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At least 235 records · Page 13

Debugging Computer Code [Slides]

Debugging? Klingons do not debug. Our software does not coddle the weak. For the rest of us, finding and removing defects in code is a fundamental programming skill. Besides preventing code from performing its intended function, bugs destroy users’ confidence in the reliability of code even when no errors are obvious. A through discussion of debugging techniques could easily fill a semester course in computer science. We have an hour here today. I will take that time to discuss broad principles rather than fine points of debugging.

97 MATHEMATICS AND COMPUTING↗

A feasibility study on porting the community land model onto accelerators using OpenACC

As environmental models (such as Accelerated Climate Model for Energy (ACME), Parallel Reactive Flow and Transport Model (PFLOTRAN), Arctic Terrestrial Simulator (ATS), etc.) became more and more complicated, we are facing enormous challenges regarding to porting those applications onto hybrid computing architecture. OpenACC appears as a very promising technology, therefore, we have conducted a feasibility analysis on porting the Community Land Model (CLM), a terrestrial ecosystem model within the Community Earth System Models (CESM)). Specifically, we used automatic function testing platform to extract a small computing kernel out of CLM, then we apply this kernel into the actually CLM dataflow procedure, and investigate the strategy of data parallelization and the benefit of data movement provided by current implementation of OpenACC. Even it is a non-intensive kernel, on a single 16-core computing node, the performance (based on the actual computation time using one GPU) of OpenACC implementation is 2.3 time faster than that of OpenMP implementation using single OpenMP thread, but it is 2.8 times slower than the performance of OpenMP implementation using 16 threads. On multiple nodes, MPI_OpenACC implementation demonstrated very good scalability on up to 128 GPUs on 128 computing nodes. This study also provides useful information for us to look into the potential benefits of “deep copy” capability and “routine” feature of OpenACC standards. In conclusion, we believe that our experience on the environmental model, CLM, can be beneficial to many other scientific research programs who are interested to porting their large scale scientific code using OpenACC onto high-end computers, empowered by hybrid computing architecture.

54 ENVIRONMENTAL SCIENCES↗

Realizing High-Performance Parallel Computing Final Report CRADA No. TC-0319-92

The objectives of this project were to improve the programming environment for scientific applications on shared-memory (SMP) and massively-parallel (MMP) computer systems and to develop high-performance, parallel rational drug design applications. The collaborators, IBM Corp., BioNumerik Pharmaceuticals (BNP), and Lawrence Livermore National Laboratory (LLNL), each brought unique expertise to the project. IBM contributed state-of-the-art SMP and MMP computer systems; BNP provided proprietary quantum mechanical and statistical mechanical molecular dynamics codes and experimental data; and LLNL contributed its high-performance Sisal compilers, runtime systems, and programming tools.

97 MATHEMATICS AND COMPUTING↗

ZEM: Integrated Framework for Real-Time Data and Model Analyses for Robust Environmental Management Decision Making - 16438

Typically environmental management (EM) problems require analysis of large and complex data sets originating from concurrent data streams with different data collection frequencies and pedigree. These big data sets require on-the-fly analysis, assimilation and integration into a series of models with different complexity for various types of model-based analyses. This is needed to provide fast iterative model analyses based on the latest available data to guide decision-making. Furthermore, the data and model are associated with uncertainties. The uncertainties are probabilistic (e.g. measurement errors) and non-probabilistic (unknowns, e.g. alternative conceptual models characterizing site conditions). To address all of these issues, we have developed an integrated framework for real-time data and model analyses for environmental decision-making called ZEM. The framework allows for seamless and on-the-fly integration of data and modeling results for robust and scientifically-defensible decision-making applying advanced decision analyses tools such as Bayesian-Information-Gap Decision Theory (BIG-DT). The framework also includes advanced methods for optimization that are capable of dealing with a large number of unknown model parameters, and surrogate (reduced order) modeling capabilities based on support vector regression techniques. The framework is predominantly coded in Julia, a state-of-the-art high-performance programing language (http://julialang.org) and incorporates the MADS computational tools (Model Analysis and Decision Support; http://mads.lanl.gov). We demonstrate the application of ZEM for data and model analyses at the LANL Chromium site. The ZEM framework will be released as open-source code and can be applied to any environmental management site. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

