high performance computing on graphics processing units: hgpu.org

Optical measurements based on laser light scattering by nanostructures provide fast and contactless measurement of the surface of nanostructures for defects. In this paper, a novel in-process measurement method based on coherent laser light scattering by sub-100-nm structures is presented. It is shown that nanostructure defects can be identified by their unique scattering pattern. This […]

In this paper, we present an efficient diagnostic fault simulator based on a state-of-the-art graphics processing unit (GPU). Diagnostic fault simulation plays an important role to identify and locate the causes of circuit failures. However, today’s complex VLSI circuits pose ever higher computational demand for such simulators. Our GPU based diagnostic fault simulator (GDSim) is […]

Today, the multi-core processor has occupied more and more market shares, and the programming personnel also must face the collision brought by the revolution of multi-core processor. Semiconductor scaling limits and associated power and thermal challenges limit performance growth for single-core microprocessors. This reason leads many microprocessor vendors to turn instead to multi-core chip organizations. […]

Recently GPU computing, namely the possibility to use the vector processors of graphics card as computational general purpose units of High Performance Computing environments, has generated considerable interest in the scientific community. Some communities in European Grid Infrastructure (EGI) are reshaping their applications to exploit this new programming paradigm. Each EGI community, called Virtual Organization […]

Benefit from the OpenCL (Open Computing Language), applications can be easily transplanted among different GPUs, multi-core CPUs, and other processors. In this paper, we present implementation of AES finalists (Rijndael, Serpent, Twofish) in XTS mode, based on OpenCL. Benchmark testing is performed on 4 mainstream GPUs and multi-core CPUs. The results are also compared with […]

Parallelization is an effective way to reduce the computational time needed for molecular dynamics simulations. We describe a new parallelization method, the distributed-diagonal force decomposition method, with which we extend and improve the existing force decomposition methods. Our new method requires less data communication during molecular dynamics simulations than replicated data and current force decomposition […]

This thesis explores the possibility of mapping power flow algorithms on a graphics processor. In particular we demonstrate the implementation of DC power flow based contingency analysis on a graphic processing unit (GPU). GPU’s are SIMD processors with highly streamlined architecture to support rendering of graphic images on the computer screen. However, in the recent […]

Graphic processing units (GPUs) are single instruction, multiple data processors which have become an integral part of modern high-end video cards installed on a general purpose PCs. This paper investigates the parallel implementation of DC power flow based contingency analysis on graphic processing units. Results for the IEEE standard test systems show a speed-up of […]

A Helmholtz equation in two dimensions discretized by a second order finite difference scheme is considered. Krylov methods such as Bi-CGSTAB and IDR(s) have been chosen as solvers. Since the convergence of the Krylov solvers deteriorates with increasing wave number, a shifted Laplacian multigrid preconditioner is used to improve the convergence. The implementation of the […]

We present results of molecular dynamics simulations of fully hydrated DMPC bilayers performed on graphics processing units (GPUs) using current state-of-the-art non-polarizable force fields and a local GPU-enabled molecular dynamics code named FEN ZI. We treat the conditionally convergent electrostatic interaction energy exactly using the particle mesh Ewald method (PME) for solution of Poisson’s Equation […]

During the last decades, explicit finite element approximate inverse preconditioning methods have been extensively used for efficiently solving sparse linear systems on multiprocessor systems. The effectiveness of explicit approximate inverse preconditioning schemes relies on the use of efficient preconditioners that are close approximants to the coefficient matrix and are fast to compute in parallel. New […]

Metaheuristics are used for solving optimization problems since they are able to compute near optimal solutions in reasonable times. However, solving large instances it may pose a challenge even for these techniques. For this reason, metaheuristics parallelization is an interesting alternative in order to decrease the execution time and to provide a different search pattern. […]