Abstract
The complexity of many problems in science and engineering requires computational capacity exceeding what the average user can expect from a single computational center. While many of these problems can be viewed as a set of independent tasks, their collective complexity easily requires millions of core-hours on any high-power computing (HPC) resource, and throughput that can't be sustained by a single, multiuser queuing system. An exploration of the use of aggregated HPC resources to solve large-scale engineering problems shows that it's possible to build a computational federation that's easy for end users to implement, and is elastic, resilient, and scalable. Here, the authors argue that the fusion of federated computing and real-life engineering problems can be brought to the average user if relevant middleware is provided. They report on the use of federation of 10 distributed heterogeneous HPC resources to perform a large-scale interrogation of the parameter space in the microscale fluid flow problem.
| Original language | English |
|---|---|
| Article number | 6695747 |
| Pages (from-to) | 62-72 |
| Number of pages | 11 |
| Journal | Computing in Science and Engineering |
| Volume | 16 |
| Issue number | 4 |
| DOIs | |
| State | Published - 2014 |
Keywords
- Cloud computing
- Federated computing
- Fluid flow
- Large-scale engineering problems
- Scientific computing
- Software-defined infrastructure
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