high performance computing on graphics processing units: hgpu.org

We explore software mechanisms for managing irregular tasks on graphics processing units (GPUs). We demonstrate that dynamic scheduling and efficient memory management are critical problems in achieving high efficiency on irregular workloads. We experiment with several task-management techniques, ranging from the use of a single monolithic task queue to distributed queuing with task stealing and […]

The computational power provided by many-core graphics processing units (GPUs) has been exploited in many applications. The programming techniques currently employed on these GPUs are not sufficient to address problems exhibiting irregular, and unbalanced workload. The problem is exacerbated when trying to effectively exploit multiple GPUs concurrently, which are commonly available in many modern systems. […]

This research project studies the parallel computing technique offered by the graphics processing unit (GPU), and uses it to accelerate the computation of image registration. Image registration is a process that aligns two images so that the point in one image corresponds to the same anatomical point in the other. It is a key part […]

This thesis presents a comparison of high-speed rendering algorithms for the application in 2D/3D-image registration in radiation oncology. Image guided radiation therapy (IGRT) is a technique for improving the treatment of cancer with ionizing radiation by adapting the treatment plan to the current situation using 2D/3D-image registration. To accelerate this procedure, also rendering of Digitally […]

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 […]

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 […]