Apriori-Based algorithms are widely used for association rule mining. However, these algorithms cannot exploit the parallel processing power of modern GPU (Graphics Processing Unit). To make an algorithm to be compatible with GPU, it needs to be changed in representation of data, parallel processing and also in support count. In this paper we propose an Apriori-based algorithm HSApriorifor high speed association rule mining besides suitable data representation and support counting mechanisms. OpenCL is one of the best General Purpose Graphics Processing Unit (GPGPU) platforms used to implement the functionality of the algorithm. OpenCL with Java extensions are used for developing HSApriori. The datasets used include chess, pumsb, and accidents that are obtained from UCI machine learning repository. One more dataset used is synthetic in nature which is collected from IBM Almaden Quest Research Group. We built a prototype application to demonstrate the proof of concept. The experimental results are compared with BorgeltApriori. The results revealed that HSApriori outperforms BorgeltApriori.
Biomedical image reconstruction applications require producing high fidelity images in or close to real-time. We have implemented reconstruction of three dimensional conebeam computed tomography(CBCT) with two dimensional projections. The algorithm takes slices of the target, weights and filters them to backproject the data, then creates the final 3D volume. We have implemented the algorithm using […]
September 1, 2014 by hgpu
Over the past decade, the design of microprocessors has been shifting to a new model where the microprocessor has multiple homogeneous processing units, aka cores, as a result of heat dissipation and energy consumption issues. Meanwhile, the demand for heterogeneity increases in computing systems due to the need for high performance computing in recent years. […]
We show that surface normal information allows to significantly improve the accuracy of a spatio-temporal multi-view reconstruction. On one hand, normal information can improve the quality of photometric matching scores. On the other hand, the same normal information can be employed to drive an adaptive anisotropic surface regularization process which better preserves fine details and […]
GPU computing has become popular in computational finance and many financial institutions are moving their CPU based applications to the GPU platform. Since most Monte Carlo algorithms are embarrassingly parallel, they benefit greatly from parallel implementations, and consequently Monte Carlo has become a focal point in GPU computing. GPU speed-up examples reported in the literature […]
Computing platforms equipped with accelerators like GPUs have proven to provide great computational power. However, exploiting such platforms for existing scientific applications is not a trivial task. Current GPU programming frameworks such as CUDA C/C++ require low-level programming from the developer in order to achieve high performance code. As a result porting of applications to […]
A model of a multilayer device with non-trivial geometrical and material structure and its working process is suggested. The thermal behavior of the device as one principle characteristic is simulated. The algorithm for solving the non-stationary heat conduction problem with a time-dependent periodical heating source is suggested. The algorithm is based on finite difference explicit–implicit […]
A new trend in chip multiprocessor (CMP) design is to incorporate graphics processing unit (GPU) cores, making them heterogeneous. GPU cores have a higher bandwidth requirement than CPU cores, as they tend to generate much more memory requests. In order to achieve good performance, there must be sufficient bandwidth between the GPU shader cores and […]
Managing memory between the CPU and GPU is a major challenge in GPU computing. A programming model, Unified Memory Access (UMA), has been recently introduced by Nvidia to simplify the complexities of memory management while claiming good overall performance. In this paper, we investigate this programming model and evaluate its performance and programming model simplifications […]
Various guidelines for acceleration of MoM by GPU computing are summarized. Acceleration of direct/iterative solver for MoM by using GPU is realized. Quantitative study of computing time shows the performance of each guideline.
Parallelcomputing is one of significant components of the High Performance Computing (HPC) and is being used to solve problems, which are large and complex in nature. Fuzzy Logic System (FLS) is a problem that becomes computationally intensive with increase in number of inputs and/or fuzzy rules. Running an FLS is highly parallel in nature, therefore, […]
We present a block structured orthogonal factorization (BSOF) algorithm and its parallelization for computing the inversion of block p-cyclic matrices.We aim at the high performance on multicores with GPU accelerators. We provide a quantitative performance model for optimal host-device load balance, and validate the model through numerical tests. Benchmarking results show that the parallel BSOF […]
August 23, 2014 by hgpu