high performance computing on graphics processing units: hgpu.org

Real-time rendering of complex 3D models is still a very challenging task. Recently, many GPU-based level-of-detail (LOD) algorithms have been proposed to decrease the complexity of 3D models in a parallel fashion. However, LOD approaches alone are not sufficient to reduce the amount of geometry data for interactive rendering of massive scale models. Visibility-based culling, […]

This paper presents the Saddle Vertex Graph (SVG), a novel solution to the discrete geodesic problem. The SVG is a sparse undirected graph that encodes complete geodesic distance information: a geodesic path on the mesh is equivalent to a shortest path on the SVG, which can be solved efficiently using the shortest path algorithm (e.g., […]

This paper develops a modeling and simulation framework for determining mission effectiveness of a two-body Hypervelocity Asteroid Intercept Vehicle (HAIV). This HAIV concept has been being developed to overcome key difficulties in coupling energy from nuclear explosives to an asteroid target at high relative velocities of 5 – 30 km/s. It does so by blending […]

In this paper, we explore the opportunity for solving high dimensional Backward Stochastic Differential Equations (BSDEs) on the GPU with application in high dimensional American option pricing. A Least Square Monte Carlo method based numerical algorithm for solving the BSDEs is studied and summarized in four phases. For the parallel GPU algorithms of different phases, […]

Neuroscience currently lacks a comprehensive theory of how cognitive processes can be implemented in a biological substrate. The Neural Engineering Framework (NEF) proposes one such theory, but has not yet gathered significant empirical support, partly due to the technical challenge of building and simulating large-scale models with the NEF. Nengo is a software tool that […]

In this paper, we present a new approach for shape-grammar-based generation and rendering of huge cities in real-time on the graphics processing unit (GPU). Traditional approaches rely on evaluating a shape grammar and storing the geometry produced as a preprocessing step. During rendering, the pregenerated data is then streamed to the GPU. By interweaving generation […]

Hidden Semi-Markov Models (HSMMs) are powerful generalizations of Hidden Markov Models that have been effectively employed in tasks such as machine translation and optical character recognition. A principal computational bottleneck on these systems as applied to optical character recognition [5] is the need to compute emission probabilities for a large number of possible model states. […]

In this study, an implementation of a Kite Aerial Photography (KAP) system for real time image enhancement /reconstruction of remote sensing (RS) imagery is presented. The system is comprised in three stages: first, a gyro-stabilized mechatronic platform for the image acquisition is developed; second, the multispectral images are transmitted via RF to ground station; and […]

There are great interests in understanding the manner by which the prime numbers are distributed throughout the integers. Prime numbers are being used in secret codes for more than 60 years now. Computer security authorities use extremely large prime numbers when they devise cryptographs, like RSA (short for Rivest, Shamir, and Adleman) algorithm, for protecting […]

Every area of science and engineering today has to process voluminous data sets. Using exact, or even approximate, algorithms to solve intractable problems in critical areas, such as computational biology, takes time that is exponential in some of the underlying parameters. Parallel computing addresses this issue and has become affordable with the advent of multicore […]

User-level components can expose multiple functionally equivalent implementations with different resource requirements and performance characteristics. A composition framework can then choose a suitable implementation for each component invocation guided by an objective function (execution time, energy etc.). In this paper, we describe the idea of conditional composition which enables the component writer to specify constraints […]

The Bayesian theorem is the most used instrument for stochastic inferencing in nonlinear dynamic systems and also the fundament of measurement uncertainty evaluation in the GUM. Many powerful algorithms have been derived and applied to numerous problems. The most widely used algorithms are the broad family of Kalman filters (KFs), the grid-based filters and the […]