Download or read book Parallel Algorithms for Monte Carlo Particle Transport Simulation on Exascale Computing Architectures written by Paul Kollath Romano and published by . This book was released on 2013 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monte Carlo particle transport methods are being considered as a viable option for high-fidelity simulation of nuclear reactors. While Monte Carlo methods offer several potential advantages over deterministic methods, there are a number of algorithmic shortcomings that would prevent their immediate adoption for full-core analyses. In this thesis, algorithms are proposed both to ameliorate the degradation in parallal efficiency typically observed for large numbers of processors and to offer a means of decomposing large tally data that will be needed for reactor analysis. A nearest-neighbor fission bank algorithm was proposed and subsequently implemented in the OpenMC Monte Carlo code. A theoretical analysis of the communication pattern shows that the expected cost is O([square root]N) whereas traditional fission bank algorithms are O(N) at best. The algorithm was tested on two supercomputers, the Intrepid Blue Gene/P and the Titan Cray XK7, and demonstrated nearly linear parallel scaling up to 163,840 processor cores on a full-core benchmark problem. An algorithm for reducing network communication arising from tally reduction was analyzed and implemented in OpenMC. The proposed algorithm groups only particle histories on a single processor into batches for tally purposes - in doing so it prevents all network communication for tallies until the very end of the simulation. The algorithm was tested, again on a full-core benchmark, and shown to reduce network communication substantially. A model was developed to predict the impact of load imbalances on the performance of domain decomposed simulations. The analysis demonstrated that load imbalances in domain decomposed simulations arise from two distinct phenomena: non-uniform particle densities and non-uniform spatial leakage. The dominant performance penalty for domain decomposition was shown to come from these physical effects rather than insufficient network bandwidth or high latency. The model predictions were verified with measured data from simulations in OpenMC on a full-core benchmark problem. Finally, a novel algorithm for decomposing large tally data was proposed, analyzed, and implemented/tested in OpenMC. The algorithm relies on disjoint sets of compute processes and tally servers. The analysis showed that for a range of parameters relevant to LWR analysis, the tally server algorithm should perform with minimal overhead. Tests were performed on Intrepid and Titan and demonstrated that the algorithm did indeed perform well over a wide range of parameters.
Download or read book Parallel Algorithms in Computational Science written by Dieter W. Heermann and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our aim in this book is to present and enlarge upon those aspects of parallel computing that are needed by practitioners of computational science. Today al most all classical sciences, such as mathematics, physics, chemistry and biology, employ numerical methods to help gain insight into nature. In addition to the traditional numerical methods, such as matrix inversions and the like, a whole new field of computational techniques has come to assume central importance, namely the numerical simulation methods. These methods are much less fully developed than those which are usually taught in a standard numerical math ematics course. However, they form a whole new set of tools for research in the physical sciences and are applicable to a very wide range of problems. At the same time there have been not only enormous strides forward in the speed and capability of computers but also dramatic new developments in computer architecture, and particularly in parallel computers. These improvements offer exciting prospects for computer studies of physical systems, and it is the new techniques and methods connected with such computer simulations that we seek to present in this book, particularly in the light of the possibilities opened up by parallel computers. It is clearly not possible at this early stage to write a definitive book on simulation methods and parallel computing.
Download or read book Monte Carlo Methods for Particle Transport written by Alireza Haghighat and published by CRC Press. This book was released on 2020-08-09 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fully updated with the latest developments in the eigenvalue Monte Carlo calculations and automatic variance reduction techniques and containing an entirely new chapter on fission matrix and alternative hybrid techniques. This second edition explores the uses of the Monte Carlo method for real-world applications, explaining its concepts and limitations. Featuring illustrative examples, mathematical derivations, computer algorithms, and homework problems, it is an ideal textbook and practical guide for nuclear engineers and scientists looking into the applications of the Monte Carlo method, in addition to students in physics and engineering, and those engaged in the advancement of the Monte Carlo methods. Describes general and particle-transport-specific automated variance reduction techniques Presents Monte Carlo particle transport eigenvalue issues and methodologies to address these issues Presents detailed derivation of existing and advanced formulations and algorithms with real-world examples from the author’s research activities
Download or read book Scalable Domain Decomposed Monte Carlo Particle Transport written by and published by . This book was released on 2013 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, we present the parallel algorithms necessary to run domain decomposed Monte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costly than the numerical simulation.
Download or read book Scalable Domain Decomposed Monte Carlo Particle Transport written by Matthew Joseph O'Brien and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, we present the parallel algorithms necessary to run domain decomposedMonte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costlythan the numerical simulation. The main algorithms we consider are:* Domain decomposition of constructive solid geometry: enables extremely largecalculations in which the background geometry is too large to fit in the memory of asingle computational node.* Load Balancing: keeps the workload per processor as even as possible so the calculationruns efficiently.* Global Particle Find: if particles are on the wrong processor, globally resolve theirlocations to the correct processor based on particle coordinate and background domain.* Visualizing constructive solid geometry, sourcing particles, deciding that particlestreaming communication is completed and spatial redecomposition.These algorithms are some of the most important parallel algorithms required for domaindecomposed Monte Carlo particle transport. We demonstrate that our previous algorithmswere not scalable, prove that our new algorithms are scalable, and run some of the algorithmsup to 2 million MPI processes on the Sequoia supercomputer.
