Research Computing Workshop Common Solutions Group Meeting

1. The Role of Central IT in meeting Large-scale Computational and Data Needs Vijay K. Agarwala, George Otto, Jason Holmes, and Michael Fenn Research Computing and Cyberinfrastructure Information Technology Services The Pennsylvania State University University Park, PA 16802 george-otto@psu.edu Research Computing Workshop Common Solutions Group Meeting June 16, 2011

2. Meeting large-scale computational and data needs RCC, a part of the central IT organization at Penn State, allocates its resources equally between three functions: Teaching: invited lectures on large-scale computational and data techniques in undergraduate and graduate classes, seminars, workshops, user group meetings, teaching-on-demand, and systems support for classes. Independent curiosity-driven research: one-on-one support and consulting for research with academic credit. Exploratory partnerships with faculty. Sponsored research: support for proposal development, student and staff training, and successful implementation of hardware and software systems. It is important for central IT organizations to recognize this three-pronged service in delivery of advanced computing resources.

3. Benefits of supporting Advanced Computing at Central IT • Efficient and cost-effective resource provisioning and operations: • Coordinated resource provisioning can provide cost and utilization efficiencies at the institutional level. Shared resources offer better scalability and more optimal utilization when compared with more fragmented efforts at the level of individual research grants or groups. • Consistent and persistent professional support: • Persistent professional support offers continuity of skills and services for the research community at large. • Responsiveness to the needs of researchers: • Campus based computational resources are designed, and their software stacks tuned, to meet specific needs of researchers, with the sole focus on increasing computational productivity of faculty and students. • Support for computational science education: • Advanced computing systems and staff expertise can be leveraged for hands-on training and individual consulting for more challenging problems, helping to create and sustain interest in advanced computing technologies and applications among faculty, graduate students, and the undergraduate student community across all disciplines at the university. • Partnerships with vendors and industry developers: • An advanced computing group, as a part of central IT, is well positioned for forging relationships with technology developers and suppliers, allowing for more futures-oriented planning, the development of local test beds for new technologies, and formation of "local collaboratories" around which facultyand students across the entire campus can collaborate for more effective adoption of advanced computing technologies and techniques in their ongoing work. • Institutional competitiveness for research proposals: • Faculty research proposals can demonstrate institutional support, both for infrastructure and expertise.

4. Building Advanced Computing services as a part of Central ITTop 10 practices • Appeal to a broad constituency: science, engineering, medicine, business, humanities, liberal arts. Provision 25% of compute cycles with minimal requirements of proposal and review. • Flexibility in system configuration and adaptability to faculty needs: work with partners on their queue requirements, accommodate temporary priority boost. • Keep barriers to faculty participation low: as low as a $5000 investment for a contributing partner with priority access. Try-before-you-buy program and guest status for prospective faculty partners. • Maximize system utilization: consistently above 90%, even contributing partners don't have instantaneous access. • Extensive software stack, and rapid turnaround in installation of new software: rich set of tools, compilers, libraries, community codes and ISV codes. • Provide consulting with subject matter expertise: differentiate the service from “flop shops” and cloud providers. • Strong commitment to training: teaching in classes, seminars, workshops. • Build strong partnerships with hardware and software vendors. • Make new technologies and test beds available to faculty and students. • Provide accurate and daily system utilization data.

5. The case for investment in Computing and CyberinfrastructureIs there a “right to compute” as much as faculty/students need to? • At a comprehensive research university, it is likely that over the next few years 25-50% of faculty and students will use computations in their teaching, learning and research endeavors. These will be either data centric and/or science and engineering based modeling and simulation. About 25% of this community needs large-scale computationresources. This indicates that between 5 to 10% of the academic community on a campus can benefit from advanced computing services. For example, at a university with 50,000 students and faculty, 5,000 are likely to benefit from being able to use compute engines and advanced research CI. • This 10% segment of the academic community has a major role in bringing external grants and contributes a large share of a university’s research funding. The expectation amongst this segment is that the institution should meet all of their CI needs. • An estimation: if a university were to annually invest in advanced CI 0.5% of its core operating budget, then it is likely that its advanced CI will keep pace with the increasing demand for such services in teaching and research. For example, for an institution with a core general funds operating budget of $1.5 billion, a yearly investment of $7.5 million in building and supporting the advanced CI will likely put large-scale computing and data services on a stable path.

6. A potential model for supporting Advanced Computing Assumes capital expenditures have been incurred for data center space as well as hardware and software. For example, a $10-12 million investment today in a green data center with a PUE of 1.25 and lower levels of redundancy can create a facility with: 5,000 sq. ft. of raised floor, 3,000 sq. ft. of office space, 2.0 megawatts of electrical power, limited capacity UPS, and HVAC systems, all housed in a 12,000 sq. ft. building. A similar $10 million investment in hardware today can build aggregate peak computing capacity of 500 teraflops (50,000 cores) and 20 - 50 petabytes of storage. Annual Operating Expenditure Hardware:            $2.50 million replacing 25% of installed compute capacity each year Software:              $0.25 million annual licensing costs Utility cost:         $1.00 million (100 racks, avg. 15 KW/rack) Staff (32 people): $3.50 million in salary and benefits Other expenses:  $0.25 million Total:                    $7.50 million annual investment in support of teaching, independent research and sponsored research Once initial capital expenditures have been made, it is possible to deliver compute cycles, with a high level of system and computational staff support, at a cost between $0.015 to $0.025 per core hour (2.8 - 3.0 GHz cores).

7. For more information on RCC systems and servicesrcc.its.psu.eduThank you.