high performance computing on graphics processing units: hgpu.org

Graphics processor units (GPUs) offer high performance and power efficiency for a large number of data-parallel applications. Previous research has shown that a GPU-based version of a neuromorphic motion estimation algorithm can achieve a x32 speedup using these devices. However, the memory consumption creates a bottleneck due to the expansive tree of signal processing operations […]

Computer-aided modeling and simulation is a crucial step in developing, integrating and optimizing unit operations and subsequently entire processes, in the chemical/pharmaceutical industry. This study details two methods of reducing the computational time to solve complex process models, namely the population balance model which given the source terms can be very computationally intensive. Population balance […]

The presented contribution maps the possibilities of exploitation of the massive parallel computational hardware (namely GPU) for solution of the initial value problems of ordinary differential equations. Two cases are discussed: parallel solution of a single ODE and parallel execution of scalar ODE solvers. Whereas the advantages of the special architecture in the case of […]

This paper proposes an efficient parallel shooting and bouncing ray (SBR) method on the graphics processing unit (GPU) cluster for solving the electromagnetic scattering problems. At each incident direction, the parallel SBR method partitions the virtual aperture into sub-apertures, and distributes the computational process of each sub-aperture over GPU nodes. As ray tubes in the […]

This research explores the benefits of using commonly-available graphics processing units (GPUs) to perform classification of network traffic using supervised machine learning algorithms. Two full factorial experiments are conducted using a NVIDIA GeForce GTX 280 graphics card. The goal of the first experiment is to create a baseline for the relative performance of the CPU […]

Integration of GPUs in a Cloud Computing environment is an emerging research area. The GPUs are used to perform processing extremely exigent in terms of power computation and the Cloud computing has the potential to become a major tool for scientists and engineers to access high performance resource and storage. The proposed work has been […]

Increasing need for high quality video communication and video streaming, and tremendous growth of video content on Internet stimulated development of highly efficient compression methods. H.264/AVC is the newest international video coding standard, which achieves compression gain of about 50% comparing the previous standards, keeping the same quality of reconstructed video [1]. However, such compression […]

To tackle the exponentially increasing throughput of Next-Generation Sequencing (NGS), most of the existing short-read aligners can be configured to favor speed in trade of accuracy and sensitivity. SOAP3-dp, through leveraging the computational power of both CPU and GPU with optimized algorithms, delivers high speed and sensitivity simultaneously. Compared with widely adopted aligners including BWA, […]

The current powerful graphics cards, providing stunning real-time visual effects for computer-based entertainment, have to accommodate powerful hardware components that are able to deliver the photo-realistic simulation to the end-user. Given the vast computing power of the graphics hardware, its producers very often offer a programming interface that makes it possible to use the computational […]

As graphics processing units (GPUs) are becoming increasingly popular for general purpose workloads (GPGPU), the question arises how such processors will evolve architecturally in the near future. In this work, we identify and discuss tradeoffs for three GPU architecture parameters: active thread count, compute-memory ratio, and cluster and warp sizing. For each parameter, we propose […]

Stochastic simulation techniques employed for portfolio risk analysis, often referred to as Aggregate Risk Analysis, can benefit from exploiting state-of-the-art highperformance computing platforms. In this paper, we propose parallel methods to speedup aggregate risk analysis for supporting real-time pricing. To achieve this an algorithm for analysing aggregate risk is proposed and implemented in C and […]

In recent studies, phase changing memory (PCM) has shown promising energy efficiency for systems with a modest level of parallelism. But it remains an open question whether it can benefit GPU-like massively parallel systems. This work conducts the first systematic investigation into this question. It empirically shows that contrary to the promising results shown before […]