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You're reading from  Hands-On GPU Programming with Python and CUDA

Product typeBook
Published inNov 2018
Reading LevelBeginner
PublisherPackt
ISBN-139781788993913
Edition1st Edition
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Dr. Brian Tuomanen
Dr. Brian Tuomanen
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Dr. Brian Tuomanen

Dr. Brian Tuomanen has been working with CUDA and General-Purpose GPU Programming since 2014. He received his Bachelor of Science in Electrical Engineering from the University of Washington in Seattle, and briefly worked as a Software Engineer before switching to Mathematics for Graduate School. He completed his Ph.D. in Mathematics at the University of Missouri in Columbia, where he first encountered GPU programming as a means for studying scientific problems. Dr. Tuomanen has spoken at the US Army Research Lab about General Purpose GPU programming, and has recently lead GPU integration and development at a Maryland based start-up company. He currently lives and works in the Seattle area.
Read more about Dr. Brian Tuomanen

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Using cuSolver from Scikit-CUDA

We will now look at how we can use cuSolver from Scikit-CUDA's linalg submodule. Again, this provides a high-level interface for both cuBLAS and cuSolver, so we don't have to get caught up in the small details.

As we noted in the introduction, cuSolver is a library that's used for performing more advanced linear algebra operations than cuBLAS, such as the Singular Value Decomposition, LU/QR/Cholesky factorization, and eigenvalue computations. Since cuSolver, like cuBLAS and cuFFT, is another vast library, we will only take the time to look at one of the most fundamental operations in data science and machine learning—SVD.

Please refer to NVIDIA's official documentation on cuSOLVER if you would like further information on this library: https://docs.NVIDIA.com/cuda/cusolver/index.html.
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Hands-On GPU Programming with Python and CUDA
Published in: Nov 2018Publisher: PacktISBN-13: 9781788993913

Author (1)

author image
Dr. Brian Tuomanen

Dr. Brian Tuomanen has been working with CUDA and General-Purpose GPU Programming since 2014. He received his Bachelor of Science in Electrical Engineering from the University of Washington in Seattle, and briefly worked as a Software Engineer before switching to Mathematics for Graduate School. He completed his Ph.D. in Mathematics at the University of Missouri in Columbia, where he first encountered GPU programming as a means for studying scientific problems. Dr. Tuomanen has spoken at the US Army Research Lab about General Purpose GPU programming, and has recently lead GPU integration and development at a Maryland based start-up company. He currently lives and works in the Seattle area.
Read more about Dr. Brian Tuomanen