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DOE OSTI2021

Schema Elements for Granta Annual Report

Granta: Materials Intelligence, also known as Granta:MI or Granta, is a commercial database software by Ansys, Inc. that is utilized by the Nuclear Security Enterprise (NSE) to organize and store materials data relevant to the complex. The software was first adopted by individual sites in the early 2000’s, but in FY20, enterprise-wide licensing was purchased for the NSE by the Product Realization Integrated Digital Enterprise (PRIDE) program. Currently, there are 375 floating licenses available for users at all sites. There are also two shared instances of Granta; a classified production instance on the Enterprise Secure Network (ESN) and an unclassified development instance. Additionally, some individual sites such as Los Alamos National Laboratory (LANL), Lawrence Livermore National Laboratory (LLNL), Sandia National Laboratories (SNL), Kansas City National Security Campus (KCNSC), and Savannah River National Laboratory (SRNL) host their own local Granta instances on their own networks that, in general, only their employees can access.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Validating the simulation of large-scale parallel applications using statistical characteristics

Simulation is a widely adopted method to analyze and predict the performance of large-scale parallel applications. Validating the hardware model is highly important for complex simulations with a large number of parameters. Common practice involves calculating the percent error between the projected and the real execution time of a benchmark program. However, in a high-dimensional parameter space, this coarse-grained approach often suffers from parameter insensitivity, which may not be known a priori. Moreover, the traditional approach cannot be applied to the validation of software models, such as application skeletons used in online simulations. In this work, we present a methodology and a toolset for validating both hardware and software models by quantitatively comparing fine-grained statistical characteristics obtained from execution traces. Although statistical information has been used in tasks like performance optimization, this is the first attempt to apply it to simulation validation. Lastly, our experimental results show that the proposed evaluation approach offers significant improvement in fidelity when compared to evaluation using total execution time, and the proposed metrics serve as reliable criteria that progress toward automating the simulation tuning process.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Particle Swarm Optimization Algorithm for Critical Experiment Design

Nuclear criticality experiments are used to validate nuclear cross section data used by simulation software. This is typically achieved by designing a critical system with a high sensitivity to a certain material’s cross section. Once the experiment has been carried out, a high fidelity model of the system is developed into a benchmark. When this benchmark model is simulated by a transport code, some of the difference between the experimental and computational effective neutron multiplication factor can be attributed to inaccurate nuclear data. Nuclear data evaluators then can make adjustments accordingly to improve cross section data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2016

CHSalign: A Web Server That Builds upon Junction-Explorer and RNAJAG for Pairwise Alignment of RNA Secondary Structures with Coaxial Helical Stacking

RNA junctions are important structural elements of RNA molecules. They are formed when three or more helices come together in three-dimensional space. Recent studies have focused on the annotation and prediction of coaxial helical stacking (CHS) motifs within junctions. Here we exploit such predictions to develop an efficient alignment tool to handle RNA secondary structures with CHS motifs. Specifically, we build upon our Junction-Explorer software for predicting coaxial stacking and RNAJAG for modelling junction topologies as tree graphs to incorporate constrained tree matching and dynamic programming algorithms into a new method, called CHSalign, for aligning the secondary structures of RNA molecules containing CHS motifs. Thus, CHSalign is intended to be an efficient alignment tool for RNAs containing similar junctions. Experimental results based on thousands of alignments demonstrate that CHSalign can align two RNA secondary structures containing CHS motifs more accurately than other RNA secondary structure alignment tools. CHSalign yields a high score when aligning two RNA secondary structures with similar CHS motifs or helical arrangement patterns, and a low score otherwise. This new method has been implemented in a web server, and the program is also made freely available, at http://bioinformatics.njit.edu/CHSalign/.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Towards a Robust System-of-Systems Control Architecture for Robotics - 18359

This paper presents the methodology and results of developing and implementing a system-of-systems architecture for controlling many robotic systems within the context of industrial facilities, where the life of the facility will be far longer than the life of the robotics, due to software updates and accelerated digital obsolescence. The use cases are the JET and ITER fusion research reactors. Remote maintenance is both device defining and mission critical for a future fusion reactor and we foresee the need to utilise a considerable number of robotic devices within an overall digital control architecture. The paper will explore the challenges of long term management of digital complexity using the real experience of JET over the last 20 years. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2015

TU-AB-201-02: An Automated Treatment Plan Quality Assurance Program for Tandem and Ovoid High Dose-Rate Brachytherapy

