high performance computing on graphics processing units: hgpu.org

Unsteady free-wake solutions of wind turbine flow fields involve computationally intensive interaction calculations, which generally limit the total amount of simulation time or the number of turbines that can be simulated by the method. This problem, however, can be addressed easily using high-level of parallelization. Especially when exploited with a GPU, a Graphics Processing Unit, […]

This paper introduces the development of a new GPU-based database to accelerate data retrieval. The main goal is to explore new ways of handling complex data types and managing data and workloads in massively parallel databases. This paper presents three novel innovations to create an efficient virtual database engine that executes the majority of database […]

The Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) is a general-purpose particle detector and comprises the largest silicon-based tracking system built to date with 75 million individual readout channels. The precise reconstruction of particle tracks from this tremendous amount of input channels is a compute-intensive task. The foreseen LHC beam parameters […]

In this paper CUDA (Compute Unified Device Architecture) programming and OpenMP (Open Multi-Processing) are used for the GPU (Graphics Processing Unit) and CPU (Central Processing Unit) parallel computation of material damage. The material damage is evaluated by a multilevel finite element analysis within material domains reconstructed from a high-resolution micro-focus X-ray computed tomography system. An […]

Sequence alignment is a task that calculates the degree of similarity between two sequences. Given a query sequence, finding a database sequence which is most similar to the query by sequence alignment is the first step in bioinformatics research. The first sequence alignment algorithm was proposed by Needle-man and Wunsch. They got the optimal global […]

Medusa is a parallel graph processing system on graphics processors (GPUs). The core design of Medusa is to enable developers to leverage the massive parallelism and other hardware features of GPUs by writing sequential C/C++ code for a small set of APIs. This simplifies the implementation of parallel graph processing on the GPU. The runtime […]

The demands placed on systems to analyse corpus data increase with input size, and the traditional approaches to processing this data are increasingly having impractical run-times. We show that the use of desktop GPUs presents a significant opportunity to accelerate a number of stages in the normal corpus analysis pipeline. This paper contains our exploratory […]

Geostatistical methods provide a powerful tool to understand the complexity of data arising from Earth sciences. Since the mid 70’s, this numerical approach is widely used to understand the spatial variation of natural phenomena in various domains like Oil and Gas, Mining or Environmental Industries. Considering the huge amount of data available, standard implementations of […]

In this paper, we study application behavior in GPGPUs. We investigate how data type impacts performance in different applications. As we show, expectedly, some applications can take significant advantage of small data types. Such applications benefit from small data types as a result of increasing cache effective capacity, reducing memory pressure, access latency, and memory […]

A recent trend in scientific computing is the increasingly important role of co-processors, originally built to accelerate graphics rendering, and now used for general high-performance computing. The INFN Computing On Knights and Kepler Architectures (COKA) project focuses on assessing the suitability of co-processor boards for scientific computing in a wide range of physics applications, and […]

We present GPU implementations of two fast force calculation methods, based on series expansions of the Poisson equation. One is the Self-Consistent Field (SCF) method, which is a Fourier-like expansion of the density field in some basis set; the other is the Multipole Expansion (MEX) method, which is a Taylor-like expansion of the Green’s function. […]

With the advent of many-core computer architectures such as GPGPUs from NVIDIA and AMD, and more recently Intel’s Xeon Phi, ensuring performance portability of HPC codes is potentially becoming more complex. In this work we have focused on one important application area — structured grid codes — and investigated techniques for ensuring performance portability across […]