high performance computing on graphics processing units: hgpu.org

With the rapid development of infrared detector, Realtime detection of infrared targets faces biggish challenge; In the Infrared System with detector of more cells and higher frame speed, when using more complicated processing arithmetic, the Signal Processing Platform basing on the trad framework has met hardly the demand of System’s Real-Time Detecting; the GPU for […]

In this paper, we propose a novel floorplanning algorithm based on simulated annealing on GPUs. Simulated annealing is an inherently sequential algorithm, far from the typical programs suitable for Single Instruction Multiple Data (SIMD) style concurrency in a GPU. We propose a fundamentally different approach of exploring the floorplan solution space, where we evaluate concurrent […]

Functional verification of modern digital designs is a mission critical and time-consuming task. Verification is essential since it ensures the correctness of the final product; however, due to the complexity of modern designs, verification has become the primary bottleneck of time to market. Logic simulation forms the core of most current verification efforts, as it […]

Providing realistic, high-resolution and high fidelity representation of motions ia essential in the cloth simulation problem. In order to make high resolution simulations tractable, several algorithms have been developed that manage cloth-object interactions efficiently through specialized data structures such as AABB trees. However, implementation restrictions on single CPU architectures impose certain limits on quality and […]

Recent windowing systems allow graphics applications to directly access the graphics processing unit (GPU) for fast rendering. However, application tasks that render frames on the GPU contend heavily with the windowing server that also accesses the GPU to blit the rendered frames to the screen. This resource-sharing nature of direct rendering introduces core challenges of […]

In this paper, we analyze a particular spatial locality case (called horizontal locality) inherent to manycore accelerator architectures employing barrel execution of SPMD kernels, such as GPUs. We then propose an adaptive memory access granularity framework to exploit and enforce the horizontal locality in order to reduce the interferences among accelerator cores memory accesses and […]

For the last two years, we have been experimenting with applying compressed sensing parallel imaging for body imaging of pediatric patients. It is a joint-effort by teams from UC Berkeley, Stanford University and GE Healthcare. This paper aims to summarize our experience so far. We describe our acquisition approach: 3D spoiled-gradient-echo with poisson-disc random undersampling […]

In this paper, we present a GPU-based algorithm which accelerates the MoM impedance matrix computation. Based on an efficient quasi-one-dimensional approximation of the reaction integrals, the MPIE formulation for the analysis of microstrip circuits is considered. We use NVIDIA CUDA as GPU development tool and choose an edge-connected line-fed patch antenna as reference problem. In […]

Compton reconstruction requires the computationally intensive, yet highly parallelizable, task of Cone of Response (CoR) back-projection. The acceleration of CoR back-projection is of significant importance as a faster algorithm allows the user to increase either the size or resolution of the imaging volume. Such acceleration also lends itself to the realization of real-time reconstruction. The […]

The programmability of recent graphic processing unit (GPU) architectures has been the main factor driving the dramatic increase in interest for this class of architectures as low-cost accelerators for a wide range of high-performance applications. Current GPU programming models, such as OpenCL and CUDA, still expose too many architectural features, such as the memory hierarchy, […]

Clinical diagnosis and quantification of liver disease have been improved through the development of techniques using contrast-enhanced liver MRI sequences. To qualitatively or quantitatively analyze such image sequences, one first needs to correct for rigid and non-rigid motion of the liver. For motion correction of the liver, we have employed bi-directional local correlation coefficient Demons, […]

Stochastic methods based on Maximum Likelihood Estimation (MLE) provide accurate tomographic reconstruction for emission imaging. Moreover methods based on MLE allow to include an accurate physical model of the imaging setup in the reconstruction process, thus enabling quantitative reconstruction of radio-tracer activity distribution. It has been shown that inclusion of a spatially dependent PSF that […]