Purpose: For tandem and ovoid (T&O) HDR brachytherapy in our clinic, it is required that the planning physicist manually capture ∼10 images during planning, perform a secondary dose calculation and generate a report, combine them into a single PDF document, and upload it to a record- and-verify system to prove to an independent plan checker that the case was planned correctly. Not only does this slow down the already time-consuming clinical workflow, the PDF document also limits the number of parameters that can be checked. To solve these problems, we have developed a web-based automatic quality assurance (QA) program. Methods: We set up a QA server accessible through a web- interface. A T&O plan and CT images are exported as DICOMRT files and uploaded to the server. The software checks 13 geometric features, e.g. if the dwell positions are reasonable, and 10 dosimetric features, e.g. secondary dose calculations via TG43 formalism and D2cc to critical structures. A PDF report is automatically generated with errors and potential issues highlighted. It also contains images showing important geometric and dosimetric aspects to prove the plan was created following standard guidelines. Results: The program has been clinically implemented in our clinic. In each of the 58 T&O plans we tested, a 14- page QA report was automatically generated. It took ∼45 sec to export the plan and CT images and ∼30 sec to perform the QA tests and generate the report. In contrast, our manual QA document preparation tooks on average ∼7 minutes under optimal conditions and up to 20 minutes when mistakes were made during the document assembly. Conclusion: We have tested the efficiency and effectiveness of an automated process for treatment plan QA of HDR T&O cases. This software was shown to improve the workflow compared to our conventional manual approach.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

ADEPT: a domain independent sequence alignment strategy for gpu architectures

Bioinformatic workflows frequently make use of automated genome assembly and protein clustering tools. At the core of most of these tools, a significant portion of execution time is spent in determining optimal local alignment between two sequences. This task is performed with the Smith-Waterman algorithm, which is a dynamic programming based method. With the advent of modern sequencing technologies and increasing size of both genome and protein databases, a need for faster Smith-Waterman implementations has emerged. Multiple SIMD strategies for the Smith-Waterman algorithm are available for CPUs. However, with the move of HPC facilities towards accelerator based architectures, a need for an efficient GPU accelerated strategy has emerged. Existing GPU based strategies have either been optimized for a specific type of characters (Nucleotides or Amino Acids) or for only a handful of application use-cases. In this paper, we present ADEPT, a new sequence alignment strategy for GPU architectures that is domain independent, supporting alignment of sequences from both genomes and proteins. Our proposed strategy uses GPU specific optimizations that do not rely on the nature of sequence. We demonstrate the feasibility of this strategy by implementing the Smith-Waterman algorithm and comparing it to similar CPU strategies as well as the fastest known GPU methods for each domain. ADEPT’s driver enables it to scale across multiple GPUs and allows easy integration into software pipelines which utilize large scale computational systems. We have shown that the ADEPT based Smith-Waterman algorithm demonstrates a peak performance of 360 GCUPS and 497 GCUPs for protein based and DNA based datasets respectively on a single GPU node (8 GPUs) of the Cori Supercomputer. Overall ADEPT shows 10x faster performance in a node-to-node comparison against a corresponding SIMD CPU implementation. ADEPT demonstrates a performance that is either comparable or better than existing GPU strategies. We demonstrated the efficacy of ADEPT in supporting existing bionformatics software pipelines by integrating ADEPT in MetaHipMer a high-performance denovo metagenome assembler and PASTIS a high-performance protein similarity graph construction pipeline. Our results show 10% and 30% boost of performance in MetaHipMer and PASTIS respectively.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2013

SciDAC-Center for Plasma Edge Simulation Report

The Common Component Architecture (CCA) effort is the embodiment of a long-range program of research and development into the formulation, roles, and use of component technologies in high-performance scientific computing. CCA components can interoperate with other components in a variety of frameworks, including SCIRun2 from the University of Utah. The SCIRun2 framework is also developing the ability to connect components from a variety of different models through a mechanism called meta-components. The meta component model operates by providing a plugin architecture for component models. Abstract components are manipulated and managed by the SCIRun2 framework, while concrete component models perform the actual work and communicate with each other directly. We will leverage the SCIRun2 framework and the Kepler system to orchestrate components in the Fusion Simulation Project (FSP) and to provide a CCA-based interface with Kepler. The groundwork for this functionality is being performed with the Scientific Data Management center. The SDM center is developing CCA-compliant interfaces for expressing and executing workflows and create workflow components based on SCIRun and Ptolemy (Kepler) execution engines, including development of uniform interfaces for selecting, starting, and monitoring scientific workflows. Accomplishments include Introduction to CCA and Simulation Software Systems, Introduction into SCIRun2 and Bridging within SCIRun2, CCALoop: A scalable design for a distributed component framework, and Combining Workflow methodologies with Component Architectures.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Scan2Sim: Software to Convert Network Scans to Emulations

