem: the cloudinit.d program, a tool for launching, configuring, monitoring, and repairing a set of interdependent virtual machines in an infrastructure-as-a-service (IaaS) cloud or over a set of IaaS clouds. The cloudinit.d program was developed in the context of the Ocean Observatory Initiative (OOI) project to help it launch and maintain complex virtual platforms provisioned on demand on top of infrastructure clouds. Like the UNIX init.d program, cloudinit.d can launch specified groups of services and the VMs in which they run, at different run levels representing dependencies of the launched VMs. Once launched, cloudinit.d monitors the health of each running service to ensure that the overall application is operating properly. If a problem is detected in a service, cloudinit.d will restart only that service and any other service that failed that depended on it.