This teaching module guides students through the process of building programs using a heterogeneous computing module on a cluster of computers that are themselves able to perform parallel computations. The examples show partial code for running MPI message passing on processes on machines in a cluster, each of which can then run a parallel task in CUDA using a GPU card.
- Students will be able to build and run programs solving straightforward linear algebra techniques using a heterogeneous computing paradigm (MPI + CUDA) on a cluster of workstations.
Context for Use
- This module can be taught in a C Programming Language based course or in a course in which students have had prior C Programming Language experience. Student with little or no knowledge of C Programming Language will find materials inside this module difficult to apprehend, and therefore adequate of C Programming Language background is mandatory.
- It is designed for use as a lab.
- Depending on curriculum, this module could be considered to be at an "intermediate" or "advanced" level.
Description and Teaching Materials
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Teaching Notes and Tips
References and Resources
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