David Y. Hancock

Jetstream: a self-provisioned, scalable science and engineering cloud environment

Jetstream will be the first production cloud resource supporting general science and engineering research within the XD ecosystem. In this report we describe the motivation for proposing Jetstream, the configuration of the Jetstream system as funded by the NSF, the team that is implementing Jetstream, and the communities we expect to use this new system. Our hope and plan is that Jetstream, which will become available for production use in 2016, will aid thousands of researchers who need modest amounts of computing power interactively. The implementation of Jetstream should increase the size and disciplinary diversity of the US research community that makes use of the resources of the XD ecosystem.

What is cyberinfrastructure

Cyberinfrastructure is a word commonly used but lacking a single, precise definition. One recognizes intuitively the analogy with infrastructure, and the use of cyber to refer to thinking or computing -- but what exactly is cyberinfrastructure as opposed to information technology infrastructure? Indiana University has developed one of the more widely cited definitions of cyberinfrastructure. Cyberinfrastructure consists of computing systems, data storage systems, advanced instruments and data repositories, visualization environments, and people, all linked together by software and high performance networks to improve research productivity and enable breakthroughs not otherwise possible. A second definition, more inclusive of scholarship generally and educational activities, has also been published and is useful in describing cyberinfrastructure: Cyberinfrastructure consists of computational systems, data and information management, advanced instruments, visualization environments, and people, all linked together by software and advanced networks to improve scholarly productivity and enable knowledge breakthroughs and discoveries not otherwise possible. In this paper, we describe the origin of the term cyberinfrastructure based on the history of the root word infrastructure, discuss several terms related to cyberinfrastructure, and provide several examples of cyberinfrastructure

Demonstrating lustre over a 100Gbps wide area network of 3,500km

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 Lustres 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.

Jetstream: A Cloud System Enabling Learning in Higher Education Communities

Jetstream is the first production cloud funded by the NSF for conducting general-purpose science and engineering research as well as an easy-to-use platform for education activities. Unlike many high-performance computing systems, Jetstream uses the interactive Atmosphere graphical user interface developed as part of the iPlant (now CyVerse) project and focuses on interactive use on uniprocessor or multiprocessor. This interface provides for a lower barrier of entry for use by educators, students, practicing scientists, and engineers. A key part of Jetstreams mission is to extend the reach of the NSFs eXtreme Digital (XD) program to a community of users who have not previously utilized NSF XD program resources, including those communities and institutions that traditionally lack significant cyberinfrastructure resources. One manner in which Jetstream eases this access is via virtual desktops facilitating use in education and research at small colleges and universities, including Historically Black Colleges and Universities (HBCUs), Minority Serving Institutions (MSIs), Tribal colleges, and higher education institutions in states designated by the NSF as eligible for funding via the Experimental Program to Stimulate Competitive Research (EPSCoR). Jetstream entered into full production in September 2016 and during the first six months it has supported more than a dozen educational efforts across the United States. Here, we discuss how educators at institutions of higher education have been using Jetstream in the classroom and at student-focused workshops. Specifically, we explore success stories, difficulties encountered, and everything in between. We also discuss plans for increasing the use of cloud-based systems in higher education. A primary goal in this paper is to spark discussions between educators and information technologists on how to improve using cloud resources in education.

Methodologies and practices for adoption of a novel national research environment

There are numerous domains of science that have been using high performance computing (HPC) systems for decades. Historically, when new HPC resources are introduced, specific variations may require researchers to make minor adjustments to their workflows but the general usage and expectations remain much the same. This consistency means that domain scientists can generally move from system to system as necessary and as new resources come online, they can be fairly easily adopted by these researchers. However, as novel resources, such as cloud computing systems, become available, additional work may be required in order to help researchers find and use the resource. When the goal of a systems funding and deployment is to find non-traditional research groups that have been under-served by the national cyberinfrastructure, a different approach to system adoption and training is required. When Jetstream was funded by the NSF as the first production research cloud, it became clear that to attract non-traditional or under-served researchers, a very proactive approach would be required. Here we show how the Jetstream team 1) developed methods and practices for increasing awareness of the system to both traditional HPC users as well as under-served and non-traditional users of HPC systems, 2) developed training approaches which highlight the capabilities that a cloud system may offer that are different from traditional HPC systems. We also discuss areas of success and failure, and plans for future efforts.

