high performance computing on graphics processing units: hgpu.org

Significant new challenges are continuously confronting the High Energy Physics (HEP) experiments, in particular the two detectors at the Large Hadron Collider (LHC) at CERN, where nominal conditions deliver proton-proton collisions to the detectors at a rate of 40 MHz. This rate must be significantly reduced to comply with both the performance limitations of the […]

The gap between a supercomputer’s theoretical maximum ("peak") floating-point performance and that actually achieved by applications has grown wider over time. Today, a typical scientific application achieves only 5-20% of any given machine’s peak processing capability, and this gap leaves room for significant improvements in execution times. This problem is most pronounced for modern "accelerator" […]

Continuous integration is the software engineering principle of rapid and automated development and testing. We identify several key points of continuous integration and demonstrate how they relate to the needs of computational science projects by discussing the implementation and relevance of these principles to AMBER, a large and widely used molecular dynamics software package. The […]

This paper reports on the development of an MPI/OpenCL implementation of LU, an application-level benchmark from the NAS Parallel Benchmark Suite. An account of the design decisions addressed during the development of this code is presented, demonstrating the importance of memory arrangement and work-item/work-group distribution strategies when applications are deployed on different device types. The […]

We report on the stability of hypothetical Super-Earths in the habitable zone of known multi-planetary systems. Most of them have not yet been studied in detail concerning the existence of additional low-mass planets. The new N-body code GENGA developed at the UZH allows us to perform numerous N-body simulations in parallel on GPUs. With this […]

Modern computers have graphics cards with much higher theoretical efficiency than conventional CPU. The paper presents application possibilities GPU CUDA acceleration for encryption of data using the new architecture tailored to the 3DES algorithm, characterized by increased security compared to the normal DES. The algorithm used in ECB mode (Electronic Codebook), in which 64-bit data […]

In this study, we widely investigate the problem of string matching in the context of Heterogeneous Parallel Computing. A overview of string matching is made, in which the different forms of string matching problem are distinguished, and the classifications of string matching algorithm are discussed. As an alternative to grep for computational intensive string matching […]

In this paper we study a parallel form of the SOR method for the numerical solution of the Convection Diffusion equation suitable for GPUs using CUDA. To exploit the parallelism offered by GPUs we consider the fine grain parallelism model. This is achieved by considering the local relaxation version of SOR. More specifically, we use […]

Modern GPUs are powerful parallel computing devices. In this report, a quick look at the GPU architecture and programming is provided. Collision detection algorithms are briefly surveyed to provide a good overall picture of the field before examining two GPU based collision detection methods in more detail. The fist method is a parallel implementation of […]

We present a method to accelerate robot localization and mapping by using CUDA (Compute Unified Device Architecture), the general purpose parallel computing platform on NVIDIA GPUs. In robotics, the particle filter-based SLAM (Simultaneous Localization and Mapping) algorithm has many applications, but is computationally intensive. Prior work has used CUDA to accelerate various robot applications, but […]

The parallelism in GPUs offers extremely good performance on a lot of high-performance computing applications. Linear algebra is one of the areas which can benefit from GPU potential. Conjugate Gradient (CG) benchmark is a significant computation in computing applications. It uses conjugate gradient method that offers numerical solutions on specific systems of linear equations. The […]

The objective of this paper is to demonstrate a topology optimization method that can handle multiple constraints. The method relies on the concept of topological sensitivity that captures the first order change in any quantity of interest to a topological change. Specifically, in this paper, the topological sensitivity field for each of constraints is first […]