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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 397 records · Page 22

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DOE OSTI2012

SDAV Viz July Progress Update: LANL

SDAV Viz July Progress Update: (1) VPIC (Vector Particle in Cell) Kinetic Plasma Simulation Code - (a) Implemented first version of an in-situ adapter based on Paraview CoProcessing Library, (b) Three pipelines: vtkDataSetMapper, vtkContourFilter, vtkPistonContour, (c) Next, resolve issue at boundaries of processor domains; add more advanced viz/analysis pipelines; (2) Halo finding/merger trees - (a) Summer student Wathsala W. from University of Utah is working on data-parallel halo finder algorithm using PISTON, (b) Timo Bremer (LLNL), Valerio Pascucci (Utah), George Zagaris (Kitware), and LANL people are interested in using merger trees for tracking the evolution of halos in cosmo simulations; discussed possible overlap with work by Salman Habib and Katrin Heitmann (Argonne) during their visit to LANL 7/11; (3) PISTON integration in ParaView - Now available from ParaView github.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Final Report

The purpose of this project was to develop tools and techniques to improve the ability of computational scientists to investigate and correct problems (bugs) in their programs. Specifically, the University of Maryland component of this project focused on the problems associated with the finite number of bits available in a computer to represent numeric values. In large scale scientific computation, numbers are frequently added to and multiplied with each other billions of times. Thus even small errors due to the representation of numbers can accumulate into big errors. However, using too many bits to represent a number results in additional computation, memory, and energy costs. Thus it is critical to find the right size for numbers. This project focused on several aspects of this general problem. First, we developed a tool to look for cancelations, the catastrophic loss of precision in numbers due to the addition of two numbers whose actual values are close to each other, but whose representation in a computer is identical or nearly so. Second, we developed a suite of tools to allow programmers to identify exactly how much precision is required for each operation in their program. This tool allows programmers to both verify that enough precision is available, but more importantly find cases where extra precision could be eliminated to allow the program to use less memory, computer time, or energy. These tools use advanced binary modification techniques to allow the analysis of actual optimized code. The system, called Craft, has been applied to a number of benchmarks and real applications.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

DEGAS: Dynamic Exascale Global Address Space Programming Environments

The Dynamic, Exascale Global Address Space programming environment (DEGAS) project will develop the next generation of programming models and runtime systems to meet the challenges of Exascale computing. The Berkeley part of the project concentrated on communication-optimal code generation to optimize speed and energy efficiency by reducing data movement. Our work developed communication lower bounds, and/or communication avoiding algorithms (that either meet the lower bound, or do much less communication than their conventional counterparts) for a variety of algorithms, including linear algebra, machine learning and genomics. The Berkeley part of the project concentrated on communication-optimal code generation to optimize speed and energy efficiency by reducing data movement. Our work developed communication lower bounds, and/or communication avoiding algorithms (that either meet the lower bound, or do much less communication than their conventional counterparts) for a variety of algorithms, including linear algebra, machine learning and genomics.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Investigating Fission Reaction Rate Ratio Sensitivities [Slides]

One EUCLID project goal is to create a NEW capability in the MCNP6 code. This is being tested on reaction rate sensitivities and compared with SENSMG results. Reaction rate ratio sensitivities were added to EUCLID sensitivity library and investigated to determine value toward designing optimized experiments aimed at reducing compensating errors in nuclear data. The use of adjustment using multiple responses (and underlying/required capabilities) may benefit many applications. These include a tool for adjustment using multiple integral responses (ND adjustment and validation community); sensitivities of additional responses (ND adjustment and validation community); sensitivity capabilities (users in many application areas including safeguards/nonproliferation, criticality safety, etc.); and experiment optimization capability (applications which can benefit from integral experiments). Team is working to build and test future tools and to understand compensating errors

235U↗

DOE OSTI2023

ORNL’s Continuing Efforts in Evaluating and Validating TSLs [Slides]

This presentation finds that INS measurements are not as variable based on sample composition, because phonon spectra is a properly of the bulk material. Additionally, INS and transmission measurements are and should be the most significant part of TSL validation, as they are the fundamental quantities used by Monte Carlo neutronics codes. This presentation reasons that relaying solely on theoretical atomistic calculations for TSL evaluation is not enough, they are highly dependent on inter-atomic potentials (which are not the most accurate depending on the quantity trying to be reproduced) and evaluators knowledge and understanding of the material being studied. Finally on Critical benchmarks, while extremely useful for validation of nuclear data at all energies, critical benchmarks are not the best tool to provide a definitive answer on conflicting TSLs. The presentation concludes that INS and transmission measurements need to be the basis of validation of TSLs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2014

