With the rise of Internet of Things devices, there is an increasing demand for embedded control systems. Discrete-Event modeling of embeddedsystems (DEMES) is a Discrete Event System Specification (DEVS) based model ...
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Sensor fusion is a technique used to combine sensor data and improve the description of the physical property measured by these sensors. Sensors working alone could provide data that is erroneous, incomplete and uncer...
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There are many possible applications for virtual reality, which is regarded as the apex of human-computer interactions. In order to improve the standardization and automation of disaster operation management, a novel ...
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ISBN:
(纸本)9781665462761
There are many possible applications for virtual reality, which is regarded as the apex of human-computer interactions. In order to improve the standardization and automation of disaster operation management, a novel emergency management strategy based on activity network technology is presented. First, the emergency plan is constructed utilizing technology called an activity network and emergency response activities. Straight lines connecting waypoints of interest can be used to depict a virtual journey, although this basic model does not adequately capture ordinary user activity. We put the model into a framework that may be used to reroute medical and food assistance in various real-world and virtual settings. It is helpful for evaluating redirected parameters in different circumstances. In our concept, a flood scenario is the emergency that is needed, and the virtual hologram aids the user in gathering data from each person who requires assistance utilizing a wireless sensor network. The electronic civilization has undergone significant transformation thanks to embedded technology, which has a sizable community. Microcontrollers can be used by embeddedsystems to collectdata, process it, and produce reliable results. Intelligent principal layout and precise analysis are provided by simulation software when designing a project.
Graphics processing units (GPUs) are widely used in the area of scientific computing. While GPUs provide much higher peak performance, efficient implementation of real applications on the GPU architectures is still a ...
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Graphics processing units (GPUs) are widely used in the area of scientific computing. While GPUs provide much higher peak performance, efficient implementation of real applications on the GPU architectures is still a non-trivial task. It is crucial to realize efficient solution algorithms that can better utilize GPU architectures. This paper presents our efforts in parallelizing and optimizing LESAP, a CFD application for scramjet combustion simulation, on NVIDIA GPUs. The GPU parallelization is realized based on the CUDA programming model, with a data-parallel implicit time-marching method that is efficient on the GPU architecture. Furthermore, shared memory and redundant calculation are proposed to reduce memory access overhead during GPU computation, and data transfer between CPU and GPU is optimized by packing the data to be transferred. The experimental results show that the GPU version, when runs on four V100 GPUs, achieves a speedup of 11.26 times compared to the CPU version that runs on two 24-core Intel Skylake Gold 6240R CPUs. Excellent parallel scalability across multiple GPUs is also observed.
We present the HelioCubed, a high-order magnetohydrodynamic (MHD) code designed for modeling the inner heliosphere. The code is designed to achieve 4th order accuracy both in space and in time. In addition, HelioCubed...
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The increasing complexity of Cyber-Physical systems (CPS) causes a shift from traditional single-core embedded platforms to complex multi-core or even heterogeneous platforms to meet the performance requirements. Howe...
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Recent advancements in distributed data storage, colloborative processing capabilities, and their architectural design have a profound influence on our daily lives, simplifying the process of hosting computation-inten...
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ISBN:
(数字)9798350306545
ISBN:
(纸本)9798350306552
Recent advancements in distributed data storage, colloborative processing capabilities, and their architectural design have a profound influence on our daily lives, simplifying the process of hosting computation-intensive software applications. A single software hosting device, for instance, an Onboard Computation Unit (OBCU) of an autonomous vehicle, on the other hand, can’t keep up with the growing need for diverse requirements of computing architectures and processing power of such applications. For example, the real-time handling and generation of HD maps is one such crucial and highly computation-intensive application for autonomous vehicles. For this purpose, an efficient solution is to rely on the computing power of adjacent resource-rich nodes. Hence, the use of a latency-aware predictive analytics-based computation task offloading method has a vital significance, especially with the advent of Vehicular Edge and Fog Computing (VEFC). VEFC models pool redundant computational resources in close proximity. It, however, faces several challenges. The stochastic nature of vehicular networks, intricate heterogeneity at several levels, and the uncertainty of time-sensitive applications for the timely completion of tasks impede the VEFC’s efficiency. We developed a computation offloading framework that timely alleviates the computing-resource-deficit devices by deploying vehicles as fog-nodes commensurate with the minimum latency requirements of advanced vehicular applications, especially computation-intensive HD map handling, and generation in real-time. Our technique is a greedy heuristic method that works in small, discrete steps instead of solving the entire optimization problem holistically. We used Monte Carlo simulation to show that our approach had an overall response time of under-300 milliseconds compared to other baseline methods.
A formal computational model is presented for the sequential kernel of an automotive embedded real-time operating system, which provides infrastructural mechanism to support the isolation between applications and the ...
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ISBN:
(纸本)9781665413657
A formal computational model is presented for the sequential kernel of an automotive embedded real-time operating system, which provides infrastructural mechanism to support the isolation between applications and the operating system, as well as the isolation between executive entities such as tasks and ISRs (Interrupt Service Routines) in applications. The target embedded system is modeled at the granularity of isolated memory regions and stacks. Tasks, nested ISRs and the preempt-able part of the operating system (i.e. system services) are concurrent entities executing on dedicated memory regions and stacks determined by the sequential kernel. States of these entities can be correctly saved and restored in isolated stacks and in the kernel data structures, such that the control flow changes among them can be correctly made. The implementation correctness theorem of the kernel is established along with the corresponding simulation relationship and implementation invariants. According to the features of the model and the related implementation languages, the kernel is formally verified with the theorem prover Isabelle/HOL.
Machine learning is one of the most cutting edge methods in computer vision. Convolutional Neural Networks (CNN) in particular are widely used in edge computing based applications such as autonomous driving for image ...
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Dynamic management of modern Multi-Processors System on Chip (MPSoC) become mandatory for optimization purpose. Evaluation of these managers is essential early in the design process to guarantee a reduced design cycle...
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ISBN:
(纸本)9783030275624;9783030275617
Dynamic management of modern Multi-Processors System on Chip (MPSoC) become mandatory for optimization purpose. Evaluation of these managers is essential early in the design process to guarantee a reduced design cycle. However, most of the existing system-level simulation-based frameworks consider static application mapping and do not consider the run-time management effects. In this work, we present a modeling and simulation approach that allows integration of run-time management strategies in MPSoC system simulation. We have integrated the proposed approach in an industrial modeling and simulation framework. A case-study with seven applications running on a heterogeneous multicore platform is considered and different management strategies are evaluated according to latency and power consumption criteria.
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