high performance computing on graphics processing units: hgpu.org

The use of GPUs for general-purpose applications promises huge performance returns for a small investment. However the internal design of such processors is undocumented and many details are unknown, preventing developers to optimize their code for these architectures. One solution is to use functional simulation to determine program behavior and gather statistics when counters are […]

Modern graphics processing units (GPUs) with many-core architectures have emerged as general-purpose parallel computing platforms that can accelerate simulation science applications tremendously. While multiGPU workstations with several TeraFLOPS of peak computing power are available to accelerate computational problems, larger problems require even more resources. Conventional clusters of central processing units (CPU) are now being augmented […]

This paper presents a GPU-based method for interactive global illumination that integrates complex effects such as multi-bounce indirect lighting, glossy reflections, caustics, and arbitrary specular paths. Our method builds upon scattered data sampling and interpolation on the GPU. We start with raytraced shading points and partition them into coherent shading clusters using adaptive seeding followed […]

Distant astrophysical objects like planetary nebulae can normally only be observed from a single point of view. Assuming a cylindrically symmetric geometry, one can nevertheless create 3D models of those objects using tomographic methods. We solve the resulting algebraic equations efficiently on graphics hardware. Small deviations from axial symmetry are then corrected using heuristic methods, […]

Building on the trend of offloading more tasks from the CPU to the GPU to take advantage of the GPU’s steeper performance curve, we propose a new method to simulate cloth on any GPU supporting Shader Model 3. Our implementation is geared toward performance and visual realism, rather than physical accuracy. As such, it’s more […]

Scientific computing applications demand ever-increasing performance while traditional microprocessor architectures face limits. Recent technological advances have led to a number of emerging computing platforms that provide one or more of the following over their predecessors: increased energy efficiency, programmability/flexibility, different granularities of parallelism, and higher numerical precision support. This dissertation explores emerging platforms such as […]

Many computational protein modeling applications using numerical methods such as Molecular Dynamics (MD), Monte Carlo (MC), or Genetic Algorithms (GA) require a large number of energy estimations of the protein molecular system. A typical energy function describing the protein energy is a combination of a number of terms characterizing various interactions within the protein molecule […]

The widespread availability of parallel computing architectures has lead to research regarding algorithms and techniques that best exploit available parallelism. In addition to the CPU parallelism available; the GPU has emerged as a parallel computational device. The goal of this study was to explore the combined use of CPU and GPU parallelism by developing a […]

In the past, graphics processors were special-purpose hardwired application accelerators, suitable only for conventional graphics applications. Modern GPUs are fully programmable, massively parallel floating point processors. In this talk I will describe NVIDIA’s scalable, highly parallel many-core GPU architecture and how CUDA software for GPU computing delivers high throughput for data-intensive processing. I will discuss […]

The performance and the level of programmability of graphics processors (GPU) on current video cards offer new capabilities beyond the graphics applications for which they were designed. These are general-purpose computations which expose parallelism. In this thesis, I describe the iterative methods for solving sparse linear systems: the Jacobi, Gauss-Seidel, Conjugate Gradient and BiConjugate Gradient […]

User needs increases as time passes. We started with computers like the size of a room where the perforated plaques did the same function as the current machine code object does and at present we are at a point where the number of processors within our graphic device unit it’s not enough for our requirements. […]

Perhaps the most important innovation of the latest generation of programmable graphics processors (GPUs) is their capability to work with floating point color data. Previous generations of GPUs have worked with up to a byte of integer data per color channel. Developers working on graphics engines with advanced lighting effects often complained about banding artifacts, […]