Modernization Enhancements in SCALE 6.2

SCALE is a widely used suite of tools for nuclear systems modeling and simulation that provides comprehensive, verified and validated, user-friendly capabilities for criticality safety, reactor physics, radiation shielding, and sensitivity and uncertainty analysis. For more than 30 years, regulators, industry, and research institutions around the world have used SCALE for nuclear safety analysis and design. However, the underlying architecture of SCALE is based on a 40-year old design with dozens of independent functional modules and control programs, primarily implemented in the Fortran programming language, with extensive use of customized intermediate files to control the logical flow of the analysis. Data are passed between individual computational codes using custom binary files that are read from and written to the hard disk. The SCALE modernization plan provides a progression towards SCALE 7, which will provide an object-oriented parallel-enabled software infrastructure with state-of-the-art methods implemented as reusable components. This paper provides a brief overview of the goals of SCALE modernization and details some modernized features available with SCALE 6.2.

modern↗

DOE OSTI2023

Application of a Density Law via Python for Aqueous Plutonium Nitrate

A predictive density tool has been developed in Python to reduce bias and uncertainty in nuclear criticality safety calculations for plutonium nitrate systems. The Pitzer Method and an empirical method were implemented into the tool, allowing for plutonium nitrate density calculations. Additionally, the Python tool can generate atom densities for a MCNP6.2 material card using the density from the selected method and directly the densities into a prepared MCNP6 input text file. The material card and density are calculated based on customizable user inputs of plutonium content, nitric acid content, temperature, plutonium isotope weight percentages and impurity concentrations. The Python tool has been validated and verified against the International Handbook of Evaluated Criticality Safety Benchmark Experiments to predict densities within a root mean square error of 1.0% for the Pitzer method and 1.8% for the empirical method. These errors in density were shown to lead to a ±0.5% error in MCNP6.2 calculated k effective for the Pitzer method and a ±1.7% error for the Empirical method. Simultaneous work is also being done at the University of New Mexico and Los Alamos National Laboratory to create a similar tool for plutonium chloride solutions, which aims to provide the accreditation of the chlorine absorption. These capabilities will not only provide more accurate models but also lead the way towards a better understanding of solution systems and potential relaxation in the conservatism of the current aqueous plutonium processing limits.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Hyper-Heuristics to Automatically Target Code to Computer Architectures

With each new generation of High Performance Computing (HPC) architecture, the gap between peak theoretical performance and the observed performance is growing. The goal of this research is to develop a tool to utilize hyper-heuristics to target code to a computational environment. In order to test this, sorting algorithms will be evolved on several different architectures. The final solutions will then migrate to all other architectures and their fitnesses compared. If the natively-evolved algorithms out-perform all others, then it can be concluded that the tool successfully targeted its solutions to the architecture of origin. This is the first step towards creating a program-agnostic tool for optimizing code to the native environment. The results are pending testing on the high performance cluster. If it can be shown that the tool is able to optimize solutions for the environment, then the door opens to automatically optimizing entire programs.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Student-Friendly Guide to Molecular Integrals

Preceding even the Hartree–Fock method, molecular integrals are the very foundation upon which quantum chemical molecular modeling depends. Discussions of molecular integrals are normally found only in advanced and technical texts or articles. The objective of the present article is to provide less experienced readers, or students in a physical/computational chemistry course, a thorough understanding of molecular integrals. Through a series of detailed Handouts, the student/reader can participate in the derivation of molecular integrals, and in turn implement them in computer code. Hartree–Fock theory is discussed in enough detail to motivate the molecular integrals and address such topics as the atomic orbital basis. An introduction to the programming language of choice, Python3, is provided, tailored toward developing the essential skills necessary for implementing molecular integrals. In conclusion, the article is intended to be useful not only to instructors of physical/computational chemistry, but also to any reader who has independently sought a primer on this elusive subject.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Scalable Failure Masking for Stencil Computations using Ghost Region Expansion and Cell to Rank Remapping

In order to achieve exascale systems, application resilience needs to be addressed. Some programming models, such as task-DAG (directed acyclic graphs) architectures, currently embed resilience features whereas traditional SPMD (single program, multiple data) and message-passing models do not. Since a large part of the community's code base follows the latter models, it is still required to take advantage of application characteristics to minimize the overheads of fault tolerance. To that end, this paper explores how recovering from hard process/node failures in a local manner is a natural approach for certain applications to obtain resilience at lower costs in faulty environments. In particular, this paper targets enabling online, semitransparent local recovery for stencil computations on current leadership-class systems as well as presents programming support and scalable runtime mechanisms. Also described and demonstrated in this paper is the effect of failure masking, which allows the effective reduction of impact on total time to solution due to multiple failures. Furthermore, we discuss, implement, and evaluate ghost region expansion and cell-to-rank remapping to increase the probability of failure masking. To conclude, this paper shows the integration of all aforementioned mechanisms with the S3D combustion simulation through an experimental demonstration (using the Titan system) of the ability to tolerate high failure rates (i.e., node failures every five seconds) with low overhead while sustaining performance at large scales. In addition, this demonstration also displays the failure masking probability increase resulting from the combination of both ghost region expansion and cell-to-rank remapping.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