Within operational technology (OT) systems design, the construction of testing environments for simulation is often a tedious, manual process that slows down safety and security evaluations. This document details the design and functionality of Scan2Sim, a program designed to construct high-fidelity topological schematics for OT systems without significant manual human input. Scan2Sim may take as input a detailed network scan of a system, and produces an instruction set to re-create the original scanned network within a virtualized simulation network. This construction is achieved via heuristic methods of machine template selection, which allows for a fast, performant approach to automated environment construction. The current tool is designed to produce topology schematics compatible with the Minimega, a tool designed by Sandia National Laboratories for repeatable experimentation management.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Correct Compilation of Concurrent C Code

The CompCert compiler represents a landmark effort in program verification as both a piece of verified software and as a compiler for verified C programs. A key shortcoming of CompCert however is that it does not support multithreaded programs. Prior work to add threads to CompCert has either required major rewrites of parts of the proof or only works for well synchronized programs. The problem is that CompCert’s backward simulation derives from a forward simulation via the determinism of the semantics of intermediate representation languages. This makes the proofs in CompCert easier but also makes them incompatible with standard models of multithreading which are non-deterministic. Here we propose an alternate formulation of CompCert’s proof structure that parameterizes the existing single threaded semantics with nondeterministic behavior generated at the multithreading level. While this is an old trick where program equivalence is concerned, performing it in the context of CompCert is quite subtle. Our approach allows for expressive concurrent semantics and does not require major proof rewrites but still results in a global backward simulation for multithreaded programs.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Simulation of the NaGd(MoO{sub 4}){sub 2}–NaEu(MoO{sub 4}){sub 2} and Na{sub 2}Gd{sub 4}(MoO{sub 4}){sub 7}–Na{sub 2}Eu{sub 4}(MoO{sub 4}){sub 7} Solid Solutions by the Interatomic Potential Method

Simulation of the solid solutions in the system of double sodium–gadolinium and sodium–europium molybdates, which are promising matrices for solid state lasers and phosphors has been carried out by the method of interatomic potentials. Two types of solid solutions have been studied, one of which contains finite components corresponding to the stoichiometric NaGd(MoO{sub 4}){sub 2}–NaEu(MoO{sub 4}){sub 2} compositions with statistical distribution of cations in the crystal lattice. Another object is a cation-deficient Na{sub 2}Gd{sub 4}(MoO{sub 4}){sub 7}–Na{sub 2}Eu{sub 4}(MoO{sub 4}){sub 7} system, in which we have examined the variants of statistical distribution and partial ordering of cations over structural positions. Atomistic simulation has been performed using the GULP 4.0.1 software package (General Utility Lattice Program). It is shown that when we pass from sodium-gadolinium molybdate to sodium-europium molybdate, both of stoichiometric and cation-deficient compositions, an increase in the unit cell volume is observed, while the density of the crystal, the energy of interatomic interactions in the structure, the vibrational entropy and the heat capacity decrease along with increasing europium content. The energy of interatomic interactions in the structure for cation-deficient solid solutions is less than for stoichiometric ones. Other aforementioned characteristics for cation-deficient solid solutions have greater values than for stoichiometric ones. The role of cluster europium centers in concentration quenching in NaGd(MoO{sub 4}){sub 2}–NaEu(MoO{sub 4}){sub 2} solid solutions has been examined.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2017

Virtual sensors for robust on-line monitoring (OLM) and diagnostics - 197

Unscheduled shutdown of nuclear power facilities for recalibration and replacement of faulty sensors can be expensive and disruptive to grid management. In this work, we present virtual (software) sensors that can replace a faulty physical sensor for a short duration thus allowing recalibration to be safely deferred to a later time. The virtual sensor model uses a Gaussian process model to process input data from redundant and other nearby sensors. Predicted data includes uncertainty bounds including spatial association uncertainty and measurement noise and error. Using data from an instrumented cooling water flow loop test bed, the virtual sensor model has predicted correct sensor measurements and the associated error corresponding to a faulty sensor. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

