403,195 research outputs found

    A real-time, dual processor simulation of the rotor system research aircraft

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    A real-time, man-in-the loop, simulation of the rotor system research aircraft (RSRA) was conducted. The unique feature of this simulation was that two digital computers were used in parallel to solve the equations of the RSRA mathematical model. The design, development, and implementation of the simulation are documented. Program validation was discussed, and examples of data recordings are given. This simulation provided an important research tool for the RSRA project in terms of safe and cost-effective design analysis. In addition, valuable knowledge concerning parallel processing and a powerful simulation hardware and software system was gained

    Parallel Anisotropic Unstructured Grid Adaptation

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    Computational Fluid Dynamics (CFD) has become critical to the design and analysis of aerospace vehicles. Parallel grid adaptation that resolves multiple scales with anisotropy is identified as one of the challenges in the CFD Vision 2030 Study to increase the capacity and capability of CFD simulation. The Study also cautions that computer architectures are undergoing a radical change and dramatic increases in algorithm concurrency will be required to exploit full performance. This paper reviews four different methods to parallel anisotropic grid generation. They cover both ends of the spectrum: (i) using existing state-of-the-art software optimized for a single core and modifying it for parallel platforms and (ii) designing and implementing scalable software with incomplete, but rapidly maturating functionality. A brief overview for each grid adaptation system is presented in the context of a telescopic approach for multilevel concurrency. These methods employ different approaches to enable parallel execution, which provides a unique opportunity to illustrate the relative behavior of each approach. Qualitative and quantitative metric evaluations are used to draw lessons for future developments in this critical area for parallel CFD simulation

    Normalized analysis and design of LCC resonant converters

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    Abstract—A normalization of the LCC voltage-output resonant converter performance characteristics, in terms of the tank gain at resonance and the parallel-to-series-capacitor ratio, is presented. The resulting description is subsequently used for the derivation of a design procedure that incorporates the effects of diode losses and the finite charge/discharge time of the parallel capacitor. Unlike previously reported techniques, the resulting normalized behavior of the converter is used to identify design regions to facilitate a reduction in component electrical stresses, and the use of harmonics to transfer real power. Consideration of the use of preferred component values is also given. The underlying methodology is ultimately suitable for incorporation into a software suite for use as part of a rapid interactive design tool. Both simulation results and experimental measurements from a prototype converter are included to demonstrate the attributes of the proposed analysis and design methodologies

    High-performance cluster computing, algorithms, implementations and performance evaluation for computation-intensive applications to promote complex scientific research on turbulent flows

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    Large-scale high-performance computing is a very rapidly growing field of research that plays a vital role in the advance of science, engineering, and modern industrial technology. Increasing sophistication in research has led to a need for bigger and faster computers or computer clusters, and high-performance computer systems are themselves stimulating the redevelopment of the methods of computation. Computing is fast becoming the most frequently used technique to explore new questions. We have developed high-performance computer simulation modeling software system on turbulent flows. Five papers are selected to present here from dozens of papers published in our efforts on complex software system development and knowledge discovery through computer simulations. The first paper describes the end-to-end computer simulation system development and simulation results that help understand the nature of complex shelterbelt turbulent flows. The second paper deals specifically with high-performance algorithm design and implementation in a cluster of computers. The third paper discusses the twelve design processes of parallel algorithms and software system as well as theoretical performance modeling and characterization of cluster computing. The fourth paper is about the computing framework of drag and pressure coefficients. The fifth paper is about simulated evapotranspiration and energy partition of inhomogeneous ecosystems. We discuss the end-to-end computer simulation system software development, distributed parallel computing performance modeling and system performance characterization. We design and compare several parallel implementations of our computer simulation system and show that the performance depends on algorithm design, communication channel pattern, and coding strategies that significantly impact load balancing, speedup, and computing efficiency. For a given cluster communication characteristics and a given problem complexity, there exists an optimal number of nodes. With this computer simulation system, we resolved many historically controversial issues and a lot of important problems

    QuOp_MPI: a framework for parallel simulation of quantum variational algorithms

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    QuOp_MPI is a Python package designed for parallel simulation of quantum variational algorithms. It presents an object-orientated approach to quantum variational algorithm design and utilises MPI-parallelised sparse-matrix exponentiation, the fast Fourier transform and parallel gradient evaluation to achieve the highly efficient simulation of the fundamental unitary dynamics on massively parallel systems. In this article, we introduce QuOp_MPI and explore its application to the simulation of quantum algorithms designed to solve combinatorial optimisation algorithms including the Quantum Approximation Optimisation Algorithm, the Quantum Alternating Operator Ansatz, and the Quantum Walk-assisted Optimisation Algorithm.Comment: Software available at: https://github.com/Edric-Matwiejew/QuOp_MP

    Hardware for a real-time multiprocessor simulator

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    The hardware for a real time multiprocessor simulator (RTMPS) developed at the NASA Lewis Research Center is described. The RTMPS is a multiple microprocessor system used to investigate the application of parallel processing concepts to real time simulation. It is designed to provide flexible data exchange paths between processors by using off the shelf microcomputer boards and minimal customized interfacing. A dedicated operator interface allows easy setup of the simulator and quick interpreting of simulation data. Simulations for the RTMPS are coded in a NASA designed real time multiprocessor language (RTMPL). This language is high level and geared to the multiprocessor environment. A real time multiprocessor operating system (RTMPOS) has also been developed that provides a user friendly operator interface. The RTMPS and supporting software are currently operational and are being evaluated at Lewis. The results of this evaluation will be used to specify the design of an optimized parallel processing system for real time simulation of dynamic systems

