High Performance Parallel Computing With Clouds and Cloud Technologies
Source: Indiana University
Infrastructure services (Infrastructure-as-a-service), provided by cloud vendors, allow any user to provision a large number of compute instances fairly easily. Whether leased from public clouds or allocated from private clouds, utilizing these virtual resources to perform data/compute intensive analyses requires employing different parallel runtimes to implement such applications. Among many parallelizable problems, most "Pleasingly Parallel" applications can be performed using MapReduce technologies such as Hadoop, CGL-MapReduce, and Dryad, in a fairly easy manner. However, many scientific applications, which require complex communication patterns, still require optimized runtimes such as MPI.
| Format: | Size: | 906.40 | |
| Date: | Jun 2009 |
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