high performance computing on graphics processing units: hgpu.org

In the domain of the Side Channel Attacks, various statistical tools have succeeded to retrieve a secret key, as the Pearson coefficient or the Mutual Information. In this paper we propose to study the Maximal Information Coefficient (MIC) which is a non-parametric method introduced by Reshef et al. [13] to compare two random variables. The […]

A fingerprint matching algorithm with a novel set of matching parameters based on core points and triangular descriptors is proposed to discover rarity in fingerprints. The algorithm uses a mathematical and statistical approach to discover rare features in fingerprints which provides scientific validation for both ten-print and latent fingerprint evidence. A feature is considered rare […]

Nowadays there exist several frameworks to utilize a computation power of graphics cards and other computational devices such as FPGA, ARM and multi-core processors. The best known are either low-level and need a lot of controlling code or are bounded only to special graphic cards. Furthermore there exist more specialized frameworks, mainly aimed to the […]

In the last few years, the development of programming languages for general purpose computing on Graphic Processing Units (GPUs) has led to the design and implementation of fast parallel algorithms for this architecture for a large spectrum of applications. Given the streaming-processing characteristics of GPUs, most practical applications consist of tasks that admit highly data-parallel […]

Particle systems are important building block for simulating vivid and detail-rich effects in virtual world. One of the most difficult aspects of particle systems has been detecting collisions between particlesand mesh surface. Due to the huge computation, a variety of proxy-based approaches have been proposed recently to perform visually correct simulation. However, all either limit […]

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. […]