Memory and Run-Time Efficient Image Texture Classification using NVIDIA GPU as a co-processor

ECE 734 PROJECT PROPOSAL Implementing Memory and Run-Time Efficient Texture Classification using NVIDIA GPU, as a co-processor

An approach to Improve Particle Swarm Optimization Algorithm Using CUDA

The time consumption in solving computationally heavy problems has always been a concern for computer programmers. Due to simplicity of its implementation, the PSO (Particle Swarm Optimization) is a suitable meta-heuristic algorithm for solving computationally heavy problems. However, despite the simplicity, the algorithm is inefficient for solving real computationally heavy problems but the pr...

Optimized pre-processing input plane GPU implementation of an optical face recognition technique using a segmented phase only composite filter

The key outcome of this work is to propose and validate a fast and robust correlation scheme for face recognition applications. The robustness of this fast correlator is ensured by an adapted pre-processing step for the target image allowing us to minimize the impact of its (possibly noisy and varying) amplitude spectrum information. A segmented composite filter is optimized, at the very outset...

Texture Cache Approximation on GPUs

We present texture cache approximation as a method for using existing hardware on GPUs to eliminate costly global memory accesses. We develop a technique for using a GPU’s texture fetch units to generate approximate values, and argue that this technique is applicable to a wide variety of GPU kernels. Applying texture cache approximation to an image blur kernel on an NVIDIA 780GTX, we obtain a 1...

Energy Efficient Platform for Sobel Filter in Energy and Size Constrained Systems

The design space of a computer vision engineer is very large when it comes to the selection of hardware for high performance and energy efficient computing. By comparing a few potential (Parallella with Epiphany co-processor, Radxa Rock2 with Mali T764 GPU and Airvision Core X1 with Nvidia Tegra X1) platforms we have narrowed down this design space. This paper analyses three recent heterogeneou...