high performance computing on graphics processing units: hgpu.org

In computer graphics, human hair simulation represents a challenging issue, and is still an active research subject nowadays. The problem comprises two complementary dimensions: the physical simulation and the rendering. While both aspects must be treated individually for each strand, they must also be treated globally due to interactions between hair strands. Because of the […]

The paper presents the implementation of a parallel version of FDK (Felkamp, David e Kress) algorithm using graphics processing units. Discussion was briefly some elements the computed tomographic scan and FDK algorithm; and some ideas about GPUs (Graphics Processing Units) and its use in general purpose computing were presented. The paper shows a computational implementation […]

Lung cancer is one of the deadliest and most common types of cancer in Norway. Early and precise diagnosis is crucial for improving the survivalrate. Diagnosis is often done by extracting a tissue sample in the lung throughthe mouth and throat. It is difficult to navigate to the tissue because of thecomplexity of the airways […]

The utilization of Graphical Processing Units (GPUs) for the element-by-element (EbE) finite element method (FEM) is demonstrated. EbE FEM is a long known technique, by which a conjugate gradient (CG) type iterative solution scheme can be entirely decomposed into computations on the element level, i.e., without assembling the global system matrix. In our implementation, NVIDIA’s […]

The lattice Boltzmann method has become a valuable tool in computational fluid dynamics, one of the reasons is due to the simplicity of its coding. In order to maximize the performance potential of today’s computers, code has to be optimized for parallel execution. In order to achieve parallel execution of the lattice Boltzmann method, the […]

We present a general method for accelerating by more than an order of magnitude the convolution of pixelated function on the sphere with a radially-symmetric kernel. Our method splits the kernel into a compact real-space, and a compact spherical harmonic space component that can then be convolved in parallel using an inexpensive commodity GPU and […]

Recent developments in graphics processing unit (GPU) technology has invigorated an interest in using GPUs for accelerating the simulation of SystemC models. SystemC is extensively used for design space exploration, and early performance analysis of hardware systems. SystemC’s reference implementation of the simulation kernel supports a single-threaded simulation kernel. However, modern computing platforms offer substantially […]

B+ tree structured index searches are one of the fundamental database operations and hence, accelerating them is essential. GPUs provide a compelling mix of performance per watt and performance per dollar, and thus are an attractive platform for accelerating B+ tree searches. However, tree search on discrete GPUs presents significant challenges for acceleration due to […]

This work presents parallel implementations of the MinMin scheduling heuristic for heterogeneous computing using Graphic Processing Units, in order to improve its computational efficiency. The experimental evaluation of the four proposed MinMin variants demonstrates that a significant reduction on the computing times can be attained, allowing to tackle large scheduling scenarios in reasonable execution times.

As a major breakthrough, in 2009 Gentry introduced the first plausible construction of a fully homomorphic encryption (FHE) scheme. FHE allows the evaluation of arbitrary functions directly on encrypted data on untwisted servers. In 2010, Gentry and Halevi presented the first FHE implementation on an IBM x3500 server. However, this implementation remains impractical due to […]

The training phase of the Continuous Space Language Model (CSLM) was implemented in the NVIDIA hardware/software architecture Compute Unified Device Architecture (CUDA). Implementation was accomplished using a combination of CUBLAS library routines and CUDA kernel calls on three different CUDA enabled devices of varying compute capability and a time savings over the traditional CPU approach […]

Biomedical image reconstruction applications with large datasets can benefit from acceleration. Graphic Processing Units(GPUs) are particularly useful in this context as they can produce high fidelity images rapidly. An image algorithm to reconstruct conebeam computed tomography(CT) using two dimensional projections is implemented using GPUs. The implementation takes slices of the target, weighs the projection data […]