SIERRA Multimechanics Module: Aria Thermal Theory Manual - Version 4.48

This document describes the theoretical foundation of thermal analysis in Sierra Mechanics. The SIERRA Multimechanics Module: Aria, henceforth referred to as Aria for brevity, was developed at Sandia National Laboratories under the ASC program, and approximates linear and nonlinear continuum models of heat transfer. Aria uses the SIERRA Framework, which provides data management services commonly required by computational mechanics software, and facilitates the development of coupled, multi-mechanics applications for massively parallel computers. The mathematical models in Aria are based heavily on those of COYOTE, a well-established thermal analysis program that was also developed at Sandia and its ASC code predecessor, Calore. Aria, Calore and COYOTE share a significant body of numerical methods, which are described in detail by Reddy and Gartling. Throughout this document, the terms software and implementation are syn onymous with the Aria thermal-fluid analysis computer program. Whether one uses Aria to perform heat transfer analysis, or in developing a new capability for the Aria application, this document provides the information needed understand the existing numerical algorithm implementations. Justification for the fundamental assumptions of heat transfer, nor derivation of the energy conservation equations are included in this document. For a more thorough theoretical background, one is referred to one of the many available textbooks, e.g. Another reference, which is freely available in downloadable electronic form, is Lienhard and Lienhard.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Investigation of Heterogeneity Effects on Calculated Sensitivities of the ZPPR-15B Assemblies

In past years, sensitivity studies of ZPR and ZPPR assemblies were carried out with deterministic codes for several purposes, such as uncertainty estimation of calculated parameter values, cross section adjustment, representativity analysis. etc. However, these sensitivity studies used simplified R-Z models of ZPR/ZPPR assemblies where the multi-group cross section data was obtained from the homogenized material compositions of each reactor zone. The main reason for this simplification was the lack of a deterministic path able to compute sensitivity coefficients for complicated 3D geometries in transport theory. Also, each ZPR and ZPPR assembly consists of several different drawers each containing different plate types and plate arrangements and it was felt that performing sensitivity calculations with an equivalent R-Z reactor model would capture most of the feedback while the heterogeneity effects were believed to be of second order. Recently a new code, BuildZPRModel, was developed at ANL that automatically generates the inputs for cross section processing and core calculation of heterogeneous ZPR and ZPPR assemblies for 3D transport calculations. Additionally, the PERSENT code (recently developed at ANL as well) is able to carry out sensitivity calculations in transport theory on 3D geometries. With the benefit of the newly developed codes, a sensitivity study was performed for the heterogeneous model of ZPPR-15B assemblies 96 and 102 generated by BuildZPRModel. The results were compared with the sensitivities computed with the use of fully homogenized R-Z reactor models, in order to quantify the impact of heterogeneity effects neglected in the analysis performed in past years.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Compiler and Runtime Approaches to Enable Large-Scale Irregular Programs. Final report, July 2013 - July 2019

While regular algorithms, characterized by operations on dense matrices and arrays, have long been the mainstay of scientific, high-performance computing, irregular algorithms, which feature unpredictable accesses to pointer-based data structures, are becoming increasingly common in high performance computing, arising in graph analysis, data mining and visualization, among other domains. Unfortunately, the defining characteristics of irregular applications, their dynamic, unpredictable, data-dependent access patterns and data layouts, make achieving high performance on large scale systems difficult. Scaling applications to peta- and exa-scale requires carefully controlling communication and data movement and placement, an inherently difficult task when access patterns and data layouts are unpredictable! Most irregular applications that attain high performance must be painstakingly hand-written and hand-tuned, with few common principles or paradigms uniting various implementations and easing future development. Despite the increasing importance of irregular applications, there is little programmer knowledge, and even less compiler ability, devoted to optimizing them. This project aims to solve these problems. By allowing programmers to write irregular applications in high level forms, with at most a few annotations highlighting key structural properties, programmers can focus on developing their algorithms and methods. The compiler and run-time system can take on the tedious task of optimizing the application for execution at large scales, and can automatically provide efficient implementations. This will provide portability and ease maintenance for existing irregular applications, but, more importantly, open up whole new domains of computational science to large-scale, high-performance simulation codes.

