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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Phase II Final Report Computer Optimization of Electron Guns

This program implemented advanced computer optimization into an adaptive mesh, finite element, 3D, charged particle code. The routines can optimize electron gun performance to achieve a specified current, beam size, and perveance. It can also minimize beam ripple and electric field gradients. The magnetics optimization capability allows design of coil geometries and magnetic material configurations to achieve a specified axial magnetic field profile. The optimization control program, built into the charged particle code Beam Optics Analyzer (BOA) utilizes a 3D solid modeling package to modify geometry using design tables. Parameters within the graphical user interface (currents, voltages, etc.) can be directly modified within BOA. The program implemented advanced post processing capability for the optimization routines as well as the user. A Graphical User Interface allows the user to set up goal functions, select variables, establish ranges of variation, and define performance criteria. The optimization capability allowed development of a doubly convergent multiple beam gun that could not be designed using previous techniques.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

KokkACC: Enhancing Kokkos with OpenACC

Template metaprogramming is gaining popularity as a high-level solution for achieving performance portability on heterogeneous computing resources. Kokkos is a representative approach that offers programmers high-level abstractions for generic programming while most of the device-specific code generation and optimizations are delegated to the compiler through template specializations. For this, Kokkos provides a set of device-specific code specializations in multiple back ends, such as CUDA and HIP. Unlike CUDA or HIP, OpenACC is a high-level and directive-based programming model. This descriptive model allows developers to insert hints (pragmas) into their code that help the compiler to parallelize the code. The compiler is responsible for the transformation of the code, which is completely transparent to the programmer. This paper presents an OpenACC back end for Kokkos: KokkACC. As an alternative to Kokkos’s existing device-specific back ends, KokkACC is a multi-architecture back end providing a high-productivity programming environment enabled by OpenACC’s high-level and descriptive programming model. Moreover, we have observed competitive performance; in some cases, KokkACC is faster (up to 9×) than NVIDIA’s CUDA back end and much faster than OpenMP’s GPU offloading back end. This work also includes implementation details and a detailed performance study conducted with a set of mini-benchmarks (AXPY and DOT product) and three mini-apps (LULESH, miniFE and SNAP, a LAMMPS proxy mini-app).

Valero Lara, Pedro↗
DOE OSTI2011

SU (2) lattice gauge theory simulations on Fermi GPUs

In this work we explore the performance of CUDA in quenched lattice SU (2) simulations. CUDA, NVIDIA Compute Unified Device Architecture, is a hardware and software architecture developed by NVIDIA for computing on the GPU. We present an analysis and performance comparison between the GPU and CPU in single and double precision. Analyses with multiple GPUs and two different architectures (G200 and Fermi architectures) are also presented. In order to obtain a high performance, the code must be optimized for the GPU architecture, i.e., an implementation that exploits the memory hierarchy of the CUDA programming model. We produce codes for the Monte Carlo generation of SU (2) lattice gauge configurations, for the mean plaquette, for the Polyakov Loop at finite T and for the Wilson loop. We also present results for the potential using many configurations (50,000) without smearing and almost 2000 configurations with APE smearing. With two Fermi GPUs we have achieved an excellent performance of 200x the speed over one CPU, in single precision, around 110 Gflops/s. We also find that, using the Fermi architecture, double precision computations for the static quark-antiquark potential are not much slower (less than 2x slower) than single precision computations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Gradient Coding With Iterative Block Leverage Score Sampling

Gradient coding is a method for mitigating straggling servers in a centralized computing network that uses erasure-coding techniques to distributively carry out first-order optimization methods. Randomized numerical linear algebra uses randomization to develop improved algorithms for large-scale linear algebra computations. In this study, we propose a method for distributed optimization that combines gradient coding and randomized numerical linear algebra. The proposed method uses a randomized ℓ 2 -subspace embedding and a gradient coding technique to distribute blocks of data to the computational nodes of a centralized network, and at each iteration the central server only requires a small number of computations to obtain the steepest descent update. The novelty of our approach is that the data is replicated according to importance scores, called block leverage scores, in contrast to most gradient coding approaches that uniformly replicate the data blocks. Furthermore, we do not require a decoding step at each iteration, avoiding a bottleneck in previous gradient coding schemes. We show that our approach results in a valid ℓ 2 -subspace embedding, and that our resulting approximation converges to the optimal solution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Validation of hydrogen gas stratification and mixing models

