high performance computing on graphics processing units: hgpu.org

We present practical algorithms for accelerating geometric queries on models made of NURBS surfaces using programmable Graphics Processing Units (GPUs). We provide a generalized framework for using GPUs as co-processors in accelerating CAD operations. By attaching the data corresponding to surface-normals to a surface bounding-box structure, we can calculate view-dependent geometric features such as silhouette […]

Today, it is possible to associate multiple CPUs and multiple GPUs in a single shared memory architecture. Using these resources efficiently in a seamless way is a challenging issue. In this paper, we propose a parallelization scheme for dynamically balancing work load between multiple CPUs and GPUs. Most tasks have a CPU and GPU implementation, […]

With the term super-resolution we refer to the problem of reconstructing an image of higher resolution than that of unregistered and degraded observations. Typically, the reconstruction is based on the inversion of the observation generation model. In this paper this problem is formulated using a variational Bayesian inference framework and an edge-preserving image prior. A […]

Modern GPUs are massively parallel microprocessors that can deliver very high performance for the parallel computations common in science and engineering.

The OpenCL standard offers a common API for program execution on systems composed of different types of computational devices such as multicore CPUs, GPUs, or other accelerators.

Computational neuroscience is being revolutionized with the advent of multi-electrode arrays that provide real-time, dynamic, perspectives into brain function. Mining event streams from these chips is critical to understanding the firing patterns of neurons and to gaining insight into the underlying cellular activity. We present a GPGPU solution to mining spike trains. We focus on […]

This paper presents two conceptually simple methods for parallelizing a Parallel Tempering Monte Carlo simulation in a distributed volunteer computing context, where computers belonging to the general public are used. The first method uses conventional multi-threading. The second method uses CUDA, a graphics card computing system. Parallel Tempering is described, and challenges such as parallel […]

The temperature induced phase transition is investigated in the one-component scalar field phi^4 model on a lattice by using Monte Carlo simulations. Due to GPGPU technology used a huge amount of data is generated and treated that gives a possibility to determine the Linde-Weinberg low bound on the coupling constant lambda_0 and investigate the type […]

We present an implementation of the disconnected diagram contributions to quantities such as the flavor-singlet pseudoscalar meson mass which are accelerated by GPGPU technology utilizing the NVIDIA CUDA platform. To enable the exact evaluation of the disconnected loops we use a $16^3 times 32$ lattice and $N_f=2$ Wilson fermions simulated by the SESAM Collaboration. The […]

In the last few years, GPUs have become new, promising targets for general purpose programming. Their inherent parallel architecture makes them particularly suited for scientific numerical computations with high arithmetical density. There have been several proposals to exploit the computational power of GPUs for data-parallel algorithms. These approaches vary greatly in the abstraction level of […]

Automated code generation and performance tuning techniques for concurrent architectures such as GPUs, Cell and FPGAs can provide integer factor speedups over multi-core processor organizations for data-parallel, floating-point computation in SPICE model-evaluation. Our Verilog AMS compiler produces code for parallel evaluation of non-linear circuit models suitable for use in SPICE simulations where the same model […]

We present a parallel conjugate gradient solver for the Poisson problem optimized for multi-GPU platforms. Our approach includes a novel heuristic Poisson preconditioner well suited for massively-parallel SIMD processing. Furthermore, we address the problem of limited transfer rates over typical data channels such as the PCI-express bus relative to the bandwidth requirements of powerful GPUs. […]