Cluster-based Computing Framework

A Cluster-based Computing Framework is a computing framework that is a cluster-based framework (to implement cluster computing jobs).

• AKA: Loosely-Coupled Multiprocessing Framework.
• Context:
  • It can range from being a Fault-Tolerant Cluster Framework to being a Weak-Availability Guarantee Cluster.
  • It can range from being a Special-Purpose Cluster Computing Framework to being a General-Purpose Cluster Computing Framework.
  • …
• Example(s):
  • Open Cluster Framework.
  • Red Hat Cluster Suite.
  • Spark Framework.
  • Hadoop Framework.
  • …
• Counter-Example(s):
  • a Single-Computer Computing Framework.
  • a Cluster-based Data Processing Framework.
  • a Distributed Operating System.
  • an Shared-Memory Multiprocessing Framework, such as OpenMP (for a supercomputer).
• See: MPI, Distributed Computing, Distcc, MPICH, Linux Virtual Server, Linux-HA, OpenSSI.

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References

2014

• (Wikipedia, 2014) ⇒ http://en.wikipedia.org/wiki/computer_cluster#Some_implementations Retrieved:2014-8-8.
  • The GNU/Linux world supports various cluster software; for application clustering, there is distcc, and MPICH. Linux Virtual Server, Linux-HA - director-based clusters that allow incoming requests for services to be distributed across multiple cluster nodes. MOSIX, openMosix, Kerrighed, OpenSSI are full-blown clusters integrated into the kernel that provide for automatic process migration among homogeneous nodes. OpenSSI, openMosix and Kerrighed are single-system image implementations.

     Microsoft Windows Compute Cluster Server 2003 based on the Windows Server platform provides pieces for High Performance Computing like the Job Scheduler, MSMPI library and management tools.

     gLite is a set of middleware technologies created by the Enabling Grids for E-sciencE (EGEE) project.

     slurm is also used to schedule and manage some of the largest supercomputer clusters (see top500 list.)

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