high performance computing on graphics processing units: hgpu.org

Evaluating multi-dimensional integrals is a commonly encountered problem in many areas of science including Physics and Volume estimation of convex bodies. One of the widely used techniques for integral evaluation in large dimensions is the Monte Carlo method. Vanilla Monte Carlo methods of Integral Estimation use uniform sampling techniques. Variance of such uniform sampling reduces […]

One of the most time-consuming parts of the simulation of underwater networks is the realistic simulation of underwater sound propagation. Some well-known software tools used for networks simulations to date employ ray tracing to simulate sound propagation. This gives rise to high computational complexity, and may require very long time to complete a simulation. In […]

Monte Carlo (MC) method is able to accurately calculate eigenvalues in reactor analysis. Its lengthy computation time can be reduced by general-purpose computing on Graphics Processing Units (GPU), one of the latest parallel computing techniques under development. The method of porting a regular transport code to GPU is usually very straightforward due to the "embarrassingly […]

Data layout, data placement, and synchronization processes are not usually part of a speech application expert’s daily concerns. Yet failure to carefully take these concerns into account in a highly parallel implementation on the graphics processing units (GPUs) could mean an order of magnitude of loss in application performance. In this paper we present an […]

This paper presents a parallel implementation and performance analysis of a system for traffic sign recognition with digital map fusion on emerging multicore processors and graphics processing units (GPU). The system employs a particle filter based localization and map matching and template-based matching for sign recognition. In the proposed system, a GPS, odometer and camera […]

The accuracy on time delay estimation given pairs of irregularly sampled time series is of great relevance in astrophysics. However the computational time is also important because the study of large data sets is needed. Besides introducing a new approach for time delay estimation, this paper presents a parallel approach to obtain a fast algorithm […]

In this paper we explore mapping of a high-level macro data-flow programming model called Concurrent Collections (CnC) onto heterogeneous platforms in order to achieve high performance and low energy consumption while preserving the ease of use of data-flow programming. Modern computing platforms are becoming increasingly heterogeneous in order to improve energy efficiency. This trend is […]

This paper shows the potential of heterogeneous computing in solving dynamic equilibrium models in economics. We illustrate the power and simplicity of the C++ Accelerated Massive Parallelism recently introduced by Microsoft. Starting from the same exercise as Aldrich et al. (2011) we document a speed gain together with a simplified programming style that naturally enables […]

The Fast Multipole Method (FMM) allows O(N) evaluation to any arbitrary precision of N-body interactions that arises in many scientific contexts. These methods have been parallelized, with a recent set of papers attempting to parallelize them on heterogeneous CPU/GPU architectures [1]. While impressive performance was reported, the algorithms did not demonstrate complete weak or strong […]

Most of today’s cryptographic primitives are based on computations that are hard to perform for a potential attacker but easy to perform for somebody who is in possession of some secret information, the key, that opens a back door in these hard computations and allows them to be solved in a small amount of time. […]

BACKGROUND: Calculating the electrostatic surface potential (ESP) of a biomolecule is critical towards understanding biomolecular function. Because of its quadratic computational complexity (as a function of the number of atoms in a molecule), there have been continual efforts to reduce its complexity either by improving the algorithm or the underlying hardware on which the calculations […]

In this paper we identify important classes of program control flows in applications targeted to commercially available graphics processing units (GPUs) and characterize their presence in real workloads such as those that occur in CUDA and OpenCL. Broadly, control flow can be characterized as structured or unstructured. It is shown that most existing techniques for […]