An Investigation into Parallel SVD for MATH-GA.2011.001:
نویسندگان
چکیده
We discuss an investigation into parallelizing the computation of a singular value decomposition (SVD). We break the process into three steps: bidiagonalization, computation of the singular values, and computation of the singular vectors. We discuss the algorithms, parallelism, implementation, and performance of each of these three steps. The original goal was to accomplish all three tasks using a graphics processing unit (GPU) but the final implementation uses a combination of GPU computing and multicore central processing unit (CPU) computing. The two parallelization standards used were OpenCL and OpenMP. Our SVD implementation and its components are available freely online.
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