97 MATHEMATICS AND COMPUTING↗

Review of Transient Testing of Fast Reactor Fuels in the Transient REActor Test Facility (TREAT)

The restart of the Transient REActor Test (TREAT) facility provides a unique opportunity to engage the fast reactor fuels community to reinitiate in-pile experimental safety studies. Historically, the TREAT facility played a critical role in characterizing the behavior of both metal and oxide fast reactor fuels under off-normal conditions, irradiating hundreds of fuel pins to support fast reactor fuel development programs. The resulting test data has provided validation for a multitude of fuel performance and severe accident analysis computer codes. This paper will provide a review of the historical database of TREAT experiments including experiment design, instrumentation, test objectives, and salient findings. Additionally, the paper will provide an introduction to the current and future experiment plans of the U.S. transient testing program at TREAT.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

CSRI Summer Proceedings 2021

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia National Laboratories for focused collaborative research on Department of Energy (DOE) computer and computational science problems. The institute provides an opportunity for university researches to learn about problems in computer and computational science at DOE laboratories, and help transfer results of their research to programs at the labs. Some specific CSRI research interest areas are: scalable solvers, optimization, algebraic preconditioners, graph-based, discrete, and combinatorial algorithms, uncertainty estimation, validation and verification methods, mesh generation, dynamic load-balancing, virus and other malicious-code defense, visualization, scalable cluster computers, beyond Moore’s Law computing, exascale computing tools and application design, reduced order and multiscale modeling, parallel input/output, and theoretical computer science. The CSRI Summer Program is organized by CSRI and includes a weekly seminar series and the publication of a summer proceedings.

97 MATHEMATICS AND COMPUTING↗

CSRI Summer Proceedings 2021

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia National Laboratories for focused collaborative research on Department of Energy (DOE) computer and computational science problems. The institute provides an opportunity for university researches to learn about problems in computer and computational science at DOE laboratories, and help transfer results of their research to programs at the labs. Some specific CSRI research interest areas are: scalable solvers, optimization, algebraic preconditioners, graph-based, discrete, and combinatorial algorithms, uncertainty estimation, validation and verification methods, mesh generation, dynamic load-balancing, virus and other malicious-code defense, visualization, scalable cluster computers, beyond Moore’s Law computing, exascale computing tools and application design, reduced order and multiscale modeling, parallel input/output, and theoretical computer science. The CSRI Summer Program is organized by CSRI and includes a weekly seminar series and the publication of a summer proceedings.

97 MATHEMATICS AND COMPUTING↗

An extension to V ORO ++ for multithreaded computation of Voronoi cells

V ORO ++ is a software library written in C++ for computing the Voronoi tessellation, a technique in computational geometry that is widely used for analyzing systems of particles. V ORO ++ was released in 2009 and is based on computing the Voronoi cell for each particle individually. Here, we take advantage of modern computer hardware, and extend the original serial version to allow for multithreaded computation of Voronoi cells via the OpenMP application programming interface. We test the performance of the code, and demonstrate that it can achieve parallel efficiencies greater than 95% in many cases. Further, the multithreaded extension follows standard OpenMP programming paradigms, allowing it to be incorporated into other programs. We provide an example of this using the VoroTop software library, performing a multithreaded Voronoi cell topology analysis of up to 102.4 million particles.

97 MATHEMATICS AND COMPUTING↗

The CCONE Code System and its Application to Nuclear Data Evaluation for Fission and Other Reactions

A computer code system, CCONE, was developed for nuclear data evaluation within the JENDL project. The CCONE code system integrates various nuclear reaction models needed to describe nucleon, light charged nuclei up to alpha-particle and photon induced reactions. The code is written in the C++ programming language using an object-oriented technology. At first, it was applied to neutron-induced reaction data on actinides, which were compiled into JENDL Actinide File 2008 and JENDL-4.0. It has been extensively used in various nuclear data evaluations for both actinide and non-actinide nuclei. The CCONE code has been upgraded to nuclear data evaluation at higher incident energies for neutron-, proton-, and photon-induced reactions. It was also used for estimating β-delayed neutron emission. This paper describes the CCONE code system indicating the concept and design of coding and inputs. Details of the formulation for modelings of the direct, pre-equilibrium and compound reactions are presented. Applications to the nuclear data evaluations such as neutron-induced reactions on actinides and medium-heavy nuclei, high-energy nucleon-induced reactions, photonuclear reaction and β-delayed neutron emission are mentioned.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Preface to the Special Issue on TOUGH Symposium 2015

