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March 28, 2008
In just eleven days during 2007, the Stanford University High-Performance Computing (HPC) Center nearly doubled the performance of its existing compute system. The center leveraged certification methodology from the Intel Cluster Ready Program to fully implement a 1,696-core cluster solution. The solution integrates Clustercorp, Dell and Panasas technologies to give the center the flexibility to meet ever-expanding computational and application requirements and to enable Stanford researchers to achieve faster time-to-results. Steve Jones, the founder and manager of the Stanford HPC Center, writes about the design and deployment of this system.
Mission: Enable CFD on Demand
The goal of our expansion was simple: acquire sufficient compute power to facilitate School of Engineering coursework and research efforts and to support the university's industrial affiliates program.
The system would need to support more than 200 researchers and effectively enable CFD on demand. Two departments in particular require large-scale, massively parallel computing resources for their work. Researchers in the mechanical engineering and aeronautics and astronautics departments leverage HPC Center resources to analyze the details of flow and acoustics created by helicopters in forward flight. Critical applications include two major in-house-developed simulation codes: Stanford University multiblock (SUmb) and CDP, named for the late Charles David Pierce. Commercial applications include ANSYS, Gaussian, MatLab, and VASP. Stanford's post-processing programs include EnSight for distributed rendering and Tecplot for visualization.
Objective: Extend In-House Support for Complex Code Verification and Validation
To address Stanford researchers' increasing needs for code validation, our team opted to bolster local compute resources. The goal was to build a cluster-based solution capable of scaling to thousands of nodes and supporting our large user base. The minimum expectation for the cluster was to run routine jobs in-house and to allow researchers to do more extensive verification and validation of code destined for the national labs. In addition to the large compute capacity and scalability requirements, the system needed to be capable of sustained performance with a file system fast enough to cope with massive I/O load and to deliver the granularity of results researchers require.
Challenge: Overcome Limitations in Space, Time, and Staff
While our plan was to dramatically expand compute resources, the project was bound by constraints of space, time and staff. The Stanford HPC Center has limited square footage in which to operate, so footprint was an issue, not only in terms of the system size and density, but also in how it would impact general HVAC requirements. Extensive project demands also applied scheduling pressures that propelled the deployment team to implement a more aggressive rollout than the three- to six-month timeframe more typically allotted for implementations of this scope. The final challenge was the center's requirements to grow overall services delivery while maintaining the existing support staff.
We felt that taking advantage of an integrated solution would help us meet our compute and deployment objectives without exceeding our space, time, and staffing limitations. In particular, we were sold on the idea of the Intel Cluster Ready (ICR) program where certification of the Clustercorp/Dell/Panasas solution had been completed upfront. The certification provides cluster components validation to ensure accurate configuration, optimal performance, and a system that is easy to manage and seamlessly expand.
Solution: Use Certified Best-of-Breed Compute, Distribution, and Storage Components
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