Download or read book Advanced Monte Carlo for Radiation Physics Particle Transport Simulation and Applications written by Andreas Kling and published by Springer Science & Business Media. This book was released on 2014-02-22 with total page 1200 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the state of the art of Monte Carlo methods in radiation physics and particle transport simulation and applications. Special attention is paid to algorithm development for modeling, and the analysis of experiments and measurements in a variety of fields.
Download or read book Monte Carlo Particle Transport Methods written by I. Lux and published by CRC Press. This book was released on 2018-05-04 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: With this book we try to reach several more-or-less unattainable goals namely: To compromise in a single book all the most important achievements of Monte Carlo calculations for solving neutron and photon transport problems. To present a book which discusses the same topics in the three levels known from the literature and gives us useful information for both beginners and experienced readers. It lists both well-established old techniques and also newest findings.
Download or read book Massively Parallel Algorithms for Method of Characteristics Neutral Particle Transport on Shared Memory Computer Architectures written by William Robert Dawson Boyd (III.) and published by . This book was released on 2014 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past 20 years, parallel computing has enabled computers to grow ever larger and more powerful while scientific applications have advanced in sophistication and resolution. This trend is being challenged, however, as the power consumption for conventional parallel computing architectures has risen to unsustainable levels and memory limitations have come to dominate compute performance. Multi-core processors and heterogeneous computing platforms, such as Graphics Processing Units (GPUs), are an increasingly popular paradigm for resolving these issues. This thesis explores the applicability of shared memory parallel platforms for solving deterministic neutron transport problems. A 2D method of characteristics code - OpenMOC - has been developed with solvers for shared memory multi-core platforms as well as GPUs. The multi-threading and memory locality methodologies for the multi-core CPU and GPU solvers are presented. Parallel scaling results using OpenMP demonstrate better than ideal weak scaling and nearly perfect strong scaling on both Intel Xeon and IBM Blue Gene/Q architectures. Performance results for the 2D C5G7 benchmark demonstrate up to 50x speedup for MOC on a GPU. The lessons learned from this thesis will provide the basis for further exploration of MOC on many-core platforms and GPUs as well as design decisions for hardware vendors exploring technologies for the next generation of machines for scientific computing.
Download or read book Challenges of Monte Carlo Transport written by and published by . This book was released on 2016 with total page 49 pages. Available in PDF, EPUB and Kindle. Book excerpt: These are slides from a presentation for Parallel Summer School at Los Alamos National Laboratory. Solving discretized partial differential equations (PDEs) of interest can require a large number of computations. We can identify concurrency to allow parallel solution of discrete PDEs. Simulated particles histories can be used to solve the Boltzmann transport equation. Particle histories are independent in neutral particle transport, making them amenable to parallel computation. Physical parameters and method type determine the data dependencies of particle histories. Data requirements shape parallel algorithms for Monte Carlo. Then, Parallel Computational Physics and Parallel Monte Carlo are discussed and finally the results are given. The mesh passing method greatly simplifies the IMC implementation and allows simple load-balancing. Using MPI windows and passive, one-sided RMA further simplifies the implementation by removing target synchronization. The author is very interested in implementations of PGAS that may allow further optimization for one-sided, read-only memory access (e.g. Open SHMEM). The MPICH_RMA_OVER_DMAPP option and library is required to make one-sided messaging scale on Trinitite - Moonlight scales poorly. Interconnect specific libraries or functions are likely necessary to ensure performance. BRANSON has been used to directly compare the current standard method to a proposed method on idealized problems. The mesh passing algorithm performs well on problems that are designed to show the scalability of the particle passing method. BRANSON can now run load-imbalanced, dynamic problems. Potential avenues of improvement in the mesh passing algorithm will be implemented and explored. A suite of test problems that stress DD methods will elucidate a possible path forward for production codes.
Download or read book Monte Carlo Methods And Parallel Algorithms International Youth Workshop written by I Dimov and published by World Scientific. This book was released on 1991-01-31 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: These proceedings present recent advances in the Monte Carlo methods, covering theoretical aspects, a wide range of applications in solving problems, and parallel algorithms for Monte Carlo computations.
