346 research outputs found

    A Proposal for a Three Detector Short-Baseline Neutrino Oscillation Program in the Fermilab Booster Neutrino Beam

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    A Short-Baseline Neutrino (SBN) physics program of three LAr-TPC detectors located along the Booster Neutrino Beam (BNB) at Fermilab is presented. This new SBN Program will deliver a rich and compelling physics opportunity, including the ability to resolve a class of experimental anomalies in neutrino physics and to perform the most sensitive search to date for sterile neutrinos at the eV mass-scale through both appearance and disappearance oscillation channels. Using data sets of 6.6e20 protons on target (P.O.T.) in the LAr1-ND and ICARUS T600 detectors plus 13.2e20 P.O.T. in the MicroBooNE detector, we estimate that a search for muon neutrino to electron neutrino appearance can be performed with ~5 sigma sensitivity for the LSND allowed (99% C.L.) parameter region. In this proposal for the SBN Program, we describe the physics analysis, the conceptual design of the LAr1-ND detector, the design and refurbishment of the T600 detector, the necessary infrastructure required to execute the program, and a possible reconfiguration of the BNB target and horn system to improve its performance for oscillation searches.Comment: 209 pages, 129 figure

    Fast algorithm for real-time rings reconstruction

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    The GAP project is dedicated to study the application of GPU in several contexts in which real-time response is important to take decisions. The definition of real-time depends on the application under study, ranging from answer time of ÎĽs up to several hours in case of very computing intensive task. During this conference we presented our work in low level triggers [1] [2] and high level triggers [3] in high energy physics experiments, and specific application for nuclear magnetic resonance (NMR) [4] [5] and cone-beam CT [6]. Apart from the study of dedicated solution to decrease the latency due to data transport and preparation, the computing algorithms play an essential role in any GPU application. In this contribution, we show an original algorithm developed for triggers application, to accelerate the ring reconstruction in RICH detector when it is not possible to have seeds for reconstruction from external trackers

    Plasma Physics Computations on Emerging Hardware Architectures

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    This thesis explores the potential of emerging hardware architectures to increase the impact of high performance computing in fusion plasma physics research. For next generation tokamaks like ITER, realistic simulations and data-processing tasks will become significantly more demanding of computational resources than current facilities. It is therefore essential to investigate how emerging hardware such as the graphics processing unit (GPU) and field-programmable gate array (FPGA) can provide the required computing power for large data-processing tasks and large scale simulations in plasma physics specific computations. The use of emerging technology is investigated in three areas relevant to nuclear fusion: (i) a GPU is used to process the large amount of raw data produced by the synthetic aperture microwave imaging (SAMI) plasma diagnostic, (ii) the use of a GPU to accelerate the solution of the Bateman equations which model the evolution of nuclide number densities when subjected to neutron irradiation in tokamaks, and (iii) an FPGA-based dataflow engine is applied to compute massive matrix multiplications, a feature of many computational problems in fusion and more generally in scientific computing. The GPU data processing code for SAMI provides a 60x acceleration over the previous IDL-based code, enabling inter-shot analysis in future campaigns and the data-mining (and therefore analysis) of stored raw data from previous MAST campaigns. The feasibility of porting the whole Bateman solver to a GPU system is demonstrated and verified against the industry standard FISPACT code. Finally a dataflow approach to matrix multiplication is shown to provide a substantial acceleration compared to CPU-based approaches and, whilst not performing as well as a GPU for this particular problem, is shown to be much more energy efficient. Emerging hardware technologies will no doubt continue to provide a positive contribution in terms of performance to many areas of fusion research and several exciting new developments are on the horizon with tighter integration of GPUs and FPGAs with their host central processor units. This should not only improve performance and reduce data transfer bottlenecks, but also allow more user-friendly programming tools to be developed. All of this has implications for ITER and beyond where emerging hardware technologies will no doubt provide the key to delivering the computing power required to handle the large amounts of data and more realistic simulations demanded by these complex systems

