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Double Divide and Conquer Singular Value Decomposition
This project forked from sddelong/ddc-svd
Double Divide and Conquer Singular Value Decomposition
DOUBLE DIVIDE AND CONQUER SINGULAR VALUE DECOMPOSITION ON THE GPU Authors: Travis Askham, Mike Lewis, Steven Delong setup: Make sure either your C_INCLUDE_PATH or the variable OPENCL_INC is pointing to the directory where your openCL include files are (This directory should have the CL subdirectory) /my/path/to/include likewise, make sure either the LD_LIBRARY_PATH or OPENCL_LIB variables have the path to your opencl library files. /home/my/path/to/lib/x86_64 Then change to the ddc-svd directory and type make. You should have the executable test-whole-svd. This can be run with ./test-whole-svd m n where m and n are integers for the number of rows and columns of a random matrix that will be decomposed into it's singular values and vectors. To use the svd in your own code, you need to use the svd_gpu function. You can find the details of this function in svd_gpu.c. To compile and run it, follow the example of test-whole-svd.c in terms of the includes, the Makefile, and the function call itself. Many of the components of the svd computation are stand alone. See additional README files for further info.
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