Cluster interconnects are the key to good performance. Understanding what type of interconnect works best for your application can make a big difference in both cost and performance.
- Written by Jeff Layton
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It is what makes a cluster "a cluster"
An often asked question from both "clusters newbies" and experienced cluster users is, "what kind of interconnects are available?" The question is important for two reasons. First, the price of interconnects can range from as little as $32 per node to as much as $3,500 per node, yet the choice of an interconnect can have a huge impact on the performance of the codes and the scalability of the codes. And second, many users are not aware of all the possibilities. People new to clusters may not know of the interconnection options and, sometimes, experienced people choose an interconnect and become fixated on it, ignoring all of the alternatives. The interconnect is an important choice and ultimately the choice depends upon on your code, requirements, and budget.
In this review we provide an overview of the available technologies and conclude with two tables summarizing key features and pricing for various size clusters.
- Written by Gilad Shainer
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Forget the benchmarks, look at real performance. Two other papers by Gilad, Single Points of Performance and Optimum Connectivity in the Multi-core Environment, expand on this idea.
Scientists, engineers and analysts in virtually every field are turning to high performance computing to solve todayâs vital and complex problems. Simulations are increasingly replacing expensive physical testing, as more complex environments can be modeled and in some cases, fully simulated.
High-performance computing encompasses advanced computation over parallel processing, enabling faster execution of highly compute intensive tasks such as climate research, molecular modeling, physical simulations, cryptanalysis, geophysical modeling, automotive and aerospace design, financial modeling, data mining and more. HPC clusters become the most common building blocks for high-performance computing, not only because they are affordable, but because they provide the needed flexibility and deliver superior price/performance compared to proprietary symmetric multiprocessing (SMP) systems, with the simplicity and value of industry standard computing.
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