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University of Utah: C-SAFE Uses Linux HPCC in Fire Research
2/3/2003
Linux Advantage
C-SAFE chose to implement a Linux cluster for one primary reason: We could not
afford a traditional supercomputer of the class and scale of those purchased
by the D'E for the ASCP program. The cluster solution is based on commodity
PC technology; each node is very similar to a personal computer. This leverages
the mass-production of personal computers to provide a price/performance ratio
unattainable by most other technologies.
Other advantages of this approach include leveraging a growing familiarity with the Linux operating system, and of course the fact that it is considered an “in vogue” thing to do in Computer Science circles. We also intend to utilize the cluster for real-time interaction with these long-running simulations, something that would be difficult to do on a larger shared resource.
However, this power d'es not come without caveat. First, the application must be able to perform well in this environment. A Linux cluster has communication latencies (both hardware and software) that are quite large relative to a traditional supercomputer. The C-SAFE software employs a novel approach to parallelism that helps mitigate the effects of these latencies, and we performed preliminary benchmarks that gave us confidence that we could achieve good performance on a machine of this size. Second, the installation and setup of a cluster can be quite complex and time-consuming.
Fortunately, Dell provided the physical installation of our cluster, which saved considerable time. Installation of operating systems on each of the 128 nodes, as well as installation and setup of additional HPC software, consumed considerable additional time.
Numerous companies, both large and small, offer computational clusters of this type. The University of Utah chose Dell to implement our cluster because of a competitive price/performance ratio, company reputation, and features of the PowerEdge 2550. Dell provided physical installation and setup of the cluster, which immensely reduced the work required to deploy this machine. The cluster fills seven standard racks, stands about six feet tall, four feet deep and 14 feet long. It produces a considerable amount of heat and fan noise.
Lessons Learned
Those that are considering a large compute cluster should keep in mind several
lessons that we have learned along the way (either from others or from the school
of hard knocks).
First, start small; we leveraged expertise from building smaller clusters before we considered a project of this size. Second, do not underestimate the time involved in physical installation and software setup of a machine of this nature. Depending on the complexity of the required environment, this can take weeks to months. Third, planning is critical. Considerations must be taken for the power consumption, heat production and physical footprint of the machine.
Finally, the biggest lesson is that it can actually work; we are performing simulations that required computers that just five years ago cost nearly a factor of 100 more. This gives us hope that our largest simulations may be achievable on a relatively common platform in the not-too-distant future. Early access to this magnitude of resources from the D'E was critical to the development of these simulations. Once the hurdles are cleared, a high-performance cluster can provide a dramatic quantity of compute cycles for complex scientific computations such as those performed for C-SAFE research.
For information contact Steven Parker, Research Assistant Professor, University of Utah, at sparker@cs.utah.edu.
Steven Parker is a Research Assistant Professor at the University of Utah.
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