    Methodology for complex dataflow application development

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    This thesis addresses problems inherent to the development of complex applications for reconfig- urable systems. Many projects fail to complete or take much longer than originally estimated by relying on traditional iterative software development processes typically used with conventional computers. Even though designer productivity can be increased by abstract programming and execution models, e.g., dataflow, development methodologies considering the specific properties of reconfigurable systems do not exist. The first contribution of this thesis is a design methodology to facilitate systematic develop- ment of complex applications using reconfigurable hardware in the context of High-Performance Computing (HPC). The proposed methodology is built upon a careful analysis of the original application, a software model of the intended hardware system, an analytical prediction of performance and on-chip area usage, and an iterative architectural refinement to resolve identi- fied bottlenecks before writing a single line of code targeting the reconfigurable hardware. It is successfully validated using two real applications and both achieve state-of-the-art performance. The second contribution extends this methodology to provide portability between devices in two steps. First, additional tool support for contemporary multi-die Field-Programmable Gate Arrays (FPGAs) is developed. An algorithm to automatically map logical memories to hetero- geneous physical memories with special attention to die boundaries is proposed. As a result, only the proposed algorithm managed to successfully place and route all designs used in the evaluation while the second-best algorithm failed on one third of all large applications. Second, best practices for performance portability between different FPGA devices are collected and evaluated on a financial use case, showing efficient resource usage on five different platforms. The third contribution applies the extended methodology to a real, highly demanding emerging application from the radiotherapy domain. A Monte-Carlo based simulation of dose accumu- lation in human tissue is accelerated using the proposed methodology to meet the real time requirements of adaptive radiotherapy.Open Acces

    New strategies for the aerodynamic design optimization of aeronautical configurations through soft-computing techniques

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    Premio Extraordinario de Doctorado de la UAH en 2013Lozano RodrĂ­guez, Carlos, codir.This thesis deals with the improvement of the optimization process in the aerodynamic design of aeronautical configurations. Nowadays, this topic is of great importance in order to allow the European aeronautical industry to reduce their development and operational costs, decrease the time-to-market for new aircraft, improve the quality of their products and therefore maintain their competitiveness. Within this thesis, a study of the state-of-the-art of the aerodynamic optimization tools has been performed, and several contributions have been proposed at different levels: -One of the main drawbacks for an industrial application of aerodynamic optimization tools is the huge requirement of computational resources, in particular, for complex optimization problems, current methodological approaches would need more than a year to obtain an optimized aircraft. For this reason, one proposed contribution of this work is focused on reducing the computational cost by the use of different techniques as surrogate modelling, control theory, as well as other more software-related techniques as code optimization and proper domain parallelization, all with the goal of decreasing the cost of the aerodynamic design process. -Other contribution is related to the consideration of the design process as a global optimization problem, and, more specifically, the use of evolutionary algorithms (EAs) to perform a preliminary broad exploration of the design space, due to their ability to obtain global optima. Regarding this, EAs have been hybridized with metamodels (or surrogate models), in order to substitute expensive CFD simulations. In this thesis, an innovative approach for the global aerodynamic optimization of aeronautical configurations is proposed, consisting of an Evolutionary Programming algorithm hybridized with a Support Vector regression algorithm (SVMr) as a metamodel. Specific issues as precision, dataset training size, geometry parameterization sensitivity and techniques for design of experiments are discussed and the potential of the proposed approach to achieve innovative shapes that would not be achieved with traditional methods is assessed. -Then, after a broad exploration of the design space, the optimization process is continued with local gradient-based optimization techniques for a finer improvement of the geometry. Here, an automated optimization framework is presented to address aerodynamic shape design problems. Key aspects of this framework include the use of the adjoint methodology to make the computational requirements independent of the number of design variables, and Computer Aided Design (CAD)-based shape parameterization, which uses the flexibility of Non-Uniform Rational B-Splines (NURBS) to handle complex configurations. The mentioned approach is applied to the optimization of several test cases and the improvements of the proposed strategy and its ability to achieve efficient shapes will complete this study

    New strategies for the aerodynamic design optimization of aeronautical configurations through soft-computing techniques