The TOUGH Symposium 2015 was held in Berkeley, California, September 28-30, 2015. The TOUGH family of codes, developed at the Energy Geosciences Division of Lawrence Berkeley National Laboratory (LBNL), is a suite of computer programs for the simulation of multiphase and multicomponent fluid and heat flows in porous and fractured media with applications in many geosciences fields, such as geothermal reservoir engineering, nuclear waste disposal, geological carbon sequestration, oil and gas reservoirs, gas hydrate research, vadose zone hydrology and environmental remediation. Since the first release in the 1980s, many modifications and enhancements have been continuously made to TOUGH and its various descendants (iTOUGH2, TOUGH+, TOUGH-MP, TOUGHREACT, TOUGH+HYDRATE, TMVOC...), at LBNL and elsewhere. Today, these codes are used worldwide in academia, government organizations and private companies in problems involving coupled hydrological, thermal, biogeochemical and geomechanical processes. The Symposia, organized every 2-3 years, bring together developers and users for an open exchange on recent code enhancements and applications. In 2015, the Symposium was attended by one hundred participants, representing thirty-four nationalities. This Special Issue in Computers & Geosciences gathers extended versions of selected Symposium proceedings related to (i) recent enhancements to the TOUGH family of codes and (ii) coupled flow and geomechanics processes modeling. In this special issue, a paper by Jung et al. provides a new base version of TOUGH, TOUGH3. This latest version addresses the computational robustness and efficiency needed for the increasing complexity of the simulated processes and the growing size of model domains. Moreover, it consolidates the serial and parallel versions into a single code, hence, inconsistencies between different versions are less likely to occur, and code maintenance and development become more efficient. Finsterle et al. present a review of the capabilities of iTOUGH2 and illustrate the workflow of an integrated simulation-optimization framework. Liu et al. present an approach to reduce the computational cost of performing Bayesian inverse modeling and demonstrate their approach using a synthetic experiment simulated with TOUGH2. Regarding the mesh generation process, the paper by Doughty presents a generalization of the grid-generation algorithm embedded in TOUGH2 (MESHMAKER) to create one-column grids with fractal dimension, useful for representing flow through fractures or highly heterogeneous media with fractal geometry, and also for inverse methods. Sentís and Gable present a module to interface the open source code Lagrit with TOUGH2, that assists in the processes of mesh generation and model setup, and that can be particularly useful for complex geometries and large models. Bonduà et al. present a pre-processing tool (VORO2MESH) that features a full 3D Voronoi approach for structured and unstructured grids, and an enhanced post-processor (TOUGH2Viewer) for the visualization of 3D Voronoi grids. The literature review shows that coupled fluid flow and geomechanics has gained increasing attention in the last years in many geosciences fields. In this context, several codes of the TOUGH family have been successfully coupled with geomechanics software. The paper by Rutqvist presents a review of some of these TOUGH-based geomechanics models, of which the TOUGH-FLAC simulator – presented for the first time in the TOUGH Symposium 2003 – is well-known worldwide and has been used in a large variety of applications, encompassing the application domains of the TOUGH codes. Blanco-Martín et al. present an extension of TOUGH-FLAC to the finite strain framework, motivated by the existence of large strains associated with rock salt deformation in the context of heat-generating nuclear waste disposal. Following a paper published in the Special Issue of the TOUGH Symposium 2012 in this journal, Kim et al. present the current status of the TOUGH-RSBN simulator for coupled hydro-mechanical modeling of hydraulic fracturing using a discrete fracture network approach, and present some validation and demonstration cases. Rinaldi and Nespoli present TOUGH-SEED, an injection-induced seismicity modeling approach using TOUGH2 and a geomechanics stochastic model, and apply it to the Basel EGS project. Finally, Rinaldi et al. use the PEST protocol implemented in iTOUGH2, combined with TOUGH-FLAC as the forward model, to perform inverse modeling for the In Salah CO2 demonstration site in Algeria. Using pore pressures and InSAR displacements as observations, this approach allows for a multi-physics joint inversion and takes advantage of the inverse capabilities of iTOUGH2 (parameter estimation, sensitivity analysis, uncertainty estimation …), applied to coupled fluid flow and geomechanics. On behalf of the members of the TOUGH Symposium 2015 Organizing Committee, I hope that this collection of papers will provide the readers of Computers & Geosciences with a recent view of the capabilities of the TOUGH family of codes, as well as with current modeling research domains in the geosciences. Last but not least, I would like to express my gratitude to all the reviewers who kindly contributed to this Special Issue, as well as the Journal staff who have made this publication possible.

