high performance computing on graphics processing units: hgpu.org

In this article, we look at early, recent, and state-of-the-art methods for registration of medical images using a range of high-performance computing (HPC) architectures including symmetric multiprocessing (SMP), massively multiprocessing (MMP), and architectures with distributed memory (DM), and nonuniform memory access (NUMA). The article is designed to be self-sufficient. We will take the time to […]

A very efficient implementation of a lattice Boltzmann (LB) kernel in 3D on a graphical processing unit using the compute unified device architecture interface developed by nVIDIA is presented. By exploiting the explicit parallelism offered by the graphics hardware, we obtain an efficiency gain of up to two orders of magnitude with respect to the […]

In-memory tree structured index search is a fundamental database operation. Modern processors provide tremendous computing power by integrating multiple cores, each with wide vector units. There has been much work to exploit modern processor architectures for database primitives like scan, sort, join and aggregation. However, unlike other primitives, tree search presents significant challenges due to […]

Is CUDA the parallel programming model that application developers have been waiting for?

A large number of algorithms have been developed to perform non-rigid registration and it is a tool commonly used in medical image analysis. The free-form deformation algorithm is a well-established technique, but is extremely time consuming. In this paper we present a parallel-friendly formulation of the algorithm suitable for graphics processing unit execution. Using our […]

Real-time graphics applications require memory organizations featuring parallel pixel access and low-cost implementation. This work bases on a nonlinear skew mapping scheme and exploits the correlation between consecutive requests for pixels to design an efficient parallel memory organization. The mapping achieves parallel access, of mn pixels in various shapes, to the memory organized with mn […]

BACKGROUND:Many analyses of microarray association studies involve permutation and bootstrap resampling, and cross-validation, that are ideally formulated as embarrassingly parallel computing problems. Given that these analyses are computationally intensive, scalable approaches that can take advantage of multi-core processor systems need to be developed. RESULTS:We have developed a CUDA based implementation, permGPU, that employs graphics processing […]

In this paper, we propose an acceleration of collapsed variational Bayesian (CVB) inference for latent Dirichlet allocation (LDA) by using Nvidia CUDA compatible devices. While LDA is an efficient Bayesian multi-topic document model, it requires complicated computations for parameter estimation in comparison with other simpler document models, e.g. probabilistic latent semantic indexing, etc. Therefore, we […]

PURPOSE: To accelerate the simultaneous algebraic reconstruction technique (SART) with motion compensation for speedy and quality computed tomography reconstruction by exploiting CUDA-enabled GPU. METHODS: Two core techniques are proposed to fit SART into the CUDA architecture: (1) a ray-driven projection along with hardware trilinear interpolation, and (2) a voxel-driven back-projection that can avoid redundant computation […]

In recent years, it can be observed that there is a gradual increase in the number of researchers and projects involved with the development of omnidirectional vision systems for various applications. The primary factors, which contributed towards this positive trend, are the availability of inexpensive and high resolution vision sensors, robust and fast computers and […]

We developed a GPU-based analytical method, named as SHEsisEpi, which purely focuses on risk epistasis in a genome-wide association study (GWAS) of complex traits, excluding the contamination of marginal effects caused by single-locus association. We analyzed the Wellcome Trust Case Control Consortium’s (WTCCC) GWAS data of bipolar disorder (BPD) with 500K SNPs.

The robust alignment of tilt-series collected for cryo-electron tomography in the absence of fiducial markers, is a problem that, especially for tilt-series of vitreous sections, still represents a significant challenge. Here we present a complete software package that implements a cross-correlation based procedure that tracks similar image features that are present in several micrographs and […]