high performance computing on graphics processing units: hgpu.org

We present a method for fast phase based registration of volume data for medical applications. As the number of different modalities within medical imaging increases, it becomes more and more important with registration that works for a mixture of modalities. For these applications the phase based registration approach has proven to be superior. Today there […]

The Variable Preconditioned GVR (VPGCR) with mixed precision on Graphics Processing Unit (GPU) using Compute Unified Device Architecture (CUDA) is numerically investigated. The convergence theorem of VPGCR is guaranteed that the residual equation for the preconditioned procedure can be solved in the range of single precision operation. The results of computations show that VPGCR with […]

During the last few years, Graphics Processing Units (GPU) have evolved from simple devices for the display signal preparation into powerful coprocessors that do not only support typical computer graphics tasks such as rendering of 3D scenarios but can also be used for general numeric and symbolic computation tasks such as simulation and optimization. As […]

The discrete wavelet transform (DWT) has been extensively used for image compression and denoising in the areas of image processing and computer vision. However, the intensive computation of DWT due to its inherent multilevel data decomposition and reconstruction operations brings a bottleneck that drastically reduces its performance and implementations for real-time applications when facing large […]

Over the past few years, there has been a shift towards multi-core processors, driven partially by physical limitations. Mistaken assumptions of how effective and useful parallel systems can be have also provided motivation for this change. In this paper, we seek to directly identify the barriers to parallel computation. The barriers are not, as conventional […]

While GPGPU stands for general-purpose computation on graphics processing units, the lack of explicit support for inter-block communication on the GPU arguably hampers its broader adoption as a general-purpose computing device. Interblock communication on the GPU occurs via global memory and then requires barrier synchronization across the blocks, i.e., inter-block GPU communication via barrier synchronization. […]

Finding the all-pairs shortest-paths on a large graph is a fundamental problem in many practical applications such as bioinformatics, internet node traffic and network routing. In this paper, we present the designs of two efficient parallel algorithms for many-core GPUs using CUDA. Our algorithms expose substantial fine-grained parallelism while maintaining minimal global communication. By using […]

In recent years, with the development of GPU, based on the general purpose computation on graphics processors has became a new field. Aiming at the processing of GPU, this paper provides the formal description for data parallel mode, a detailed description of the CUDA programming mode land the principle of optimization. It shows by the […]

Nowadays, the compute capability of traditional cluster system can’t keep up with the computing needs of a practical application, and these aspects of energy, space technology, etc. have become a huge problem. However, as parallel computing equipment, the stream processor (SP) has a high performance of floating-point operations. NVIDIA GPUs is a typical stream processor […]

Scene recognition has become a remarkable field in image processing area, and many methods have been proposed in recent years, in which the idea of extracting the scene gist from global features has been proved to have higher retrieval accuracy compared with many other methods. However, the process of extracting gist is heavily time-consuming and […]

The introduction of general purpose computing on many-core graphics processor systems, and the general shift in the industry towards parallelism, has created a demand for ease of parallelization. Software transactional memory (STM) simplifies development of concurrent code by allowing the programmer to mark sections of code to be executed concurrently and atomically in an optimistic […]

Over the last 20 years or so, a number of Bayesian researchers and groups have invested a good deal of time, effort and money in parallel computing for Bayesian analysis. The growth of “small research group” to “institutionally supported” cluster computational facilities has had a substantial impact on a number of areas of Bayesian analysis, […]