PETSc Users Manual (Rev. 3.3)

This manual describes the use of PETSc for the numerical solution of partial differential equations and related problems on high-performance computers. The Portable, Extensible Toolkit for Scientific Computation (PETSc) is a suite of data structures and routines that provide the building blocks for the implementation of large-scale application codes on parallel (and serial) computers. PETSc uses the MPI standard for all message-passing communication. PETSc includes an expanding suite of parallel linear, nonlinear equation solvers and time integrators that may be used in application codes written in Fortran, C, C++, Python, and MATLAB (sequential). PETSc provides many of the mechanisms needed within parallel application codes, such as parallel matrix and vector assembly routines. The library is organized hierarchically, enabling users to employ the level of abstraction that is most appropriate for a particular problem. By using techniques of object-oriented programming, PETSc provides enormous flexibility for users. PETSc is a sophisticated set of software tools; as such, for some users it initially has a much steeper learning curve than a simple subroutine library. In particular, for individuals without some computer science background, experience programming in C, C++ or Fortran and experience using a debugger such as gdb or dbx, it may require a significant amount of time to take full advantage of the features that enable efficient software use. However, the power of the PETSc design and the algorithms it incorporates may make the efficient implementation of many application codes simpler than “rolling them” yourself; For many tasks a package such as MATLAB is often the best tool; PETSc is not intended for the classes of problems for which effective MATLAB code can be written. PETSc also has a MATLAB interface, so portions of your code can be written in MATLAB to “try out” the PETSc solvers. The resulting code will not be scalable however because currently MATLAB is inherently not scalable; and PETSc should not be used to attempt to provide a “parallel linear solver” in an otherwise sequential code. Certainly all parts of a previously sequential code need not be parallelized but the matrix generation portion must be parallelized to expect any kind of reasonable performance. Do not expect to generate your matrix sequentially and then “use PETSc” to solve the linear system in parallel. Since PETSc is under continued development, small changes in usage and calling sequences of routines will occur. PETSc is supported; see the web site http://www.mcs.anl.gov/petsc for information on contacting support. A http://www.mcs.anl.gov/petsc/publications may be found a list of publications and web sites that feature work involving PETSc. We welcome any reports of corrections for this document.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

PETSc Users Manual (Rev. 3.4)

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

PETSc Users Manual (Rev. 3.5)

This manual describes the use of PETSc for the numerical solution of partial differential equations and related problems on high-performance computers. The Portable, Extensible Toolkit for Scientific Computation (PETSc) is a suite of data structures and routines that provide the building blocks for the implementation of large-scale application codes on parallel (and serial) computers. PETSc uses the MPI standard for all message-passing communication. PETSc includes an expanding suite of parallel linear, nonlinear equation solvers and time integrators that may be used in application codes written in Fortran, C, C++, Python, and MATLAB (sequential). PETSc provides many of the mechanisms needed within parallel application codes, such as parallel matrix and vector assembly routines. The library is organized hierarchically, enabling users to employ the level of abstraction that is most appropriate for a particular problem. By using techniques of object-oriented programming, PETSc provides enormous flexibility for users. PETSc is a sophisticated set of software tools; as such, for some users it initially has a much steeper learning curve than a simple subroutine library. In particular, for individuals without some computer science background, experience programming in C, C++ or Fortran and experience using a debugger such as gdb or dbx, it may require a significant amount of time to take full advantage of the features that enable efficient software use. However, the power of the PETSc design and the algorithms it incorporates may make the efficient implementation of many application codes simpler than “rolling them” yourself. ;For many tasks a package such as MATLAB is often the best tool; PETSc is not intended for the classes of problems for which effective MATLAB code can be written. PETSc also has a MATLAB interface, so portions of your code can be written in MATLAB to “try out” the PETSc solvers. The resulting code will not be scalable however because currently MATLAB is inherently not scalable; and PETSc should not be used to attempt to provide a “parallel linear solver” in an otherwise sequential code. Certainly all parts of a previously sequential code need not be parallelized but the matrix generation portion must be parallelized to expect any kind of reasonable performance. Do not expect to generate your matrix sequentially and then “use PETSc” to solve the linear system in parallel. Since PETSc is under continued development, small changes in usage and calling sequences of routines will occur. PETSc is supported; see the web site http://www.mcs.anl.gov/petsc for information on contacting support. A http://www.mcs.anl.gov/petsc/publications may be found a list of publications and web sites that feature work involving PETSc. We welcome any reports of corrections for this document.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Verifying MCNP Models of the TEX High 240 Plutonium Benchmark

