high performance computing on graphics processing units: hgpu.org

Recently many studies have been made to map cryptography algorithms onto graphics processors (GPU), and gained great performances. This paper does not focus on the performance of a specific program exploited by using all kinds of optimization methods algorithmically, but the intrinsic reason which lies in GPU architectural features for this performance improvement. Thus we […]

This paper presents a detailed description of an advanced real-time correlation-based stereo algorithm running completely on the graphics processing unit (GPU). This is important since it allows to free up the main processor for other tasks including high-level interpretation of the stereo results. Compared to previous GPU-based stereo implementations our implementation includes some advanced features […]

As a widely used numerical solution for the radiation transport equation (RTE), the discrete ordinates can predict the propagation of photons through biological tissues more accurately relative to the diffusion equation. The discrete ordinates reduce the RTE to a serial of differential equations that can be solved by source iteration (SI). However, the tremendous time […]

Real-time simulation of a biologically realistic spiking neural network is necessary for evaluation of its capacity to interact with real environments. However, the real-time simulation of such a neural network is difficult due to its high computational costs that arise from two factors: (1) vast network size and (2) the complicated dynamics of biologically realistic […]

While the popularity of using high-level programming languages such as MATLAB for scientific and engineering applications continues to grow, its poor performance compared to traditional languages such as Fortran or C continues to impede its deployment in full-scale simulations and data analysis. Additionally, its poor memory performance limits its performance. To ameliorate performance, we have […]

The point-based representation constitutes a recent useful alternative approach for modeling enormous and large 3D polygonal models which contain usually millions of faces. However, and in order to allow the artists and the designers to work with such representation, a new mechanisms of FFD (Free Form Deformation) must be offered and that especially with an […]

Random number generation is a key element of stochastic simulations. It has been widely studied for sequential applications purposes, enabling us to reliably use pseudo-random numbers in this case. Unfortunately, we cannot be so enthusiastic when dealing with parallel stochastic simulations. Many applications still neglect random stream parallelization, leading to potentially biased results. Particular parallel […]

This communication introduces a CUDA-enabled GPU accelerated technique for broadband analysis of arbitrary 3D conducting body-wire radiating/scattering structure. The solution is based on the integral equation discretized by the method of moments (MoM) with the use of RWG-type basis functions. Wide-band data are generated from MoM simulation employing an adaptive frequency sampling of the observed […]

In this paper we show the process of a class of algorithms parallelization which are used in digital signal processing. We present this approach on the instance of the popular LMS algorithm which is used in noise reduction, echo cancelation problems and digital signal processing in general. We propose an approach which uses a GPGPU […]

Two approaches, Virtual Reality Modeling Language (VRML) and graphic library OpenGL, are used for active stereoscopic vision of electromagnetic fields surrounding selected antenna or microwave elements. Input data are generated by analytical relations or acquired by electromagnetic field simulators and visualized in the form of vector fields and field lines by active stereoscopy. In case […]

Graphics processing units (GPUs) continue to take on increasing computational workloads and support interactive rendering that approaches cinematic quality. The architectural drivers for GPUs are programmability, parallelism, bandwidth, and memory characteristics. This article describes how one team approached the design problem.

This paper presents implementations of an FIR adaptive filter with a large number of taps on nVIDIA GeForce graphics processing unit (GPU) and CUDA software development environment. In order to overcome a long access latency for slow off-chip memory access, reduction of memory accesses by re-ordering and vector load/store operations and an increase of the […]