A PetaFLOPS Supercomputer as a Campus Resource: Innovation, Impact, and Models for Locally-Owned High Performance Computing at Research Colleges and Universities

In 1997, Indiana University (IU) began a purposeful and steady drive to expand the use of supercomputers and what we now call cyberinfrastructure. In 2001, IU implemented the first 1 TFLOPS supercomputer owned by and operated for a single US University. In 2013, IU made an analogous investment and achievement at the 1 PFLOPS level: Big Red II, a Cray XE6/XK7, was the first supercomputer capable of 1 PFLOPS (theoretical) performance that was a dedicated university resource. IUs high performance computing (HPC) resources have fostered innovation in disciplines from biology to chemistry to medicine. Currently, 185 disciplines and sub disciplines are represented on Big Red II with a wide variety of usage needs. Quantitative data suggest that investment in this supercomputer has been a good value to IU in terms of academic achievement and federal grant income. Here we will discuss how investment in Big Red II has benefited IU, and argue that locally-owned computational resources (scaled appropriately to needs and budgets) may be of benefit to many colleges and universities. We will also discuss software tools under development that will aid others in quantifying the benefit of investment in high performance computing to their campuses.

High Availability on Jetstream: Practices and Lessons Learned

Research computing has traditionally used high performance computing (HPC) clusters and has been a service not given to high availability without a doubling of computational and storage capacity. System maintenance such as security patching, firmware updates, and other system upgrades generally meant that the system would be unavailable for the duration of the work unless one has redundant HPC systems and storage. While efforts were often made to limit downtimes, when it became necessary, maintenance windows might be one to two hours or as much as an entire day. As the National Science Foundation (NSF) began funding non-traditional research systems, looking at ways to provide higher availability for researchers became one focus for service providers. One of the design elements of Jetstream was to have geographic dispersion to maximize availability. This was the first step in a number of design elements intended to make Jetstream exceed the NSFs availability requirements. We will examine the design steps employed, the components of the system and how the availability for each was considered in deployment, how maintenance is handled, and the lessons learned from the design and implementation of the Jetstream cloud.

Jetstream-Early operations performance, adoption, and impacts: Early Jetstream Performance and Results

Jetstream is a first of its kind system for the NSF — a distributed production cloud resource. We review the purpose for creating Jetstream, discuss Jetstreams key characteristics, describe our experiences from the first year of maintaining an OpenStack‐based cloud environment, and share some of the early scientific impacts achieved by Jetstream users. Jetstream offers a unique capability within the XSEDE‐supported US national cyberinfrastructure, delivering interactive virtual machines (VMs) via the Atmosphere interface. As a multi‐region deployment that operates as an integrated system, Jetstream is proving effective in supporting modes and disciplines of research traditionally underrepresented on larger XSEDE‐supported clusters and supercomputers. Already, Jetstream has been used to perform research and education in biology, biochemistry, atmospheric science, earth science, and computer science.

Jetstream: Early Operations Performance, Adoption, and Impacts

Jetstream, built with OpenStack, is the first production cloud funded by the NSF for conducting general-purpose science and engineering research as well as an easy-to-use platform for education activities. Unlike many high-performance computing systems, Jetstream uses the interactive Atmosphere graphical user interface developed as part of the iPlant (now CyVerse) project and focuses on interactive use on uniprocessor or multiprocessor. This interface provides for a lower barrier of entry for use by educators, students, practicing scientists, and engineers. A key part of Jetstreams mission is to extend the reach of the NSFs eXtreme Digital (XD) program to a community of users who have not previously utilized NSF XD program resources, including those communities and institutions that traditionally lack significant cyberinfrastructure resources. OpenStack deployments all have the same five basic services: identity, images, block storage, networking, and compute. There are additional services offered; however, by and large, they are underutilized. The use of these services will be discussed as well as highlights from the first year of production operations, and future plans for the project.

Innovations from the early user phase on the Jetstream Research Cloud.

We describe the Jetstream cyberinfrastructure for research, a purpose-built system with the goal of supporting “long-tail” research by providing a flexible infrastructure that can provide a set cloud services tuned for research applications, whether they be traditional HPC applications, science gateways, or desktop applications. Jetstream offers a library of virtual machines and allows the user to create their own virtual machines in order to provide an open cloud for science that allows both on-demand and persistent instances. The system is currently in early-user mode and a number of users at partner institutions are already creating and using images in the system. This paper details some of the early work being done with the system to create high performance clusters in an on-demand fashion to support scientific work directly as well as serve as capability backend to scientific gateways such as CyVerse and Galaxy.