A number of services for scientific computing based on cloud resources have recently drawn significant attention in both research and infrastructure provider communities. Most cloud resources currently available lack true high performance characteristics, such as high-speed interconnects or storage. Researchers studying cloud systems have pointed out that many cloud services do not provide service level agreements that may meet the needs of the research community. Furthermore, the lack of location information provided to the user and the shared nature of the systems use may create risk for users of the system, in the instance that their data is moved to an unknown location with an unknown level of security. Indiana University and Penguin Computing have partnered to create a system, Rockhopper, which addresses many of these issues. This system is a true high performance resource, with on-demand allocations, control, and tracking of jobs, situated at Indiana University's high-security datacenter facility. Rockhopper allows researchers to flexibly conduct their work under a number of use cases while also serving as an extension of cyberinfrastructure that scales from the researcher's local environment all the way up through large national resources. We describe the architecture and ideas behind the creation of the system, present a use case for campus bridging, and provide a typical example of system usage. In a comparison of Rockhopper to a cloud-based system, we run the Trinity RNA-seq software against a number of datasets on both the Rockhopper system and on Amazon's EC2 service.

As part of the SCinet Research Sandbox at the IEEE/ACM International Conference for High Performance Computing, Networking, Storage and Analysis (SC11), Indiana University utilized a dedicated 100 Gbps wide area network (WAN) link spanning more than 3,500 km (2,175 mi) to demonstrate the capabilities of the Lustre high performance parallel file system in a high bandwidth, high latency WAN environment. This demonstration functioned as a proof of concept and provided an opportunity to study Lustre's performance over a 100 Gbps WAN. To characterize the performance of the network and file system a series of benchmarks and tests were undertaken. These included low level iperf network tests, Lustre networking tests, file system tests with the IOR benchmark, and a suite of real-world applications reading and writing to the file system. All of the tests and benchmarks were run over a the WAN link with a latency of 50.5 ms. In this article we describe the configuration and constraints of the demonstration and focus on the key findings regarding the networking layer for this extremely high bandwidth and high latency connection. Of particular interest are the challenges presented by link aggregation for a relatively small number of high bandwidth connections, and the specifics of virtual local area network routing for 100 Gbps routing elements.

As part of the SCinet Research Sandbox at the Supercomputing 2011 conference, Indiana University (IU) demonstrated use of the Lustre high performance parallel file system over a dedicated 100 Gbps wide area network (WAN) spanning more than 3,500 km (2,175 mi). This demonstration functioned as a proof of concept and provided an opportunity to study Lustre's performance over a 100 Gbps WAN. To characterize the performance of the network and file system, low level iperf network tests, file system tests with the IOR benchmark, and a suite of real-world applications reading and writing to the file system were run over a latency of 50.5 ms. In this article we describe the configuration and constraints of the demonstration and outline key findings.

Abstract This paper describes Indiana University's implementation, performance testing, and use of a large high performance computing system. IU's Big Red, a 20.48 TFLOPS IBM e1350 BladeCenter cluster, appeared in the 27th Top500 list as the 23rd fastest supercomputer in the world in June 2006. In spring 2007, this computer was upgraded to 30.72 TFLOPS. The e1350 BladeCenter architecture, including two internal networks accessible to users and user applications and two networks used exclusively for system management, has enabled the system to provide good scalability on many important applications while being well manageable. Implementing a system based on the JS21 Blade and PowerPC 970MP processor within the US TeraGrid presented certain challenges, given that Intel‐compatible processors dominate the TeraGrid. However, the particular characteristics of the PowerPC have enabled it to be highly popular among certain application communities, particularly users of molecular dynamics and weather forecasting codes. A critical aspect of Big Red's implementation has been a focus on Science Gateways, which provide graphical interfaces to systems supporting end‐to‐end scientific workflows. Several Science Gateways have been implemented that access Big Red as a computational resource—some via the TeraGrid, some not affiliated with the TeraGrid. In summary, Big Red has been successfully integrated with the TeraGrid, and is used by many researchers locally at IU via grids and Science Gateways. It has been a success in terms of enabling scientific discoveries at IU and, via the TeraGrid, across the US. Copyright © 2009 John Wiley & Sons, Ltd.

Indiana University's 20.48 Teraflop IBM e1350 BladeCenter supercomputer system ("Big Red") has been made available to researchers throughout the U.S. via the NSF-funded TeraGrid. The Big Red system finished 23rd on the June 2006 Top500 list, making it at that time the fastest supercomputer owned and operated by a U.S. university and also the fastest computer to be made available through the TeraGrid to date.Big Red is a distributed shared-memory cluster, consisting of 512 IBM BladeCenter JS21s, each with two dual-core PowerPC 970 MP processors (2.5GHz), 8GB of ECC PC3200 SDRAM, 72GB local SATA disk for scratch space, 360 TB GPFS parallel filesystem and a PCI-X Myrinet 2000 adapter for high-bandwidth, low-latency MPI applications.A significant portion of Big Red will be allocated to TeraGrid utilization. The TeraGrid is the National Science Foundation's flagship effort to create a national cyberinfrastructure to support academic research and promote scientific discovery.

Indiana University provides powerful compute, storage, and network resources to a diverse local and national research community every day. IU's facilities have been used to support data-intensive applications ranging from digital humanities to computational biology.For this year's bandwidth challenge, several IU researchers will conduct experiments from the exhibit floor utilizing the resources that University Information Technology Services currently provides.Using IU's newly constructed 535 TB Data Capacitor and an additional component installed on the exhibit floor, we will use Lustre across the wide area network to simultaneously facilitate dynamic weather modeling, protein analysis, instrument data capture, and the production, storage, and analysis of simulation data.