high performance computing on graphics processing units: hgpu.org

The simulation of the hepatocellular carcinoma therapy effects is often used for the intervention planning. As the physical-based model of the simulation is very time-consuming, the speed of this method becomes an obstacle during the clinical application simulation. In order to accelerate the simulation, a GPU-based (Graphic Processing Unit) acceleration method of the pressure field […]

The extending of Synthetic Aperture Radar (SAR) applications brings new challenges to SAR signal processing. Highly efficient SAR signal processors need to be explored towards these challenges. Recently, Graphics Processing Unit (GPU) is developing at top speed, which is a novel and promising computation platform for efficient SAR processors. A GPU-based SAR signal processor is […]

GPU-based systems are used more and more for medical image processing because of their parallel processing power and memory bandwidth. Impressive results have been achieved when registering large volume, however, one of themost-used similarity measures for multi-modal registration – mutual information – is not well suited for the streaming architecture because of its memory access […]

Accelerators, such as field programmable gate arrays (FPGAs) and graphics processing units (GPUs), are special purpose processors designed to speed up compute-intensive sections of applications. FPGAs are highly customizable, while GPUs provide massive parallel execution resources and high memory bandwidth. In this paper, we compare the performance of these architectures, presenting a performance study of […]

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 […]