As design challenges become more complex and time to product launches are reduced, it is important to understand how to use a cluster for simulation, as compared to just a single node. “HPC Clusters Drive Design Optimization” is an excellent introduction on how to get the most out of a compute cluster.
“N-Body problems compare the interaction of N-bodies against N-bodies, which results in calculations of the order of N2. As this can be computationally very expensive, but a well understood process, techniques and optimizations can be performed on application code using compiler directives and easy to understand techniques.”
“With the advent of massively parallel computing coprocessors, numerical optimization for deep-learning disciplines is now possible. Complex real-time pattern recognition, for example, that can be used for self driving cars and augmented reality can be developed and high performance achieved with the use of specialized, highly tuned libraries. By just using the Message Passing Interface (MPI) API, very high performance can be attained on hundreds to thousands of Intel Xeon Phi processors.”
From bio-engineering and climate studies to big data and high frequency trading, HPC is playing an even greater role in today’s society. Without the power of HPC, the complex analysis and data driven decisions that are made as a result would be impossible. Because these super computers and HPC clusters are so powerful, they are expensive to cool, use massive amounts of energy, and can require a great deal of space.
Although there are a number of truly huge implementations of Lustre today, the community is still far from reaching the maximum configurations that the Lustre architecture is designed for. Inside the Lustre File System describes the basics of how the Lustre File System operates with descriptions of the newest features.