Pushing the Limits of the Maya Cluster

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REU2014Team4.pdf (1.73 MB)

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https://userpages.umbc.edu/~gobbert/papers/REU2014Team4.pdf

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http://hdl.handle.net/11603/11406

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UMBC Mathematics and Statistics Department
UMBC Computer Science and Electrical Engineering Department
UMBC Faculty Collection
UMBC Student Collection

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Date

2014

Type of Work

technical report
Text

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Subjects

heterogeneous computing
GPUs
conjugate gradient method
Parallelization
UMBC High Performance Computing Facility (HPCF)
multiple cores/threads
parallel computing code
Poisson equation

Abstract

Parallelization of code, using multiple cores/threads, and heterogeneous computing, using the CPU with other devices, has come to the forefront of computing as methods to reduce the execution time of computationally demanding algorithms. For our project, we test various hardware setups on the maya cluster at UMBC, which include multiple nodes and GPUs, by solving the Poisson equation using the conjugate gradient method. To explore these different setups, we made use of both industry benchmarks and our own code, which we design using the compilers native to each device and API. We fi nd significant gains both in using a heterogeneous model and after parallelizing our code.