Two validation benchmarks confirm that the BMIX++ code is capable of simulating unintended hydrogen release scenarios efficiently. The BMIX++ (UC Berkeley mechanistic MIXing code in C++) code has been developed to accurately and efficiently predict the fluid mixture distribution and heat transfer in large stratified enclosures for accident analyses and design optimizations. The BMIX++ code uses a scaling based one-dimensional method to achieve large reduction in computational effort compared to a 3-D computational fluid dynamics (CFD) simulation. Two BMIX++ benchmark models have been developed. One is for a single buoyant jet in an open space and another is for a large sealed enclosure with both a jet source and a vent near the floor. Both of them have been validated by comparisons with experimental data. Excellent agreements are observed. The entrainment coefficients of 0.09 and 0.08 are found to fit the experimental data for hydrogen leaks with the Froude number of 99 and 268 best, respectively. In addition, the BIX++ simulation results of the average helium concentration for an enclosure with a vent and a single jet agree with the experimental data within a margin of about 10% for jet flow rates ranging from 1.21 × 10⁻⁴ to 3.29 × 10⁻⁴ m³/s. In conclusion, computing time for each BMIX++ model with a normal desktop computer is less than 5 min.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

Steps towards verification and validation of the Fetch code for Level 2 analysis, design, and optimization of aqueous homogeneous reactors

Babcock and Wilcox Technical Services Group (B and W) has identified aqueous homogeneous reactors (AHRs) as a technology well suited to produce the medical isotope molybdenum 99 (Mo-99). AHRs have never been specifically designed or built for this specialized purpose. However, AHRs have a proven history of being safe research reactors. In fact, in 1958, AHRs had 'a longer history of operation than any other type of research reactor using enriched fuel' and had 'experimentally demonstrated to be among the safest of all various type of research reactor now in use [1].' While AHRs have been modeled effectively using simplified 'Level 1' tools, the complex interactions between fluids, neutronics, and solid structures are important (but not necessarily safety significant). These interactions require a 'Level 2' modeling tool. Imperial College London (ICL) has developed such a tool: Finite Element Transient Criticality (FETCH). FETCH couples the radiation transport code EVENT with the computational fluid dynamics code (Fluidity), the result is a code capable of modeling sub-critical, critical, and super-critical solutions in both two-and three-dimensions. Using FETCH, ICL researchers and B and W engineers have studied many fissioning solution systems include the Tokaimura criticality accident, the Y12 accident, SILENE, TRACY, and SUPO. These modeling efforts will ultimately be incorporated into FETCH'S extensive automated verification and validation (V and V) test suite expanding FETCH'S area of applicability to include all relevant physics associated with AHRs. These efforts parallel B and W's engineering effort to design and optimize an AHR to produce Mo99. (authors)

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2018

QMCPACK : an open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids

QMCPACK is an open source quantum Monte Carlo package for ab-initio electronic structure calculations. It supports calculations of metallic and insulating solids, molecules, atoms, and some model Hamiltonians. Implemented real space quantum Monte Carlo algorithms include variational, diffusion, and reptation Monte Carlo. QMCPACK uses Slater-Jastrow type trial wave functions in conjunction with a sophisticated optimizer capable of optimizing tens of thousands of parameters. The orbital space auxiliary field quantum Monte Carlo method is also implemented, enabling cross validation between different highly accurate methods. The code is specifically optimized for calculations with large numbers of electrons on the latest high performance computing architectures, including multicore central processing unit (CPU) and graphical processing unit (GPU) systems. We detail the program’s capabilities, outline its structure, and give examples of its use in current research calculations. The package is available at http://www.qmcpack.org.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Composable optimization and control toolkit for scientific applications

Applications of Artificial Intelligence (AI) and Machine Learning (ML) can improve the computational efficiency and scientific research output. In order to improve interoperability and reuse of AI/ML software, a composable approach is required. This talk presents a composable approach for scientific workflow development that allows seamless integration of various modules developed by independent researchers. These practices will reduce redundant software development by allowing re-use of workflow modules across projects, teams, departments and facilities. We will present three use cases that follow the composable approach namely, Scientific Optimization and Control Toolkit (SOCT), SciDAC QuantOm workflow, and JLab Nuclear Physics experimental workflows. This talk will dive deeper into SOCT and present the details of the composable code development for optimization and control algorithms using reinforcement learning.

