Type:

Other

Description:

High performance computing raises the bar for benchmarking. Existing benchmarking applications such as Linpack measure raw power of a computer in one dimension, but in the myriad architectures of high performance cluster computing an algorithm may show excellent performance on one cluster while on another cluster of the same benchmark it performs poorly. For a year a group of Earlham student researchers worked through the Undergraduate Petascale Education Program (UPEP) on an improved, multidimensional benchmarking technique that would more precisely capture the appropriateness of a cluster resource to a given algorithm. We planned to measure cluster effectiveness according to the thirteen dwarfs of computing as published in Berkeley's parallel computing research paper. To accomplish this we created PetaKit, a software stack for building and running programs on cluster computers.

Subjects:

  • Computer Science > General

Education Levels:

  • Grade 1
  • Grade 2
  • Grade 3
  • Grade 4
  • Grade 5
  • Grade 6
  • Grade 7
  • Grade 8
  • Grade 9
  • Grade 10
  • Grade 11
  • Grade 12

Keywords:

Informal Education,Visualization,Higher Education,NSDL,oai:nsdl.org:2200/20110907122304862T,Graduate/Professional,NSDL_SetSpec_ncs-NSDL-COLLECTION-000-003-112-055,Computer Science,Vocational/Professional Development Education,Computing and Information

Language:

English

Access Privileges:

Public - Available to anyone

License Deed:

Creative Commons Attribution Non-Commercial Share Alike

Collections:

None
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