99 GENERAL AND MISCELLANEOUS↗

MCNP® Code Version 6.3.1: Build Guide (Rev. 1)

This is a build guide for the MCNP® code, version 6.3.1, that expands upon the README.md included with the source code. It covers compilers, dependencies, building, testing, and installing the code in one of its supported configurations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Parallel Monte Carlo Methods for Heterogeneous Hardware Computer Systems Using GPUs and Coprocessors: Recent Development of ARCHER Code - Paper 54

Traditional methods of accelerating Monte Carlo (MC) calculations typically use CPUs as the computing unit. The parallelism is based upon multithreading on a multi-core processor, and message passing interface (MPI) across many processors and nodes. In recent years, the hardware accelerators have been introduced by the high performance computing industry as an alternative approach to achieve massive parallelism. Hardware accelerators have the advantage of high Floating-point Operations Per Second (FLOPS) and high energy efficiency. Examples include graphics processing units (GPUs) and coprocessors. Compute-intensive programs can be off-loaded to them to be concurrently executed by hundreds or thousands of active threads. Existing production MC codes, however, cannot be directly compiled or executed on the new platforms. It is therefore necessary to rewrite or redevelop the code using the hardware accelerator specific programming models and APIs. Several studies have been conducted on using GPUs to accelerate MC calculations in reactor analysis and medical physics. In this paper, we present the recent progress at Rensselaer Polytechnic Institute (RPI) in developing a new parallel MC code called ARCHER (Accelerated Radiation-transport Computations in Heterogeneous Environments) for coupled photon-electron transport simulations. The code is designed as a test bed to evaluate the efficacy of heterogeneous computing systems for low-cost MC-based radiation dosimetric calculations. The code has three variants corresponding to three parallel hardware platforms: ARCHER-CPU (multi-core CPU), ARCHER-GPU (Nvidia GPU) and ARCHER-COP (Intel Xeon Phi coprocessor). The code has been used for several applications, including CT imaging dosimetry, radiotherapy dosimetry and radiation shielding design. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

Thermal Neutron Scattering Law (TNSL) Implementation and Testing in FUDGE

Thermal neutron scattering law processing capabilities have been recently implemented in the LLNL code FUDGE (For Updating Data and Generating Evaluations). FUDGE is now capable of producing processed TNSL data for use in Monte Carlo or deterministic transport. To test this new capability, LLNL scientists performed an extensive intercomparison between the Mercury, Ardra, COG and MCNP transport codes. This intercomparison helped probe differences between how TNSL data are handled by the transport codes and by two different processing codes (LLNL’s FUDGE and LANL’s NJOY). This report summarizes recent improvements in FUDGE TNSL capabilities as well as results from the code intercomparison.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Spherical Radiative Transfer in C++ (SRTC++): A Parallel Monte Carlo Radiative Transfer Model for Titan

We present a new computer program, SRTC++, to solve spatial problems associated with explorations of Saturn’s moon Titan. The program implements a three-dimensional structure well-suited to addressing shortcomings arising from plane-parallel radiative transfer approaches. SRTC++'s design uses parallel processing in an object-oriented, compiled computer language (C++) leading to a flexible and fast architecture. We validate SRTC++ using analytical results, semianalytical radiative transfer expressions, and an existing Titan plane-parallel model. SRTC++ complements existing approaches, addressing spatial problems like near-limb and near-terminator geometries, non-Lambertian surface phase functions (including specular reflections), and surface albedo nonuniformity.

97 MATHEMATICS AND COMPUTING↗

OTERR User Manual

OTERR (Optimization of TEst Reactor Reloading) is a software tool created to assist in the determination of optimal fuel reloading patterns for test reactors. The intended application is for the Versatile Test Reactor (VTR) program, but it provides functions that could be useful for analysis and optimization of many types of fast reactors. OTERR does not perform neutron/gamma transport, heat transfer, thermal hydraulics, or depletion calculations. Instead, it acts as a wrapper around codes that provide these capabilities, with a native genetic algorithm optimization capability. At this time, wrapping is only implemented for Argonne Reactor Computation (ARC) codes DIF3D, REBUS, and GAMSOR, and SE2-ANL. OTERR also has capabilities to facilitate input creation for DASSH, a thermal hydraulics code similar to SE2- ANL being developed for the VTR program.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