high performance computing on graphics processing units: hgpu.org

Recently, we have witnessed that cloud providers start to offer heterogeneous computing environments. There have been wide interests in both cluster and cloud of adopting graphics processors (GPUs) as accelerators for various applications. On the other hand, large-scale processing is important for many data-intensive applications in the cloud. In this paper, we propose to leverage […]

Datalog is a language based on first order logic that was investigated as a data model for relational databases in the 1980s. It has recently been used in various new application areas, prompting proposals to run Datalog programs on new platforms such as Graphics Processing Units (GPUs) and MapReduce. Back then and nowadays, interest in […]

To interpret fiber-based and camera-based measurements of remitted light from biological tissues, researchers typically use analytical models, such as the diffusion approximation to light transport theory, or stochastic models, such as Monte Carlo modeling. To achieve rapid (ideally real-time) measurement of tissue optical properties, especially in clinical situations, there is a critical need to accelerate […]

This paper describes the first implementation of Andersen’s inclusion-based pointer analysis for C programs on a heterogeneous CPU-GPU system, where both its CPU and GPU cores are used. As an important graph algorithm, Andersen’s analysis is difficult to parallelise because it makes extensive modifications to the structure of the underlying graph, in a way that […]

N-Body simulation algorithms are amongst the most commonly used within the field of scientific computing. Especially in computational astrophysics, they are used to simulate gravitational scenarios for solar systems or galactic collisions. Parallel versions of such N-Body algorithms have been extensively designed and optimized for multicore and distributed computing schemes. However, N-Body algorithms are still […]

Image registration is wildly used in the biomedical image, but there are too many textures and noises in the biomedical image to get a precise image registration. In order to get the excellent registration performance, it needs more complex image processing, and it will spend expensive computation cost. For the real time issue, this paper […]

For software to fully exploit the computing power of emerging heterogeneous computers, not only must the required computational kernels be optimized for the specific hardware architectures but also an effective scheduling scheme is needed to utilize the available heterogeneous computational units and to hide the communication between them. As a case study, we develop a […]

We consider a GPU accelerated program using Monte Carlo simulation to price a basket call option on 10 FX rates driven by a 10 factor local volatility model. We develop an adjoint version of this program using algorithmic differentiation. The code uses mixed precision. For our test problem of 10,000 sample paths with 360 Euler […]

A high performance terrain data compression method is proposed based on discrete wavelet transform (DWT) and parallel run-length code. But the implementation of the schemes to solve these models in realistic scenarios imposes huge demands of computing power. Compute Unified Device Architecture (CUDA) programmed, Graphic Processing Units (GPUs) are rapidly becoming a major choice in […]

GPU parallelism for real applications can achieve enormous performance gain. CPU-GPU Communication is one of the major bottlenecks that limit this performance gain. Among several libraries developed so far to optimize this communication, DyManD (Dynamically Managed Data) provides better communication optimization strategies and achieves better performance on a single GPU. Smith-Waterman is a well known […]

We propose a numerical implementation based on a Graphics Processing Unit (GPU) for the acceleration of the execution time of the Lattice Boltzmann Method (LBM). The study focuses on the application of the LBM for patient-specific blood flow computations, and hence, to obtain higher accuracy, double precision computations are employed. The LBM specific operations are […]

In recent years, with the development of graphics processors, graphics cards have been widely used to perform general-purpose calculations. Especially with release of CUDA C programming languages in 2007, most of the researchers have been used CUDA C programming language for the processes which needs high performance computing. In this paper, a scaling approach for […]