Mar 28, 2024  
OHIO University Graduate Catalog 2020-21 
    
OHIO University Graduate Catalog 2020-21 [Archived Catalog]

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CS 5120 - Parallel Computing I


Studies different parallel structures to familiarize students with variety of approaches to parallel computing and the strengths and weaknesses of each approach. Concentrates on understanding methods for developing parallel algorithms and analyzing their performance. Advantages and disadvantages of different methods for mapping algorithms onto several different paralllel architecture studied. Algorithms discussed include sorting, searching, matrix operations, and others.

Requisites:
Credit Hours: 3
Repeat/Retake Information: May not be retaken.
Lecture/Lab Hours: 3.0 lecture
Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I
Learning Outcomes:
  • Student will become familiarized with common parallel performance measures, including the granularity of parallel processing, speed-up, scalability, and efficiency
  • Student will become familiarized with common shared memory programming API¿s and environments.
  • Student will become familiarized with different parallel computing taxonomies
  • Students will gain an understanding of distributed message passing libraries and inter-process communication technologies.
  • Students will gain an understanding of solutions to common shared memory programming problems.
  • Students will gain an understanding of the basic concepts of different forms of parallel computing, including instruction level parallelism, shared memory multiprocessing, distributed memory multiprocessing, clusters and grid computing
  • Students will gain an understanding of the concepts of concurrency, parallelism and speedup
  • Students will gain an understanding of the concepts of distributed memory programming.
  • Students will gain an understanding of the fundamentals of shared memory programming
  • Students will gain the ability to develop and analyze solutions to specific computational problems in distributed memory multiprocessor systems.
  • Students will gain the ability to develop and analyze solutions to specific computational problems on shared memory multiprocessor systems.



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