high performance computing on graphics processing units: hgpu.org

Iterative solvers for sparse linear systems often benefit from using preconditioners. While there are implementations for many iterative methods that leverage the computing power of accelerators, porting the latest developments in preconditioners to accelerators has been challenging. In this paper we develop a self-adaptive multi-elimination preconditioner for graphics processing units (GPUs). The preconditioner is based […]

This thesis focuses on the testing of WPA/WPA 2 password strength. Recently, due to progress in calculation power and technology, new factors must be taken into account when choosing a WPA/WPA2 secure password. A study regarding the security of the current deployed password is reported here. Harnessing the computational power of a single and old […]

Parallelization of scientific problems is a challenging task which has a wide application area both on distributed programming, cloud computing and recently on GPGPU. Spectral graph partitioning is a widely used technique in many fields such as image processing, scientific computing, machine learning etc. In this study we analyze spectral graph partitioning subroutines on a […]

The growing number of Boolean variables requires very efficient approaches to solve the given tasks. We explore the utilization of the GPU for fast parallel Boolean calculations in this paper. Hundreds of processor cores of the GPU offer a significant potential for improvements. Constraints in their application may restrict the reachable speedup. This paper summarizes […]

This paper focuses on evaluating the performance impact of different data layouts on the GPU-accelerated IDW interpolation. First, we redesign and improve our previous GPU implementation that was performed by exploiting the feature CUDA Dynamic Parallel (CDP). And then, we implement three versions of GPU implementations, i.e., the naive version, the tiled version, and the […]

This paper presents an efficient computation for least squares conditioning or estimates of it. We propose performance results using new routines on top of the multicore-GPU library MAGMA. This set of routines is based on an efficient computation of the variance-covariance matrix for which, to our knowledge, there is no implementation in current public domain […]

BACKGROUND: Short-read aligners have recently gained a lot of speed by exploiting the massive parallelism of GPU. An uprising alternative to GPU is Intel MIC; supercomputers like Tianhe-2, currently top of TOP500, is built with 48,000 MIC boards to offer ~55 PFLOPS. The CPU-like architecture of MIC allows CPU-based software to be parallelized easily; however, […]

We modified a MPI-friendly density functional theory (DFT) source code within hybrid parallelization including CUDA. Our objective is to find out how simple conversions within the hybrid parallelization with mid-range GPUs affect DFT code not originally suitable to CUDA. We settled several rules of hybrid parallelization for numerical-atomic-orbital (NAO) DFT codes. The test was performed […]

Nondestructive testing (NDT) is a collection of analysis techniques used by scientists and technologists as a way of analyzing the interior of an object without damaging the object. Since the analysis is done without damaging the object, NDT is an extremely valuable technique used in various industries for troubleshooting and research. CNDE has a long […]

Geospatial Processing, such as queries based on point-to-polyline shortest distance and point-in-polygon test, are fundamental to many scientific and engineering applications, such as post-processing large-scale environmental and climate model outputs and analyzing traffic and travel patterns from massive GPS collections in transportation engineering and urban studies. Commodity parallel hardware, such as multi-core CPUs, many-core GPUs […]

This problem was solved within the framework of the grant project "Solving of problems of cluster analysis with application of parallel algorithms and cloud technologies" in the Institute of Mathematics and Mathematical Modelling in Almaty. The problem of cluster analysis for the large amount of data is very important in different areas of science – […]

In this paper we solve on GPUs massive problems with large amount of data, which are not appropriate for solution with the SIMD technology. For the given problem we consider a three-level parallelization. The multithreading of CPU is used at the top level and graphic processors for massive computing. For solving problems of cluster analysis […]