high performance computing on graphics processing units: hgpu.org

We present a method for real-time clustering of VPLs obtained from Reflective Shadow Maps (RSM). The clusters are treated as area light sources and used to approximate indirect illumination. The spatial extent of a cluster is used to deduce the shape and size of the respective area light source. Our method is fully GPU-based and […]

Agglomerative clustering is an effective greedy way to quickly generate graph clusterings of high modularity in a small amount of time. In an effort to use the power offered by multi-core CPU and GPU hardware to solve the clustering problem, we introduce a fine-grained sharedmemory parallel graph coarsening algorithm and use this to implement a […]

Architectures in which multicore chips are augmented with graphics processing units (GPUs) have great potential in many domains in which computationally intensive real-time workloads must be supported. However, unlike standard CPUs, GPUs are treated as I/O devices and require the use of interrupts to facilitate communication with CPUs. Given their disruptive nature, interrupts must be […]

Most data for environmental variables (e. g. meteorological variables, soil properties etc.) are collected from point sources. For modeling and visualization purposes, the data is often needed to be available on a regular grid, which requires spatial interpolation of the scattered point measurements. A variety of interpolation methods for these purposes is available, examples are […]

Massively parallel Graphics Processing Unit (GPU) hardware has become increasingly powerful, available and affordable. Software tools have also advanced to the point that programmers can write general purpose parallel programs that take advantage of the large number of compute cores available in the hardware. With literally hundreds of compute cores available on a single device, […]

Information-theoretic measures are frequently employed to assess the degree of feature interactions when mining attribute-value data sets. For large data sets, obtaining these measures quickly poses an unmanageable computational burden. In this work we examine the applicability of consumer graphics processing units supporting CUDA architecture to speed-up the computation of information-theoretic measures. Our implementation was […]

We present an approach to tracking multiple human subjects within a camera network. A particle filter framework is used in which we combine foreground-background subtraction with a novel approach to texture learning and likelihood computation based on an ellipsoid model. As there are inevitable problems with multiple subjects due to occlusion and crossing, we include […]

Variants of the 0-1 knapsack problem manifest themselves at the core of several system-level optimization problems. The running times of such system-level optimization techniques are adversely affected because the knapsack problem is NP-hard. In this paper, we propose a new GPU-based approach to accelerate the multiple-choice knapsack problem, which is a general version of the […]

Scheduling problems exist everywhere in the so-called "real world". They are there in manufacturing, transportation and logistics as well. The main object of these problems is to find an optimal sequence of tasks to be able to fulfil predefined objectives. There are efficient methods to solve complex scheduling problems in science and industry, which methods […]

Graphics Processing units have become a valuable support for High Performance Computing (HPC) applications. However, despite the many improvements on the General Purpose GPU, there is still the need of a generic programming model adaptable to the many forms of parallelism that an application can express. The CUDA programming model is widely used on the […]

Today, computer simulations form an integral part of many research and development efforts. The scope of what can be modeled has increased dramatically, as computing performance improved over the last two decades. But with serial-execution performance of CPUs leveling off, future performance increases for computational physics, material design, and biology must come from higher parallelization. […]

This paper presents an analytic formulation for anti-aliased sampling of 2D polygons and 3D polyhedra. Our framework allows the exact evaluation of the convolution integral with a linear function defined on the polytopes. The filter is a spherically symmetric polynomial of any order, supporting approximations to refined variants such as the Mitchell-Netravali filter family. This […]