Download or read book III III written by and published by . This book was released on 1945 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Computational Science ICCS 2021 written by Maciej Paszynski and published by Springer Nature. This book was released on 2021-06-10 with total page 815 pages. Available in PDF, EPUB and Kindle. Book excerpt: The six-volume set LNCS 12742, 12743, 12744, 12745, 12746, and 12747 constitutes the proceedings of the 21st International Conference on Computational Science, ICCS 2021, held in Krakow, Poland, in June 2021.* The total of 260 full papers and 57 short papers presented in this book set were carefully reviewed and selected from 635 submissions. 48 full and 14 short papers were accepted to the main track from 156 submissions; 212 full and 43 short papers were accepted to the workshops/ thematic tracks from 479 submissions. The papers were organized in topical sections named: Part I: ICCS Main Track Part II: Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Applications of Computational Methods in Artificial Intelligence and Machine Learning; Artificial Intelligence and High-Performance Computing for Advanced Simulations; Biomedical and Bioinformatics Challenges for Computer Science Part III: Classifier Learning from Difficult Data; Computational Analysis of Complex Social Systems; Computational Collective Intelligence; Computational Health Part IV: Computational Methods for Emerging Problems in (dis-)Information Analysis; Computational Methods in Smart Agriculture; Computational Optimization, Modelling and Simulation; Computational Science in IoT and Smart Systems Part V: Computer Graphics, Image Processing and Artificial Intelligence; Data-Driven Computational Sciences; Machine Learning and Data Assimilation for Dynamical Systems; MeshFree Methods and Radial Basis Functions in Computational Sciences; Multiscale Modelling and Simulation Part VI: Quantum Computing Workshop; Simulations of Flow and Transport: Modeling, Algorithms and Computation; Smart Systems: Bringing Together Computer Vision, Sensor Networks and Machine Learning; Software Engineering for Computational Science; Solving Problems with Uncertainty; Teaching Computational Science; Uncertainty Quantification for Computational Models *The conference was held virtually. Chapter “Deep Learning Driven Self-adaptive hp Finite Element Method” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Download or read book Advances in Parallel Algorithms written by Ivan Dimov and published by IOS Press. This book was released on 1994 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text presents an overview of research in the subjects of computational linear algebra, Monte Carlo algorithms and parallel algorithms in discrete mathematics. Topics covered include theoretical investigations of numerical analysis and parallel algorithms, and practical large-scale problem solving such as modelling of semiconductor devices, ballistic trajectory estimations and the simulation of distributed memory parallel computers.
Download or read book Monte Carlo Methods for Applied Scientists written by Ivan T. Dimov and published by World Scientific. This book was released on 2008 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Monte Carlo method is inherently parallel and the extensive and rapid development in parallel computers, computational clusters and grids has resulted in renewed and increasing interest in this method. At the same time there has been an expansion in the application areas and the method is now widely used in many important areas of science including nuclear and semiconductor physics, statistical mechanics and heat and mass transfer.This book attempts to bridge the gap between theory and practice concentrating on modern algorithmic implementation on parallel architecture machines. Although a suitable text for final year postgraduate mathematicians and computational scientists it is principally aimed at the applied scientists: only a small amount of mathematical knowledge is assumed and theorem proving is kept to a minimum, with the main focus being on parallel algorithms development often to applied industrial problems.A selection of algorithms developed both for serial and parallel machines are provided.
Download or read book Development of a Multiple Perturbation Monte Carlo Method for Eigenvalue Problems and Implementation on Parallel Processors written by Amitava Majumdar and published by . This book was released on 1996 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Particle Transport Simulation with the Monte Carlo Method written by Leland Lavele Carter and published by . This book was released on 1975 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Cluster Partitioning Approaches to Parallel Monte Carlo Simulation on Multiprocessors written by Udaya A. Ranawake and published by . This book was released on 1992 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider the parallelization of Monte Carlo algorithms for analyzing numerical models of charge transport used in semiconductor device physics. Parallel algorithms for the standard k-space Monte Carlo simulation of a three band model of bulk GaAs on hypercube multicomputers are first presented. This Monte Carlo model includes scattering due to polar-optical, intervalley, and acoustic phonons, as well as electron-electron scattering. The k-space Monte Carlo program, excluding electron-electron scattering, is then extended to simulate a semiconductor device by the addition of the real space position of each simulated particle and the assignment of particle charge, using a cloud in cell scheme, to solve the Poisson's equation with particle dynamics. Techniques for effectively partitioning this device so as to balance the computational load while minimizing the communication overhead are discussed. Approaches for improving the efficiency of the parallel algorithm, either by dynamically balancing of load or by employing the usual techniques for enhancing rare events in Monte Carlo simulations are also considered. The parallel algorithms were implemented on a 64-node NCUBE multiprocessor and test results were generated to validate the parallel k-space, as well as the device simulation programs. Timing measurements were also made to study the variation of speedups as both the problem size and number of processors are varied. The effective exploitation of the computational power of message passing multiprocessors requires the efficient mapping of parallel programs onto processors so as to balance the computational load while minimizing the communication overhead between processors. A lower bound for this communication volume when mapping arbitrary task graphs onto distributed processor systems is derived. For a K processor system this lower bound can be computed from the K (possibly) largest eigenvalues of the adjacency matrix of the task graph and the eigenvalues of the adjacency matrix of the processor graph. We also derive the eigenvalues of the adjacency matrix of the processor graph for a hypercube and give test results comparing the lower bound for the communication volume with the values given by a heuristic algorithm for a number of task graphs.
