high performance computing on graphics processing units: hgpu.org

The power of Markov random field formulations of lowlevel vision problems, such as stereo, has been known for some time. However, recent advances, both algorithmic and in processing power, have made their application practical. This paper presents a novel implementation of Bayesian belief propagation for graphics processing units found in most modern desktop and notebook […]

Double-float (df64) and quad-float (qf128) numeric types can be implemented on current GPU hardware and used efficiently and effectively for extended-precision computational arithmetic. Using unevaluated sums of paired or quadrupled f32 single-precision values, these numeric types provide approximately 48 and 96 bits of mantissa respectively at single-precision exponent ranges for computer graphics, numerical, and general-purpose […]

Restricted solid on solid surface growth models can be mapped onto binary lattice gases. We show that efficient simulation algorithms can be realized on GPUs either by CUDA or by OpenCL programming. We consider a deposition/evaporation model following Kardar-Parisi-Zhang growth in 1+1 dimensions related to the Asymmetric Simple Exclusion Process and show that for sizes, […]

Object-oriented programming has worked quite well – so far. What are the objects, how do they relate to each other? Once we clarified these questions we typically feel confident to design and implement even the most complex systems. However, objects can deceive us. They can lure us into a false sense of understanding. The metaphor […]

This paper presents a novel method for using programmable graphics hardware to generate fringe patterns for SLM-based holographic displays. The algorithm is designed to take the programming constraints imposed by the graphics hardware pipeline model into consideration, and scales linearly with the number of object points. In contrast to previous methods we do not have […]

Dynamic programming has been one of the most efficient approaches to sequence analysis and structure prediction in biology. However, their performance is limited due to the drastic increase in both the number of biological data and variety of the computer architectures. With regard to such predicament, this paper creates excellent algorithms aimed at addressing the […]

Due to the immense computational power of today’s graphics processors (GPU), general purpose computation on GPUs has become a vivid research area. The performance of algorithms running on GPUs highly depends on how well they can be arranged to fit and exploit the processors single instruction multiple data (SIMD) architecture. Many tasks that are considered […]

Field programmable gate arrays (FPGAs), graphics processing units (GPUs) and Sony’s Playstation 2 vector units offer scope for hardware acceleration of applications. Implementing algorithms on multiple architectures can be a long and complicated process. We demonstrate an approach to compiling for FPGAs, GPUs and PS2 vector units using a unified description based on A Stream […]

We present an efficient implementation of motion estimation (ME) for H.264/AVC using programmable graphics hardware. The cost function for ME in H.264/AVC depends on the motion vector (MV) predictor which is the median MV of three neighboring coded blocks. Previous implementations assume no dependency among adjacent blocks, which is not true for H.264/AVC, they also […]

In this paper, we propose a new technique for hardware accelerated multi-resolution geometry synthesis. The level of detail for a given viewpoint is created on-the-fly, allowing for an almost unlimited model resolution in rendering without excessive memory usage. The models consist of regularly sampled rectangular patches that are subdivided hierarchically by a programmable shader in […]

With shrinking process technology, the primary cause of transient faults in semiconductors shifts away from high-energy cosmic particle strikes and toward more mundane and pervasive causes—power fluctuations, crosstalk, and other random noise. Smaller transistor features require a lower critical charge to hold and change bits, which leads to faster microprocessors, but which also leads to […]

This paper presents Glift, an abstraction and generic template library for defining complex, random-access graphics processor (GPU) data structures. Like modern CPU data structure libraries, Glift enables GPU programmers to separate algorithms from data structure definitions; thereby greatly simplifying algorithmic development and enabling reusable and interchangeable data structures. We characterize a large body of previously […]