    Get PDF
    Premio Extraordinario de Doctorado de la UAH en 2013Lozano RodrĂ­guez, Carlos, codir.This thesis deals with the improvement of the optimization process in the aerodynamic design of aeronautical configurations. Nowadays, this topic is of great importance in order to allow the European aeronautical industry to reduce their development and operational costs, decrease the time-to-market for new aircraft, improve the quality of their products and therefore maintain their competitiveness. Within this thesis, a study of the state-of-the-art of the aerodynamic optimization tools has been performed, and several contributions have been proposed at different levels: -One of the main drawbacks for an industrial application of aerodynamic optimization tools is the huge requirement of computational resources, in particular, for complex optimization problems, current methodological approaches would need more than a year to obtain an optimized aircraft. For this reason, one proposed contribution of this work is focused on reducing the computational cost by the use of different techniques as surrogate modelling, control theory, as well as other more software-related techniques as code optimization and proper domain parallelization, all with the goal of decreasing the cost of the aerodynamic design process. -Other contribution is related to the consideration of the design process as a global optimization problem, and, more specifically, the use of evolutionary algorithms (EAs) to perform a preliminary broad exploration of the design space, due to their ability to obtain global optima. Regarding this, EAs have been hybridized with metamodels (or surrogate models), in order to substitute expensive CFD simulations. In this thesis, an innovative approach for the global aerodynamic optimization of aeronautical configurations is proposed, consisting of an Evolutionary Programming algorithm hybridized with a Support Vector regression algorithm (SVMr) as a metamodel. Specific issues as precision, dataset training size, geometry parameterization sensitivity and techniques for design of experiments are discussed and the potential of the proposed approach to achieve innovative shapes that would not be achieved with traditional methods is assessed. -Then, after a broad exploration of the design space, the optimization process is continued with local gradient-based optimization techniques for a finer improvement of the geometry. Here, an automated optimization framework is presented to address aerodynamic shape design problems. Key aspects of this framework include the use of the adjoint methodology to make the computational requirements independent of the number of design variables, and Computer Aided Design (CAD)-based shape parameterization, which uses the flexibility of Non-Uniform Rational B-Splines (NURBS) to handle complex configurations. The mentioned approach is applied to the optimization of several test cases and the improvements of the proposed strategy and its ability to achieve efficient shapes will complete this study

    CompF2: Theoretical Calculations and Simulation Topical Group Report

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    This report summarizes the work of the Computational Frontier topical group on theoretical calculations and simulation for Snowmass 2021. We discuss the challenges, potential solutions, and needs facing six diverse but related topical areas that span the subject of theoretical calculations and simulation in high energy physics (HEP): cosmic calculations, particle accelerator modeling, detector simulation, event generators, perturbative calculations, and lattice QCD (quantum chromodynamics). The challenges arise from the next generations of HEP experiments, which will include more complex instruments, provide larger data volumes, and perform more precise measurements. Calculations and simulations will need to keep up with these increased requirements. The other aspect of the challenge is the evolution of computing landscape away from general-purpose computing on CPUs and toward special-purpose accelerators and coprocessors such as GPUs and FPGAs. These newer devices can provide substantial improvements for certain categories of algorithms, at the expense of more specialized programming and memory and data access patterns.Comment: Report of the Computational Frontier Topical Group on Theoretical Calculations and Simulation for Snowmass 202

    NASA Tech Briefs, June 2012

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    Topics covered include: iGlobe Interactive Visualization and Analysis of Spatial Data; Broad-Bandwidth FPGA-Based Digital Polyphase Spectrometer; Small Aircraft Data Distribution System; Earth Science Datacasting v2.0; Algorithm for Compressing Time-Series Data; Onboard Science and Applications Algorithm for Hyperspectral Data Reduction; Sampling Technique for Robust Odorant Detection Based on MIT RealNose Data; Security Data Warehouse Application; Integrated Laser Characterization, Data Acquisition, and Command and Control Test System; Radiation-Hard SpaceWire/Gigabit Ethernet-Compatible Transponder; Hardware Implementation of Lossless Adaptive Compression of Data From a Hyperspectral Imager; High-Voltage, Low-Power BNC Feedthrough Terminator; SpaceCube Mini; Dichroic Filter for Separating W-Band and Ka-Band; Active Mirror Predictive and Requirement Verification Software (AMP-ReVS); Navigation/Prop Software Suite; Personal Computer Transport Analysis Program; Pressure Ratio to Thermal Environments; Probabilistic Fatigue Damage Program (FATIG); ASCENT Program; JPL Genesis and Rapid Intensification Processes (GRIP) Portal; Data::Downloader; Fault Tolerance Middleware for a Multi-Core System; DspaceOgreTerrain 3D Terrain Visualization Tool; Trick Simulation Environment 07; Geometric Reasoning for Automated Planning; Water Detection Based on Color Variation; Single-Layer, All-Metal Patch Antenna Element with Wide Bandwidth; Scanning Laser Infrared Molecular Spectrometer (SLIMS); Next-Generation Microshutter Arrays for Large-Format Imaging and Spectroscopy; Detection of Carbon Monoxide Using Polymer-Composite Films with a Porphyrin-Functionalized Polypyrrole; Enhanced-Adhesion Multiwalled Carbon Nanotubes on Titanium Substrates for Stray Light Control; Three-Dimensional Porous Particles Composed of Curved, Two-Dimensional, Nano-Sized Layers for Li-Ion Batteries 23 Ultra-Lightweight; and Ultra-Lightweight Nanocomposite Foams and Sandwich Structures for Space Structure Applications
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