The CUDA execution model of Nvidia’s GPUs is based on the asynchronous execution of thread blocks, where each thread executes the same kernel in a data-parallel fashion. When threads in di↵erent thread blocks need to synchronise and communicate, the whole computation launched onto the GPU needs to be stopped and re-invoked in order to facilitate interblock synchronisations and communication. Th...

Huichao Hong, Lixin Zheng, Shuwan Pan Engineering Research Center of Industrial Intelligent Technology and Systems of Fujian Providence College of Engineering,Huaqiao University,Quanzhou, China e-mail: [email protected] Abstract: As in various fields like scientific research and industrial application, the computation time optimization is becoming a task that is of increasing importance because of ...

The Graphics Processing Unit (GPU) is a highly parallel, many-core streaming architecture that can execute hundreds of threads concurrently. The data parallel architecture of the GPU is suitable to perform computation intensive applications. In recent years, the use of GPUs for general purpose computation has increased and a large set of problems can be tackled by mapping onto GPUs. The program...

The primary goal of cloth simulation is to express object behavior in a realistic manner and achieve real-time performance by following the fundamental concept physic. In general, mass–spring system applied with three types springs. However, hard spring using requires small integration time-step order use large stiffness coefficient. Furthermore, obtain stable behavior, constraint enforcement u...

This paper presents the Animated VISualization Tool (AVIST), an exploration-oriented data visualization tool that enables rapidly exploring and filtering large time series multidimensional datasets. AVIST highlights interactive data exploration by revealing fine data details. This is achieved through the use of animation and cross-filtering interactions. To support interactive exploration of bi...

Maximizing the performance potential of the modern day GPU architecture requires judicious utilization of available parallel resources. Although dramatic reductions can often be obtained through straightforward mappings, further performance improvements often require algorithmic redesigns to more closely exploit the target architecture. In this paper, we focus on efficient molecular simulations...

The Relevance Vector Machine (RVM) algorithm has been widely utilized in many applications, such as machine learning, image pattern recognition, and compressed sensing. However, the RVM algorithm is computationally expensive. We seek to accelerate the RVM algorithm computation for time sensitive applications by utilizing massively parallel accelerators such as GPUs. In this paper, the computati...

We present an efficient algorithm to perform approximate offsetting operations on geometric models using GPUs. Our approach approximates the boundary of an object with point samples and computes the offset by merging the balls centered at these points. The underlying approach uses Layered Depth Images (LDI) to organize the samples into structured points and performs parallel computations using ...

The range migration algorithm (RMA) based on Fourier transformation is widely applied in millimeter-wave (MMW) close-range imaging because of its few operations and small approximation. However, interpolation stage not effective due to the involved intensive logic controls, which limits speed performance a graphics processing unit (GPU) platform. Therefore, this paper, we present an acceleratio...

The device-level electromagnetic transient (EMT) simulation with the nonlinear behaviour model (NBM) of insulated-gate bipolar transistors (IGBTs) and diodes can provide an accurate insight into power converters from perspective thermal performance energy efficiency. However, is rarely implemented in electric vehicles (EVs) due to its extreme computation complexity natively introduced by device...