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A study of the fundamental obstacles to accelerate the preconditioned conjugate gradient (PCG) method on modern graphic processing units (GPUs) is presented and several techniques are proposed to enhance its performance over previous work independent of the GPU generation and the matrix sparsity pattern. The proposed enhancements increase the performance of PCG up to 23 times compared to vector optimized...
This paper describes our novel work of using GPUs to improve the performance of a homography-based visual servo system. We present our novel implementations of a GPU based Efficient Second-order Minimization (GPU-ESM) algorithm. By utilizing the tremendous parallel processing capability of a GPU, we have obtained significant acceleration over its CPU counterpart. Currently our GPU-ESM algorithm can...
In this paper, we present a novel implementation of a Cellular Genetic Algorithm (cGA) model for a multi-GPU platform using NVIDIA's CUDA technology. This multi-GPU cGA model is compared first against a serial version in CPU and then versus an implementation on a single GPU. We divide the different operations of the cGA into distinct sets of instructions called kernels. Using the multi-GPU platform...
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