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Analyzing General-Purpose Computing Performance On Gpu, Fanfu Meng
Analyzing General-Purpose Computing Performance On Gpu, Fanfu Meng
Master's Theses
ABSTRACT
Analyzing General-Purpose Computing Performance on GPU
Graphic Processing Unit (GPU) has become one of the most important components in modern computer systems. GPUs have evolved from a single -purpose graphic rendering hardware to a powerful processor that is capable of handling many different kinds of computing tasks. However, GPUs don’t perform well on every application, and it takes a lot of design effort to get good performance on a GPU.
This thesis aims to investigate the relative performance of a GPU vs. CPU. Design effort is held minimum for both CPU implementations and GPU implementations. Matrix multiplication, Advance Encryption …
Optimizing Harris Corner Detection On Gpgpus Using Cuda, Justin Loundagin
Optimizing Harris Corner Detection On Gpgpus Using Cuda, Justin Loundagin
Master's Theses
ABSTRACT
Optimizing Harris Corner Detection on GPGPUs Using CUDA
The objective of this thesis is to optimize the Harris corner detection algorithm implementation on NVIDIA GPGPUs using the CUDA software platform and measure the performance benefit. The Harris corner detection algorithm—developed by C. Harris and M. Stephens—discovers well defined corner points within an image. The corner detection implementation has been proven to be computationally intensive, thus realtime performance is difficult with a sequential software implementation. This thesis decomposes the Harris corner detection algorithm into a set of parallel stages, each of which are implemented and optimized on the CUDA platform. …