high performance computing on graphics processing units: hgpu.org

We present a scalable spatial decomposition coloring approach to implement molecular dynamics simulations with embedded atom method (EAM) on multi-core architectures. It effectively solves parallelization of reduction operations on irregular arrays in molecular dynamics simulations. In OpenMP program model, our methodology avoids that the same memory location is simultaneously modified by more than one thread […]

We report a GPU implementation in HOOMD Blue of long-range electrostatic interactions based on the orientation-averaged Ewald sum scheme, introduced by Yakub and Ronchi (J. Chem. Phys. 2003, 119, 11556). The performance of the method is compared to an optimized CPU version of the traditional Ewald sum available in LAMMPS, in the molecular dynamics of […]

We present a new method for decomposing the one convolution required by standard Particle-Particle Particle-Mesh (P3M) electrostatic methods into a series of convolutions over slab-shaped subregions of the original simulation cell. Most of the convolutions derive data from separate regions of the cell and can thus be computed independently via FFTs, in some cases with […]

The scaling of serial algorithms cannot rely on the improvement of CPUs anymore. The performance of classical Support Vector Machine (SVM) implementations has reached its limit and the arrival of the multi core era requires these algorithms to adapt to a new parallel scenario. Graphics Processing Units (GPU) have arisen as high performance platforms to […]

Electrostatic potentials (ESPs) are frequently used in structural biology for the characterization of biomolecules. Here we study the potential employment of hardware accelerators like the graphics processing unit or the application-specific integrated circuit MD-GRAPE-3 for the purpose of efficient computation of ESPs. An algorithm closely coupled to the general description of molecular surfaces is ported […]

Recent advances in graphics processing units (GPUs) technology open a new era in high performance computing. Applications of GPUs to scientific computations are attracting a lot of attention due to their low cost in conjunction with their inherently remarkable performance features and the recently enhanced computational precision and improved programming tools. Domain decomposition methods (DDM) […]

This paper proposes novel methods for visualizing specifically the large power-law graphs that arise in sociology and the sciences. In such cases a large portion of edges can be shown to be less important and removed while preserving component connectedness and other features (e.g. cliques) to more clearly reveal the networkpsilas underlying connection pathways. This […]

A novel technique that uses the Moving Least Squares (MLS) method to interpolate sparse constraints over mesh surfaces is introduced in this paper. Given a set of constraints, the proposed technique constructs, directly on the surface, a smooth scalar field that interpolates or approximates the constraints. Three types of constraints: point-value, point-gradient and iso-contour, are […]

We present an extension to the CUDA programming language which extends parallelism to multi-GPU systems and GPU-cluster environments. Following the existing model, which exposes the internal parallelism of GPUs, our extended programming language provides a consistent development interface for additional, higher levels of parallel abstraction from the bus and network interconnects. The newly introduced layers […]

Regularization is a common technique used to improve image quality in inverse problems such as MR image reconstruction. In this work, we extend our previous Graphics Processing Unit (GPU) implementation of MR image reconstruction with compensation for susceptibility-induced field inhomogeneity effects by incorporating an additional quadratic regularization term. Regularization techniques commonly impose the prior information […]

Reduction is a common component of many applications, but can often be the limiting factor for parallelization. Previous reduction work has focused on detecting reduction idioms and parallelizing the reduction operation by minimizing data communications or exploiting more data locality. While these techniques can be useful, they are mostly limited to simple code structures. In […]

Many advanced MRI image acquisition and reconstruction methods see limited application due to high computational cost in MRI. For instance, iterative reconstruction algorithms (e.g. non-Cartesian k-space trajectory, or magnetic field inhomogeneity compensation) can improve image quality but suffer from low reconstruction speed. General-purpose computing on graphics processing units (GPU) have demonstrated significant performance speedups and […]