high performance computing on graphics processing units: hgpu.org

The thesis describes the original design, implementation and testing of the multi-GPU version of two fluid flow simulation models, focusing on the cellular automaton MAGFLOW lava flow simulator and the GPU-SPH model for Navier-Stokes. In both cases, a spatial subdivision of the domain is performed, with a minimal overlap to ensure the correct evaluation of […]

Language models play an important role in large vocabulary speech recognition and statistical machine translation systems. The dominant approach since several decades are back-off language models. Some years ago, there was a clear tendency to build huge language models trained on hundreds of billions of words. Lately, this tendency has changed and recent works concentrate […]

The integration of graphics processing units (GPUs) into real-time systems has recently become an active area of research. However, prior research on this topic has failed to produce real-time GPU allocation methods that fully exploit the available parallelism in GPU-enabled systems. In this paper, a GPU management framework called GPUSync is described that was designed […]

Similarity search has been widely studied in the last years, as it can be applied to several fields such as searching by content in multimedia objects, text retrieval or computational biology. These applications usually work on very large databases that are often indexed off-line to enable the acceleration of online searches. However, to maintain an […]

In recent years Independent Component Analysis (ICA) has become a standard to identify relevant dimensions of the data in neuroscience. ICA is a very reliable method to analyze data but it is, computationally, very costly. The use of ICA for on-line analysis of the data, used in brain computing interfaces, results almost completely prohibitive. We […]

We solve the ghost-gluon system of Yang-Mills theory using Graphics Processing Units (GPUs). Working in Landau gauge, we use the Dyson-Schwinger formalism for the mathematical description as this approach is well-suited to directly benefit from the computing power of the GPUs. With the help of a Chebyshev expansion for the dressing functions and a subsequent […]

The Mining Software Repositories (MSR) field integrates and analyzes data stored in repositories such as source control and bug repositories to support practitioners. Given the abundance of repository data, scaling up MSR analyses has become a major challenge. Recently, researchers have experimented with conventional techniques like a super-computer or cloud computing, but these are either […]

This paper presents an approach the point to point processing of digital images using parallel computing, particularly for grayscale, brightening, darkening, thresholding and contrast change. The point to point technique applies a transformation to each pixel on image concurrently rather than sequentially. This approach used CUDA as parallel programming tool on a GPU in order […]

Efficient implementation of general purpose particle tracking on GPUs can result in significant performance benefits to large scale particle tracking and tracking-based accelerator optimization simulations. We present our work on accelerating Argonne National Lab’s accelerator simulation code ELEGANT [1, 2] using CUDA-enabled GPUs [3]. In particular, we provide an overview of beamline elements ported to […]

This work introduces S-buffer, an efficient and memory-friendly gpu-accelerated A-buffer architecture for multi-fragment rendering. Memory is organized into variable contiguous regions for each pixel, thus avoiding limitations set in linked-lists and fixed-array techniques. S-buffer exploits fragment distribution for precise allocation of the needed storage and pixel sparsity (empty pixel ratio) for computing the memory offsets […]

The threadblock size and shape choice is one of the most important user decisions when a parallel problem is coded to run in GPU architectures. In fact, threadblock configuration has a significant impact on the global performance of the program. Unfortunately, the programmer has not enough information about the subtle interactions between this choice of […]

The Fast Multipole Method (FMM) is a hierarchical N-body algorithm with linear complexity, high arithmetic intensity, high data locality, has hierarchical communication patterns, and no global synchronization. The combination of these features allows the FMM to scale well on large GPU based systems, and to use their compute capability effectively. We present a 1 PFlop/s […]