high performance computing on graphics processing units: hgpu.org

We describe different implementations of the 3D Heisenberg spin glass model for Graphics Processing Units (GPU). The results show that the fast shared memory gives better performance with respect to the slow global memory only if a multi-hit technique is used.

In a previous paper we have shown that direct gravitational N-body simulations in astrophysics scale very well for moderately parallel supercomputers (order 10–100 nodes). The best balance between computation and communication is reached if the nodes are accelerated by special purpose hardware; in this paper we describe the implementation of particle based astrophysical simulation codes […]

Modern graphic processing units (GPUs) provide sufficiently flexible programming models that understanding their performance can provide insight in designing tomorrow’s manycore processors, whether those are GPUs or otherwise. The combination of multiple, multithreaded, SIMD cores makes studying these GPUs useful in understanding tradeoffs among memory, data, and thread level parallelism. While modern GPUs offer orders […]

BACKGROUND:Searching for similarities in protein and DNA databases has become a routine procedure in Molecular Biology. The Smith-Waterman algorithm has been available for more than 25 years. It is based on a dynamic programming approach that explores all the possible alignments between two sequences; as a result it returns the optimal local alignment. Unfortunately, the […]

In this paper we report the prototype of the first coalescing binary detection pipeline fully implemented on NVIDIA GPU hardware accelerators. The code has been embedded in a GPU library, called cuInspiral and has been developed under CUDA framework. The library contains for example a PN gravitational wave signal generator, matched filtering/FFT and detection algorithms […]

The matched filter is an important kernel in the processing of hyperspectral data. The filter enables researchers to sift useful data from instruments that span large frequency bands and can produce Gigabytes of data in seconds. In this work, we evaluate the performance of a matched filter algorithm implementation on an FPGA-accelerated co-processor (Cray XD-1), […]

The increase of computational power of programmable GPU (graphics processing unit) brings new concepts for using these devices for generic processing. Hence, with the use of the CPU and the GPU for data processing come new ideas that deals with distribution of tasks among CPU and GPU, such as automatic distribution. The importance of the […]

As a safe and feasible alternative to enriching and enhancing traditional surgical training, virtual-reality-based surgical simulators have been investigated for a long time. But it is still a challenge for researchers to accurately depict the behavior of human tissue without losing the flexibility of simulation. In this paper, we propose an improved scheme of an […]

This paper presents briefly the state of the art of accelerating image processing with graphics hardware (GPU) and discusses some of its caveats. Then it describes GpuCV, an open source multi-platform library for GPU-accelerated image processing and Computer Vision operators and applications. It is meant for computer vision scientist not familiar with GPU technologies. GpuCV […]

To meet the requirement of computer-aided medical operations, apart from the real-time deformation, it is also necessary in the design to simulate the tissue cutting and suturing in a surgery simulation. In this paper, we present a model on topology change and deformation of soft tissue, referred to as the hybrid condensed finite element model, […]

Recent advances in algorithms and graphics hardware have opened the possibility to render tetrahedral grids at interactive rates on commodity PCs. This paper extends on this work in that it presents a direct volume rendering method for such grids which supports both current and upcoming graphics hardware architectures, large and deformable grids, as well as […]

Neural networks (NNs) have been used in several areas, showing their potential but also their limitations. One of the main limitations is the long time required for the training process; this is not useful in the case of a fast training process being required to respond to changes in the application domain. A possible way […]