high performance computing on graphics processing units: hgpu.org

We present preliminary results of the acceleration of the three-dimensional (3D) alternating direction implicit finite-difference time-domain (ADI-FDTD) method on graphics processor units (GPUs). Although the ADI-FDTD iteration comprises two substeps, which each require solving a tridiagonal matrix system of equations over xy, xz, yz planes of the domain, the application of this scheme frees the […]

One important bottleneck when visualizing large data sets is the data transfer between processor and memory. Cacheaware (CA) and cache-oblivious (CO) algorithms take into consideration the memory hierarchy to design cache efficient algorithms. CO approaches have the advantage to adapt to unknown and varying memory hierarchies. Recent CA and CO algorithms developed for 3D mesh […]

The modeling of the electrical activity of the heart is of great medical and scientific interest, as it provides a way to get a better understanding of the related biophysical phenomena, allows the development of new techniques for diagnoses and serves as a platform for drug tests. However, due to the multi-scale nature of the […]

The main objective of this paper is to speed up the simulation performance of SystemC designs at the RTL abstraction level by exploiting the high degree of parallelism afforded by today’s general purpose graphics processors (GPGPUs). Our approach parallelizes SystemC’s discrete-event simulation (DES) on GPGPUs by transforming the model of computation of DES into a […]

With the advances in the processor technology, todaypsilas graphical processing unit (GPU) architectures have evolved tremendously. Their speed and computational power has increased to the giga-flops levels. This has brought about a new architectural innovation called Shaders, which are programmable processing units that make all of the resources of the GPUs available to the game […]

In this work I present the parallel implementation of a spiking neuronal network model with biologically realistic morphology, elements, and function on a graphical processing unit (GPU) using the NVidia CUDA framework. The comparison to a well-designed C/C++ implementation of the same model reveals a 24x speedup when using an NVidia Tesla C870 device for […]

To move High-Performance Computing (HPC) closer to forward operating environments and missions, the Army Research Laboratory is developing approaches using hybrid, asymmetric core computing. By blending capabilities found in Graphics Processing Units (GPUs) and traditional von Neumann multicore Central Processing Units (CPUs), approaches are being developed and optimized to provide at or near real-time processing […]

With recent advances in the measurement technology for allsky astrophysical imaging, our view of the sky is no longer limited to the tiny visible spectral range over the 2D Celestial sphere. We now can access a third dimension corresponding to a broad electromagnetic spectrum with a wide range of allsky surveys; these surveys span frequency […]

In this paper, we present a method to speed up video encoding of GPU rendered 3D scenes, which is particularly suited for the efficient and low-delay encoding of 3D game output as a video stream. The main idea of our approach is to calculate motion vectors directly from the 3D scene information used during rendering […]

This paper presented a high performance method for remote sensing image processing using CUDA-based GPU. And it introduced the process of several common algorithms in remote sensing image processing. Experiments were carried out and results showed that the computing speed of GPU was much faster than that of CPU.

The NTRU encryption algorithm, also known as NTRUEncrypt, is a parameterized family of lattice-based public key cryptosystems that has been accepted to the IEEE P1363 standards under the specifications for lattice-based public-key cryptography (IEEE P1363.1). The operations of the NTRU encryption algorithm show good characteristics for data parallel processing which makes the NTRU a good […]

GPUs are becoming an increasingly attractive option for obtaining performance speedups for data-parallel applications. FPGA technology mapping is an algorithm that is heavily data parallel; however, it has many features that make it unattractive to implement on a GPU. The algorithm uses data in irregular ways since it is a graph-based algorithm. In addition, it […]