Extreme-Scale Algorithms & Software Resilience (EASIR) Architecture-Aware Algorithms for Scalable Performance and Resilience on Heterogeneous Architectures

This project addresses both communication-avoiding algorithms, and reproducible floating-point computation. Communication, i.e. moving data, either between levels of memory or processors over a network, is much more expensive per operation than arithmetic (measured in time or energy), so we seek algorithms that greatly reduce communication. We developed many new algorithms for both dense and sparse, and both direct and iterative linear algebra, attaining new communication lower bounds, and getting large speedups in many cases. We also extended this work in several ways: (1) We minimize writes separately from reads, since writes may be much more expensive than reads on emerging memory technologies, like Flash, sometimes doing asymptotically fewer writes than reads. (2) We extend the lower bounds and optimal algorithms to arbitrary algorithms that may be expressed as perfectly nested loops accessing arrays, where the array subscripts may be arbitrary affine functions of the loop indices (eg A(i), B(i,j+k, k+3*m-7, …) etc.). (3) We extend our communication-avoiding approach to some machine learning algorithms, such as support vector machines. This work has won a number of awards. We also address reproducible floating-point computation. We define reproducibility to mean getting bitwise identical results from multiple runs of the same program, perhaps with different hardware resources or other changes that should ideally not change the answer. Many users depend on reproducibility for debugging or correctness. However, dynamic scheduling of parallel computing resources, combined with nonassociativity of floating point addition, makes attaining reproducibility a challenge even for simple operations like summing a vector of numbers, or more complicated operations like the Basic Linear Algebra Subprograms (BLAS). We describe an algorithm that computes a reproducible sum of floating point numbers, independent of the order of summation. The algorithm depends only on a subset of the IEEE Floating Point Standard 754-2008, uses just 6 words to represent a “reproducible accumulator,” and requires just one read-only pass over the data, or one reduction in parallel. New instructions based on this work are being considered for inclusion in the future IEEE 754-2018 floating-point standard, and new reproducible BLAS are being considered for the next version of the BLAS standard.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Software development infrastructure for the HYBRID modeling and simulation project

One of the goals of the HYBRID modeling and simulation project is to assess the economic viability of hybrid systems in a market that contains renewable energy sources like wind. The idea is that it is possible for the nuclear plant to sell non-electric energy cushions, which absorb (at least partially) the volatility introduced by the renewable energy sources. This system is currently modeled in the Modelica programming language. To assess the economics of the system, an optimization procedure is trying to find the minimal cost of electricity production. The RAVEN code is used as a driver for the whole problem. It is assumed that at this stage, the HYBRID modeling and simulation framework can be classified as non-safety “research and development” software. The associated quality level is Quality Level 3 software. This imposes low requirements on quality control, testing and documentation. The quality level could change as the application development continues.Despite the low quality requirement level, a workflow for the HYBRID developers has been defined that include a coding standard and some documentation and testing requirements. The repository performs automated unit testing of contributed models. The automated testing is achieved via an open-source python script called BuildingsP from Lawrence Berkeley National Lab. BuildingsPy runs Modelica simulation tests using Dymola in an automated manner and generates and runs unit tests from Modelica scripts written by developers. In order to assure effective communication between the different national laboratories a biweekly videoconference has been set-up, where developers can report their progress and issues. In addition, periodic face-face meetings are organized intended to discuss high-level strategy decisions with management. A second means of communication is the developer email list. This is a list to which everybody can send emails that will be received by the collective of the developers and managers involved in the project. Thirdly, to exchange documents quickly, a SharePoint directory has been set-up. SharePoint allows teams and organizations to intelligently share, and collaborate on content from anywhere.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

COMBIgor: Data-Analysis Package for Combinatorial Materials Science

Combinatorial experiments involve synthesis of sample libraries with lateral composition gradients requiring spatially-resolved characterization of structure and properties. Here, due to maturation of combinatorial methods and their successful application in many fields, the modern combinatorial laboratory produces diverse and complex data sets requiring advanced analysis and visualization techniques. In order to utilize these large data sets to uncover new knowledge, the combinatorial scientist must engage in data science. For data science tasks, most laboratories adopt common-purpose data management and visualization software. However, processing and cross-correlating data from various measurement tools is no small task for such generic programs. Here we describe COMBIgor, a purpose-built open-source software package written in the commercial Igor Pro environment, designed to offer a systematic approach to loading, storing, processing, and visualizing combinatorial data sets. It includes (1) methods for loading and storing data sets from combinatorial libraries, (2) routines for streamlined data processing, and (3) data analysis and visualization features to construct figures. Most importantly, COMBIgor is designed to be easily customized by a laboratory, group, or individual in order to integrate additional instruments and data-processing algorithms. Utilizing the capabilities of COMBIgor can significantly reduce the burden of data management on the combinatorial scientist.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Build and Execute Environment

