high performance computing on graphics processing units: hgpu.org

Rate-distortion (RD)-based mode selections are important techniques in video coding. In these methods, an encoder may compute the RD costs for all the possible coding modes, and select the one which achieves the best trade-off between encoding rate and compression distortion. Previous papers have demonstrated that RD-based mode selections can lead to significant improvements in […]

Graphics processors are designed to perform many floating-point operations per second. Consequently, they are an attractive architecture for high-performance computing at a low cost. Nevertheless, it is still not very clear how to exploit all their potential for general-purpose applications. In this work we present a comprehensive study of the performance of an application executing […]

Graphics processing units (GPUs) have been widely used to accelerate algorithms that exhibit massive data parallelism or task parallelism. When such parallelism is not inherent in an algorithm, computational scientists resort to simply replicating the algorithm on every multiprocessor of a NVIDIA GPU, for example, to create such parallelism, resulting in embarrassingly parallel ensemble runs […]

When reconstructing a specific type or class of object using stereo, we can leverage prior knowledge of the shape of that type of object. A popular class of object to reconstruct is the human face. In this paper we learn a statistical wavelet prior of the shape of the human face and use it to […]

Efficient implementations of the Discrete Fourier Transform (DFT) for GPUs provide good performance with large data sizes, but are not competitive with CPU code for small data sizes. On the other hand, several applications perform multiple DFTs on small data sizes. In fact, even algorithms for large data sizes use a divide-and-conquer approach, where eventually […]

In this work, we present an interactive visual clustering approach for the exploration and analysis of vast volumes of data. Our proposed approach is a bio-inspired collective behavioral model to be used in a 3D graphics environment. Our paper illustrates an extension of the behavioral model for clustering and a parallel implementation, using Compute Unified […]

It is well known that LDPC decoding is computationally demanding and one of the hardest signal operations to parallelize. Beyond data dependencies that restrict the decoding of a single word, it requires a large number of memory accesses. In this paper we propose parallel algorithms for performing in GPUs the most demanding case of irregular […]

Terrain modeling is an important task in digital content creation and physics-based approaches have the potential to simplify it. However, most of the existing simulations are hindered by a low level of user control, because they fail on large-scale phenomena. We introduce a new accessible physics-based framework for digital terrain editing. Our solution is suitable […]

We present a practical importance-driven method for GPU-based final gathering. We take as input a point cloud representing directly illuminated scene geometry; we then project and splat the points to microbuffers, which store each shading pixel’s occluded radiance field. We select points for projection based on importance, defined as each point’s estimated contribution to a […]

Variable bit rate compression can achieve better quality and compression rates than fixed bit rate methods. None the less, GPU texturing uses lossy fixed bit rate methods like DXT to allow random access and on-the-fly decompression during rendering. Changes in games and GPUs since DXT was developed make its compression artifacts less acceptable, and texture […]

Ray casting on graphics processing units (GPUs) opens new possibilities for molecular visualization. We describe the implementation and calculation of diverse molecular representations such as licorice, ball-and-stick, space-filling van der Waals spheres, and approximated solvent-accessible surfaces using GPUs. We introduce HyperBalls, an improved ball-and-stick representation replacing tubes, linking the atom spheres by hyperboloids that can […]

Partial Differential Equations (PDE) are the heart of most simulations in many scientific fields, from Fluid Mechanics to Astrophysics. One the most popular mathematical schemes to solve a PDE is Finite Difference (FD). In this work we map a PDE-FD algorithm called Reverse Time Migration to a GPU using CUDA. This seismic imaging (Geophysics) algorithm […]