Computational modeling programs are invaluable tools that allow us to understand systems, safely develop new processes, and make reliable predictions about future designs. However, the effectiveness of these codes is limited by the degree to which their parameters match the real world. In the field of nuclear engineering, cross section data is one of these vital parameters. Accurate cross section data on important fissile and fissionable isotopes promotes the design of safer and more efficient fabrication, transportation, storage, and stockpiling of nuclear fuel. Unfortunately, there are knowledge gaps in data on key isotopes. In 2011, a multinational meeting hosted by the US Department of Energy Nuclear Criticality Safety Program ranked the priority of certain cross section data needs. In response, Lawrence Livermore National Lab (LLNL) designed the Thermal and Epithermal eXperiment (TEX) series of benchmark experiments. Benchmark experiments are used to validate current cross section data. They validate data by comparing the results of an actual experiment to the predicted results from a computational model. The data a benchmark applies to depends on the isotope and energy range the experiment’s neutron multiplication factor ( k eff ) is most sensitive to. The development and testing of the TEX High 240 Plutonium Benchmark will help validate 240 Pu cross section data. The configuration and materials of this benchmark are designed to be most sensitive to 240 Pu's intermediate energy range (from 0.625 ev to 100 keV ). MCNP® models of the assembly have been developed by LLNL and the results have been written in the final design report. In order for the discrepancies between benchmark models and experiments to be attributed to cross section inaccuracies, the accuracy of the models needs to be verified. The goal of this project is to verify of the results of LLNL's modeling by creating a new set of MCNP models and comparing the results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2015

Report on results of current and future metal casting

New modeling capabilities needed to simulate the casting of metallic fuels are added to Truchas code. In this report we summarize improvements we made in FY2015 in three areas; (1) Analysis of new casting experiments conducted with BCS and EFL designs, (2) the simulation of INL’s U-Zr casting experiments with Flow3D computer program, (3) the implementation of surface tension model into Truchas for unstructured mesh required to run U-Zr casting.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

NCSP Analytical Methods Subtask 3, AMPX Development and Maintenance, and NCSP Nuclear Data Subtask 6, SAMMY Modernization

The modernization of SAMMY continued with the removal of all container array access for the main program. The container array was used due to the computer limitations at the time of the initial writing of SAMMY, but it prevented the use of some modern code testing options. Additionally, the authors continued to make the code more modular by shifting the storage of the energy grid and the covariance information to C++ storage, thus allowing for better unit testing and the elimination of scratch files. For AMPX, the authors continued to implement the new Evaluated Nuclear Data File format to allow AMPX to read new evaluations as they become available.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

On a Simplified Approach to Achieve Parallel Performance and Portability Across CPU and GPU Architectures

This paper presents software advances to easily exploit computer architectures consisting of a multi-core CPU and CPU+GPU to accelerate diverse types of high-performance computing (HPC) applications using a single code implementation. The paper describes and demonstrates the performance of the open-source C++ matrix and array (MATAR) library that uniquely offers: (1) a straightforward syntax for programming productivity, (2) usable data structures for data-oriented programming (DOP) for performance, and (3) a simple interface to the open-source C++ Kokkos library for portability and memory management across CPUs and GPUs. The portability across architectures with a single code implementation is achieved by automatically switching between diverse fine-grained parallelism backends (e.g., CUDA, HIP, OpenMP, pthreads, etc.) at compile time. The MATAR library solves many longstanding challenges associated with easily writing software that can run in parallel on any computer architecture. This work benefits projects seeking to write new C++ codes while also addressing the challenges of quickly making existing Fortran codes performant and portable over modern computer architectures with minimal syntactical changes from Fortran to C++. We demonstrate the feasibility of readily writing new C++ codes and modernizing existing codes with MATAR to be performant, parallel, and portable across diverse computer architectures.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Exploring the interoperability of remote GPGPU virtualization using rCUDA and directive-based programming models

Directive-based programming models, such as OpenMP, OpenACC, and OmpSs, enable users to accelerate applications by using coprocessors with little effort. These devices offer significant computing power, but their use can introduce two problems: an increase in the total cost of ownership and their underutilization because not all codes match their architecture. Remote accelerator virtualization frameworks address those problems. In particular, rCUDA provides transparent access to any graphic processor unit installed in a cluster, reducing the number of accelerators and increasing their utilization ratio. Joining these two technologies, directive-based programming models and rCUDA, is thus highly appealing. In this work, we study the integration of OmpSs and OpenACC with rCUDA, describing and analyzing several applications over three different hardware configurations that include two InfiniBand interconnections and three NVIDIA accelerators. Our evaluation reveals favorable performance results, showing low overhead and similar scaling factors when using remote accelerators instead of local devices.

97 MATHEMATICS AND COMPUTING↗