Quadratic Programming (QP) problems frequently appear as core component when solving constrained optimal control or estimation problems. The focus of this paper is on accelerating an existing Interior Point Method (IPM) for solving QP problems by exploiting the parallel computing characteristics of GPU. We compare the so-called data-parallel and the problem-parallel approaches to achieve speed ...

We present a fast feature detector that uses the Graphics Processing Unit (GPU) to extract distinctive features from an image, which are suitable for reliable matching between different views of an object or a scene. This detector is a particularly useful tool for the computer vision community because it is: (i) simple to implement; (ii) extremely fast; (iii) operates stand alone requires no po...

Forward Wright-Fisher simulations are powerful in their ability to model complex demography and selection scenarios, but suffer from slow execution on the Central Processor Unit (CPU), thus limiting their usefulness. However, the single-locus Wright-Fisher forward algorithm is exceedingly parallelizable, with many steps that are so-called "embarrassingly parallel," consisting of a vast number o...

Genetic Algorithm (GA) is effective and robust method for solving many optimization problems. However, it may take more runs (iterations) and time to get optimal solution. The execution time to find the optimal solution also depends upon the niching-technique applied to evolving population. This paper provides the information about how various authors, researchers, scientists have implemented G...

This study focuses on the implementation of an efficient numerical technique for cryosurgery simulations on a graphics processing unit as an alternative means to accelerate runtime. This study is part of an ongoing effort to develop computerized training tools for cryosurgery, with prostate cryosurgery as a developmental model. The ability to perform rapid simulations of various test cases is c...