The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Mesoscopic Traffic Simulation is an important tool in traffic analysis and traffic management support. The balance between traffic modeling details and performance has made Mesoscopic Traffic Simulation one of the key solutions for traffic controllers and policy makers. Mesoscopic traffic simulators offer acceptable speed in simulating normal traffic. However, when traffic prediction and optimization...
This paper implements a Smoothed Particle Hydrodynamics simulation code and distributes it on a heterogeneous cluster. The theoretical analysis results show that treating GPU as equivalent peer of CPU rather than an assistant or a substitute is the most efficient way of using a CPU+GPU compute node. However, it raises complex challenges of heterogeneous cooperation. Our strategies of hybrid-level...
Modern Graphics Processing Units (GPUs) with massive number of threads and many-core architecture support both graphics and general purpose computing. NVIDIA's compute unified device architecture (CUDA) takes advantage of parallel computing and utilizes the tremendous power of GPUs. The present study demonstrates a high performance computing (HPC) framework for a Monte-Carlo simulation to determine...
Several numerical methods for solving the Maxwell-Liouville equations have been published, featuring different accuracy, application range, and computational complexity. We implement the most established method on a multi-core central processing unit (CPU) as well as on a graphics processing unit (GPU) and demonstrate the efficiency of both implementations. The acquired performance values may serve...
Cloud computing has enabled provisioning of scalable and virtualized resources to organizations in an ubiquitous and on-demand manner. Likewise, configurable process modeling has enabled organizations to reuse their existing knowledge by sharing a reference process model between different tenants that can be customized according to specific needs. Nevertheless, there are some limitations in this context,...
Future Advanced Driver Assistance Systems (ADAS) need to create an accurate model of the environment. Accordingly, an enormous amount of data has to be fused and processed. From this data, information such as the positions of the vehicles, has to be extracted out of the model, e.g., to create a convoy track. Common architectures used today, like single-core processors in automotive Electronic Control...
How to effectively utilize the computing resource remains a longstanding challenge in MapReduce application, and MapReduce system productivity has become a major issue in research field. In the paper, we explored the productivity mathematical models for MapReduce system, defining the productivity as the ratio of the workload and energy consumption per unit time, and proposed the measurement approach...
The growing demands in IT services for improving efficiency and quality at low cost to handle complex compute requirements has led to the integration of High performance computing (HPC) systems and cloud infrastructure in data centers. Earlier, HPC systems were limited to academic and research institutions and engineering laboratories. However, the emergence of cloud infrastructures and their successful...
Molecular dynamics (MD) is a computer simulation method of studying physical movements of atoms and molecules that provide detailed microscopic sampling on molecular scale. With the continuous efforts and improvements, MD simulation gained popularity in materials science, biochemistry and biophysics with various application areas and expanding data scale. Assisted Model Building with Energy Refinement...
This paper investigates and studies the acceleration of irregular/regular algorithms via Integrate Graphic Processing Unit (Integrated GPU) known as Accelerated Processing Unit (APU) that is fused on the same die with the CPU, and Discrete Graphic Processing Unit (GPU), while answering the question of How potential is the APU for applications with iregular data structures such as trees knowing that...
GPUs have emerged as general-purpose accelerators in high-performance computing (HPC) and scientific applications. However, the reliability characteristics of GPU applications have not been investigated in depth. While error propagation has been extensively investigated for non-GPU applications, GPU applications have a very different programming model which can have a significant effect on error propagation...
Heterogeneous systems are ubiquitous in the field of High- Performance Computing (HPC). Graphics processing units (GPUs) are widely used as accelerators for their enormous computing potential and energy efficiency; furthermore, on-die integration of GPUs and general-purpose cores (CPUs) enables unified virtual address spaces and seamless sharing of data structures, improving programmability and softening...
This paper analyzes the parallelization efficiency of Menge [1], an open source virtual crowd simulation system widely used for algorithm benchmarking, with focuses on three aspects: performance of the existing parallel processing scheme, bottleneck of parallel processing, and improvement opportunities for parallel efficiency of the system. First, we calculate the speedup ratio of each Menge module...
Accelerator-based platforms are heterogeneous in nature, yet most applications avoid heterogeneity, and focus on acceleration alone. Platform-level heterogeneity can bring significant performance improvement, as it essentially means using additional resources for the same computation. But is the performance gained using these additional resources worth the effort to program and deploy heterogeneous...
In this paper, we propose a framework of CPU-GPU coupled computation based on OpenCL (Open Computing Language) for the real-time rendering of large-scale terrain datasets. Firstly, large-scale terrain datasets are divided into terrain chunks with the same size. Then appropriate terrain chunks are loaded into the host memory and the global memory of OpenCL device by 2-level caching mechanism and the...
This paper presents a novel parallelization approach to speedup EMT simulation, using GPU-based computing. This paper extends earlier published works in the area, by exploiting additional parallelism to accelerate EMT simulation. A 2D-parallel matrix-vector multiplication is used that is faster than previous 1D-methods. Also this paper implements a simpler GPU-specific sparsity technique to further...
Graph analytics has become essential to uncover relationship insights in complex systems. As graphs grow in scale, several graph-parallel frameworks including Pregel, GraphLab, and PowerGraph are developed based on commodity computers and/or Cloud instances. According to recent research and empirical performance evaluation, system optimization on PowerGraph allow it to outperform others significantly...
Many of the continuing scientific advances achieved through computational biology are predicated on the availability of ongoing increases in computational power required for detailed simulation and analysis of cellular processes on biologically-relevant timescales. A critical challenge facing the development of future exascale supercomputer systems is the development of new computing hardware and...
We present an efficient and scalable scheme for implementing agent-based modeling (ABM) simulation with In Situ visualization of large complex systems on heterogeneous computing platforms. The scheme is designed to make optimal use of the resources available on a heterogeneous platform consisting of a multicore CPU and a GPU, resulting in minimal to no resource idle time. Furthermore, the scheme was...
Cloud computing is the promising technology to support virtualization, resource management and provide services to IaaS, PaaS, SaaS. While cloud provides many features but still it has some short comings like energy consumption between clouds. So the major objective of the cloud computing is to provide the reliable service keeping minimum energy utilization. This paper focuses on analyzing the scheduling...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.