Computer Engineering Commons^™

Parallel Implementation Of The Singular Value Decomposition Using Opencl, Bhushan Rayrikar

All Theses

General-Purpose Graphics Processing Units (GPGPUs) have massively parallel computational capabilities. Low cost and ease of programming make them a popular choice over other parallel architectures such as large clusters and accelerators such as Field-Programmable Gate Arrays (FPGAs). Mature programming frameworks for GPGPUs, such as CUDA from Nvidia and OpenCL from the Khronos Group, reduce the learning curve and development time for programming GPGPU architectures. OpenCL, a relatively new industry standard for parallel computing makes it possible to write a single program for heterogeneous platforms that is portable across multiple platforms including GPGPUs and multi-core processors with minimal coding modifications.
GPGPU …