At exascale, the challenge becomes to develop applications that run at scale and use exascale platforms reliably, efficiently, and flexibly. Workflows become much more complex because they must seamlessly integrate simulation and data analytics. They must include down-sampling, post-processing, feature extraction, and visualization. Power and data transfer limitations require these analysis tasks to be run in-situ or in-transit. We expect successful workflows will comprise multiple linked simulations along with tens of analysis routines. Users will have limited development time at scale and, therefore, must have rich tools to develop, debug, test, and deploy applications. At this scale, successful workflows will compose linked computations from an assortment of reliable, well-defined computation elements, ones that can come and go as required, based on the needs of the workflow over time. We propose a novel framework that utilizes both virtual machines (VMs) and software containers to create a workflow system that establishes a uniform build and execution environment (BEE) beyond the capabilities of current systems. In this environment, applications will run reliably and repeatably across heterogeneous hardware and software. Containers, both commercial (Docker and Rocket) and open-source (LXC and LXD), define a runtime that isolates all software dependencies from the machine operating system. Workflows may contain multiple containers that run different operating systems, different software, and even different versions of the same software. We will run containers in open-source virtual machines (KVM) and emulators (QEMU) so that workflows run on any machine entirely in user-space. On this platform of containers and virtual machines, we will deliver workflow software that provides services, including repeatable execution, provenance, checkpointing, and future proofing. We will capture provenance about how containers were launched and how they interact to annotate workflows for repeatable and partial re-execution. We will coordinate the physical snapshots of virtual machines with parallel programming constructs, such as barriers, to automate checkpoint and restart. We will also integrate with HPC-specific container runtimes to gain access to accelerators and other specialized hardware to preserve native performance. Containers will link development to continuous integration. When application developers check code in, it will automatically be tested on a suite of different software and hardware architectures.

Guan, Qiang↗

DOE OSTI2017

Build and Execute Environment

Guan, Qiang↗

DOE OSTI2015

SU-E-T-519: Investigation of the CyberKnife MultiPlan Monte Carlo Dose Calculation Using EBT3 Film Absolute Dosimetry for Delivery in a Heterogeneous Thorax Phantom

Purpose To characterize the Cyberknife (CK) robotic system’s dosimetric accuracy of the delivery of MultiPlan’s Monte Carlo dose calculations using EBT3 radiochromic film inserted in a thorax phantom. Methods The CIRS XSight Lung Tracking (XLT) Phantom (model 10823) was used in this study with custom cut EBT3 film inserted in the horizontal (coronal) plane inside the lung tissue equivalent phantom. CK MultiPlan v3.5.3 with Monte Carlo dose calculation algorithm (1.5 mm grid size, 2% statistical uncertainty) was used to calculate a clinical plan for a 25-mm lung tumor lesion, as contoured by the physician, and then imported onto the XLT phantom CT. Using the same film batch, the net OD to dose calibration curve was obtained using CK with the 60 mm fixed cone by delivering 0– 800 cGy. The test films (n=3) were irradiated using 325 cGy to the prescription point. Films were scanned 48 hours after irradiation using an Epson v700 scanner (48 bits color scan, extracted red channel only, 96 dpi). Percent absolute dose and relative isodose distribution difference relative to the planned dose were quantified using an in-house QA software program. Multiplan Monte Carlo dose calculation was validated using RCF dosimetry (EBT3) and gamma index criteria of 3%/3mm and 2%/2mm for absolute dose and relative isodose distribution measurement comparisons. Results EBT3 film measurements of the patient plans calculated with Monte Carlo in MultiPlan resulted in an absolute dose passing rate of 99.6±0.4% for the Gamma Index of 3%/3mm, 10% dose threshold, and 95.6±4.4% for 2%/2mm, 10% threshold criteria. The measured central axis absolute dose was within 1.2% (329.0±2.5 cGy) of the Monte Carlo planned dose (325.0±6.5 cGy) for that same point. Conclusion MultiPlan’s Monte Carlo dose calculation was validated using the EBT3 film absolute dosimetry for delivery in a heterogeneous thorax phantom.

60 APPLIED LIFE SCIENCES↗