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Posts

May, 23

GMProf: A Low-Overhead, Fine-Grained Profiling Approach for GPU Programs

Driven by the cost-effectiveness and the power-efficiency, GPUs are being increasingly used to accelerate computations in many domains. However, developing highly efficient GPU implementations requires a lot of expertise and effort. Thus, tool support for tuning GPU programs is urgently needed, and more specifically, lowoverhead mechanisms for collecting fine-grained runtime information are critically required. Unfortunately, […]
May, 23

Molecular Distance Geometry Optimization Using Geometric Build-up and Evolutionary Techniques on GPU

We present a combination of methods addressing the molecular distance problem, implemented on a graphic processing unit. First, we use geometric build-up and depth-first graph traversal. Next, we refine the solution by simulated annealing. For an exact but sparse distance matrix, the buildup method reconstructs the 3D structures with a root-meansquare error (RMSE) in the […]
May, 23

Medical Image Registration using OpenCL

Medical image registration is a computational task involving the spatial realignment of multiple sets of images of the same or different modalities. A novel method of using the Open Computing Language (OpenCL) framework to accelerate affine image registration across multiple processing architectures is presented. The use of this method on graphics processors results in a […]
May, 23

Investigating Warp Size Impact in GPUs

There are a number of design decisions that impact a GPU’s performance. Among such decisions deciding the right warp size can deeply influence the rest of the design. Small warps reduce the performance penalty associated with branch divergence at the expense of a reduction in memory coalescing. Large warps enhance memory coalescing significantly but also […]
May, 23

Adaptive fast multipole methods on the GPU

We present a highly general implementation of fast multipole methods on graphics processing units (GPUs). Our two-dimensional double precision code features an asymmetric type of adaptive space discretization leading to a particularly elegant and flexible implementation. All steps of the multipole algorithm are efficiently performed on the GPU, including the initial phase which assembles the […]
May, 20

Self-Tuning Distribution of DB-Operations on Hybrid CPU/GPU Platforms

A current research trend focuses on accelerating database operations with the help of GPUs (Graphics Processing Units). Since GPU algorithms are not necessarily faster than their CPU counterparts, it is important to use them only if they outperform their CPU counterparts. In this paper, we address this problem by constructing a decision model for a […]
May, 20

High-Level Support for Pipeline Parallelism on Many-Core Architectures

With the increasing architectural diversity of many-core architectures the challenges of parallel programming and code portability will sharply rise. The EU project PEPPHER addresses these issues with a component-based approach to application development on top of a task-parallel execution model. Central to this approach are multi-architectural components which encapsulate different implementation variants of application functionality […]
May, 20

Computing 2D Alpha Shapes Using GPU

This report presents an approach to compute Alpha Shapes for a 2D un-weighted point set using the graphics processing unit (GPU). The problem of alpha shapes has been well-defined and algorithms have been developed to compute it efficiently in 2D and 3D using CPU. However, the nature of this problem makes it well-suited for solving […]
May, 20

Spatial Data Structures, Sorting and GPU Parallelism for Situated-agent Simulation and Visualisation

Spatial data partitioning techniques are important for obtaining fast and efficient simulations of N-Body particle and spatial agent based models where they considerably reduce redundant entity interaction computation times. Highly parallel techniques based on concurrent threading can be deployed to further speed up such simulations. We study the use of GPU accelerators and highly data […]
May, 20

CUDA Based Enhanced Differential Evolution: a Computational Analysis

General purpose graphic programming unit (GPGPU) programming is a novel approach for solving parallel variable independent problems. The graphic processor core (GPU) gives the possibility to use multiple blocks, each of which contains hundreds of threads. Each of these threads can be visualized as a core onto itself, and tasks can be simultaneously sent to […]
May, 19

Combustion Simulations Using Graphic Processing Units

Graphic processing units (GPUs) are powerful graphics engines featuring high levels of parallelism and extreme memory bandwidth, which constitute a powerful computing platform to solve complex problems involving chemically reacting flows. In the present study, computer programs for combustion simulations with detailed chemical kinetic mechanisms were compiled in the Compute Unified Device Architecture (CUDA) language […]
May, 19

A GPU Algorithm for 3D Convex Hull

A novel algorithm is presented to compute the convex hull of a point set in R3using the graphics processing unit (GPU). By exploiting the relationship between the Voronoi diagram and the convex hull, the algorithm derives the approximation of the convex hull from the former. The missed points are found back by using a two-round […]

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