    Real-time Simulation of Dynamic Vehicle Models using a High-performance Reconfigurable Platform

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    A purely software-based approach for Real-Time Simulation (RTS) may have difficulties in meeting real-time constraints for complex physical model simulations. In this paper, we present a methodology for the design and im-plementationofRTS algorithms,basedontheuseof Field-ProgrammableGateArray(FPGA) technologytoimprove the response time of these models. Our methodology utilizes traditional hardware/software co-design approaches to generate a heterogeneous architecture for an FPGA-based simulator. The hardware design was optimized such that it efficiently utilizes the parallel nature of FPGAs and pipelines the independent operations. Further enhancement is obtained through the use of custom accelerators for common non-linear functions. Since the systems we examined had relatively low response time requirements, our approach greatly simplifies the software components by porting the computationally complexregionsto hardware.We illustratethe partitioningofa hardware-based simulator design across dual FPGAs, initiateRTS usinga system input froma Hardware-in-the-Loop (HIL) framework, and use these simulation results from our FPGA-based platform to perform response analysis. The total simulation time, which includes the time required to receive the system input over a socket (without HIL), software initialization, hardware computation, and transferof simulation results backovera socket, showsa speedup of 2× as compared to a simi-lar setup with no hardware acceleration. The correctness of the simulation output from the hardware has also been validated with the simulated results from the software-only design

    Bandpass filter design with spurious frequency reduction capability

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    Passband microstrip coupled line filter are widely used in daily microwave engineering practice. There are various topologies to implement microstrip bandpass filters such as end-coupled, parallel coupled, hairpin, interdigital and combine filters. This thesis discusses design, simulation, fabrication and testing using microstrip technology. The choice of a parallel coupled filter topology is discussed and an application of the grooved substrate is presented to suppress the first spurious of Parallel Coupled Microstrip Bandpass Filter (PCMBF). Band pass filters (BPF) are significant role in wireless communication systems. These filters present an undesired pass band at twice the design central frequency of the filter. The narrowband with spurious suppression is achieved by using two stage PCMBF, BPF was designed by replacing the tight couplers are arranged at the input and output of the filter whist the weak couplers at the middle section of the tight coupler with optimize groove. By using Sonnet Lite software it shown the BPF with 2.99GHz cut off frequency and bandstop of to 7GHz has been simulated and fabricated on Flame Retardant 4 (FR4) substrate by using etching process. Significant spurious suppression up to 33.23dB is measured at 5.96GHz

    Analytic Performance Modeling and Analysis of Detailed Neuron Simulations

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    Big science initiatives are trying to reconstruct and model the brain by attempting to simulate brain tissue at larger scales and with increasingly more biological detail than previously thought possible. The exponential growth of parallel computer performance has been supporting these developments, and at the same time maintainers of neuroscientific simulation code have strived to optimally and efficiently exploit new hardware features. Current state of the art software for the simulation of biological networks has so far been developed using performance engineering practices, but a thorough analysis and modeling of the computational and performance characteristics, especially in the case of morphologically detailed neuron simulations, is lacking. Other computational sciences have successfully used analytic performance engineering and modeling methods to gain insight on the computational properties of simulation kernels, aid developers in performance optimizations and eventually drive co-design efforts, but to our knowledge a model-based performance analysis of neuron simulations has not yet been conducted. We present a detailed study of the shared-memory performance of morphologically detailed neuron simulations based on the Execution-Cache-Memory (ECM) performance model. We demonstrate that this model can deliver accurate predictions of the runtime of almost all the kernels that constitute the neuron models under investigation. The gained insight is used to identify the main governing mechanisms underlying performance bottlenecks in the simulation. The implications of this analysis on the optimization of neural simulation software and eventually co-design of future hardware architectures are discussed. In this sense, our work represents a valuable conceptual and quantitative contribution to understanding the performance properties of biological networks simulations.Comment: 18 pages, 6 figures, 15 table

    Transparently Mixing Undo Logs and Software Reversibility for State Recovery in Optimistic PDES

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    The rollback operation is a fundamental building block to support the correct execution of a speculative Time Warp-based Parallel Discrete Event Simulation. In the literature, several solutions to reduce the execution cost of this operation have been proposed, either based on the creation of a checkpoint of previous simulation state images, or on the execution of negative copies of simulation events which are able to undo the updates on the state. In this paper, we explore the practical design and implementation of a state recoverability technique which allows to restore a previous simulation state either relying on checkpointing or on the reverse execution of the state updates occurred while processing events in forward mode. Differently from other proposals, we address the issue of executing backward updates in a fully-transparent and event granularity-independent way, by relying on static software instrumentation (targeting the x86 architecture and Linux systems) to generate at runtime reverse update code blocks (not to be confused with reverse events, proper of the reverse computing approach). These are able to undo the effects of a forward execution while minimizing the cost of the undo operation. We also present experimental results related to our implementation, which is released as free software and fully integrated into the open source ROOT-Sim (ROme OpTimistic Simulator) package. The experimental data support the viability and effectiveness of our proposal
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