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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Anderson, M. Ballard, G. Demmel, J. Keutzer, K. |
| Copyright Year | 2011 |
| Abstract | We describe an implementation of the Communication-Avoiding QR (CAQR) factorization that runs entirely on a single graphics processor (GPU). We show that the reduction in memory traffic provided by CAQR allows us to outperform existing parallel GPU implementations of QR for a large class of tall-skinny matrices. Other GPU implementations of QR handle panel factorizations by either sending the work to a general-purpose processor or using entirely bandwidth-bound operations, incurring data transfer overheads. In contrast, our QR is done entirely on the GPU using compute-bound kernels, meaning performance is good regardless of the width of the matrix. As a result, we outperform CULA, a parallel linear algebra library for GPUs by up to 17x for tall-skinny matrices and Intel's Math Kernel Library (MKL) by up to 12x. We also discuss stationary video background subtraction as a motivating application. We apply a recent statistical approach, which requires many iterations of computing the singular value decomposition of a tall-skinny matrix. Using CAQR as a first step to getting the singular value decomposition, we are able to get the answer 3x faster than if we use a traditional bandwidth-bound GPU QR factorization tuned specifically for that matrix size, and 30x faster than if we use Intel's Math Kernel Library (MKL) singular value decomposition routine on a multicore CPU. |
| Starting Page | 48 |
| Ending Page | 58 |
| File Size | 1634736 |
| Page Count | 11 |
| File Format | |
| ISBN | 9781612843728 |
| ISSN | 15302075 |
| DOI | 10.1109/IPDPS.2011.15 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-05-16 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Graphics processing unit Matrix decomposition Kernel Libraries Vegetation Instruction sets |
| Content Type | Text |
| Resource Type | Article |
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