high performance computing on graphics processing units: hgpu.org

The aim of this work was the investigation of implementability and efficiency of an algorithm for solving optimal control problems on a new hardware architecture. For an academic test problem the collective smoothing multigrid method (CSMG) was realized on a commodity graphics card (GPU) and the performance in term of elapsed time compared to those […]

Ultrasonic imaging and reconstruction tools are com-monly used to detect, identify and measure defects in different mechanical parts. Due to the complexity of the underlying physics, and due to the evergrowing quantity of acquired data, computation time is becoming a limitation to the opti-mal inspection of a mechanical part. This article presents the performances of […]

This paper presents a novel local contrast enhancement algorithm based on local histogram modification. The computation of local contrast enhancement operators is usually slow though they produce better local contrast and details. We have addressed this issue by subtly designing a highly parallel algorithm, which could be easily implemented on Graphics Processing Units (GPU) to […]

Tiling is a key technique to enhance data reuse. For computations structured as one sequential outer "time" loop enclosing a set of parallel inner loops, tiling only the parallel inner loops may not enable enough data reuse in the cache. Tiling the inner loops along with the outer time loop enhances data locality but may […]

In this paper, we present an image object tracking system for GPGPU based CAMshift algorithm. For image object tracking, we use the parallel CAMshift tracking algorithm based on the HSV color image distribution of detected moving objects. In this, RGB-to-HSV color conversion, image masking such as open and close operation for image morphology, and computing […]

This research aims to accelerate the computation of the Kleene star in max-plus algebra using CUDA technology on graphics processing units (GPUs). The target module is the Kleene star of a weighted adjacency matrix for directed acyclic graph (DAGs) which plays an essential role in calculating the earliest and/or latest schedule for a class of […]

As graphics processing units (GPUs) are continually being utilized as coprocessors, the demand for optimally utilizing them for various applications continues to grow. This work narrows the gap between programmers and minimum execution time for matrix-based computations on a GPU. To minimize execution time, computation and communication time must be considered. For computation, the placement […]

In this paper, we present techniques that coordinate the thread scheduling and prefetching decisions in a General Purpose Graphics Processing Unit (GPGPU) architecture to better tolerate long memory latencies. We demonstrate that existing warp scheduling policies in GPGPU architectures are unable to effectively incorporate data prefetching. The main reason is that they schedule consecutive warps, […]

Multimedia applications are present in most mobile hand-held devices. The H.264 standard is currently dominating the video compression world. H.264 has high computational complexity requiring large amount of processing resources. Many techniques emerged that optimize H.264 using parallelization on multicore systems ranging from groups of pictures until the smallest block of pixels. We propose a […]

The volume of banks data calculation is increasing each year with extraordinary scale and with that, new forms of computation is needed. High performance computing is a very attractive field for optimization such bank calculous, which can give promising results. This paper shows a implementation of know model for assessing the credit risk of a […]

In recent years, the computational power of modern processors has been increasing mainly because of the increase in the number of processor cores. Computationally intensive applications can gain from this trend only if they employ parallelism, such as thread-level parallelization. Geometric simulations can employ thread-level parallelization because the main part of a geometric simulation can […]

A modified parallel variable distribution (PVD) algorithm for solving large-scale constrained optimization problems is developed, which modifies quadratic subproblem QPl at each iteration instead of the QPl of the SQP-type PVD algorithm proposed by C. A. Sagastizabal and M. V. Solodov in 2002. The algorithm can circumvent the difficulties associated with the possible inconsistency of […]