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An efficient out-of-core implementation of block
Cholesky decomposition on a multi-GPU system
with
Lin Cheng,
Peter Yoon and
Jiajia Zhao
Paper presented at
IASTED
PDCS
(2012)
Poster presented at IEEE EMBS
(2012)
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Synopsis
We use computing power of general-purpose
GPUs to accelerate a dense linear algebra routine known as
Cholesky decomposition. Our implementation eliminates the
limitation in memory space by storing the system matrix in hard disk
and loading only parts of it into main memory.
Publication Details
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Conference Paper:
Lin Cheng, Hyunsu Cho, Peter Yoon, and Jiajia
Zhao. “An Efficient Out-of-Core Implementation of Block
Cholesky Decomposition on a Multi-GPU System,”
Proceedings of the 24th IASTED International Conference:
Parallel and Distributed Computing and Systems, Las Vegas,
NV, November 13, 2012.
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Poster:
Lin Cheng, Hyunsu Cho, Peter Yoon, and Jiajia Zhao. “A
Multi-GPU Implementation of Incomplete Cholesky Decomposition for
Image Segmentation,”
The 34th Annual International Conference
of the IEEE Engineering in Medicine and Biology Society,
San Diego, CA, August 30, 2012.
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