Rajput, Kishansingh↗
DOE OSTI2011

Coded source neutron imaging at the PULSTAR reactor

A neutron imaging facility is located on beam-tube No.5 of the 1-MW PULSTAR reactor at North Carolina State University. An investigation of high resolution imaging using the coded source imaging technique has been initiated at the facility. Coded imaging uses a mosaic of pinholes to encode an aperture, thus generating an encoded image of the object at the detector. To reconstruct the image data received by the detector, the corresponding decoding patterns are used. The optimized design of coded mask is critical for the performance of this technique and will depend on the characteristics of the imaging beam. In this work, a 34 x 38 uniformly redundant array (URA) coded aperture system is studied for application at the PULSTAR reactor neutron imaging facility. The URA pattern was fabricated on a 500 ?m gadolinium sheet. Simulations and experiments with a pinhole object have been conducted using the Gd URA and the optimized beam line.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2011

Automated searching for quantum subsystem codes

Quantum error correction allows for faulty quantum systems to behave in an effectively error-free manner. One important class of techniques for quantum error correction is the class of quantum subsystem codes, which are relevant both to active quantum error-correcting schemes as well as to the design of self-correcting quantum memories. Previous approaches for investigating these codes have focused on applying theoretical analysis to look for interesting codes and to investigate their properties. In this paper we present an alternative approach that uses computational analysis to accomplish the same goals. Specifically, we present an algorithm that computes the optimal quantum subsystem code that can be implemented given an arbitrary set of measurement operators that are tensor products of Pauli operators. We then demonstrate the utility of this algorithm by performing a systematic investigation of the quantum subsystem codes that exist in the setting where the interactions are limited to two-body interactions between neighbors on lattices derived from the convex uniform tilings of the plane.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

EnergyPlus Interior Radiant Heat Exchange Runtime Performance Improvements

EnergyPlus is the flagship whole-building energy simulation program developed by the US Department of Energy. This paper describes the various approaches to improve the performance of the interior radiant heat exchange algorithm. Vectorization, optimized Basic Linear Algebra Subprograms (BLAS) library, multithreading, and Graphical Processing Unit (GPU) computation are all investigated. The approach with the best performance, while maintaining drop-in compatibility with existing EnergyPlus code, is the optimized BLAS library. However, GPU computing has the potential to reduce simulation time by orders of magnitude with major refactoring to EnergyPlus.

Adams, Mark↗
DOE OSTI2011

High-resolution Thomson parabola for ion analysis

A new, versatile Thomson parabola ion energy (TPIE) analyzer has been designed, constructed, and used at the OMEGA-EP facility. Laser-accelerated multi-MeV ions from hemispherical C targets are transmitted through a W pinhole into a multi-kG magnetic field and subsequently through a parallel electric field of up to 25 kV/cm. The ion drift region has a user-selected length of 10, 50, or 80 cm. With the highest fields, 400-MeV C{sup 6+} and C{sup 5+} may be resolved. TPIE is ten-inch manipulator (TIM)-mounted at OMEGA-EP and can be used opposite either of the EP ps beams. The instrument runs on pressure-interlocked 15-Vdc power available in EP TIM carts. Flux control derives from the insertion depth into the target chamber and the user-selected pinhole dimensions. The detector consists of CR39 backed by an image plate. A fully relativistic simulation code for calculating ion trajectories was employed for design optimization. Excellent agreement of code predictions with the actual ion positions on the detectors is observed. Through pit counting of carbon-ion tracks in CR39, it is shown that conversion efficiency of laser light to energetic carbon ions exceeds {approx}5% for these targets.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

Scalable Triadic Analysis of Large-Scale Graphs: Multi-Core vs. Multi-Processor vs. Multi-Threaded Shared Memory Architectures

Triadic analysis encompasses a useful set of graph mining methods that is centered on the concept of a triad, which is a subgraph of three nodes and the configuration of directed edges across the nodes. Such methods are often applied in the social sciences as well as many other diverse fields. Triadic methods commonly operate on a triad census that counts the number of triads of every possible edge configuration in a graph. Like other graph algorithms, triadic census algorithms do not scale well when graphs reach tens of millions to billions of nodes. To enable the triadic analysis of large-scale graphs, we developed and optimized a triad census algorithm to efficiently execute on shared memory architectures. We will retrace the development and evolution of a parallel triad census algorithm. Over the course of several versions, we continually adapted the code’s data structures and program logic to expose more opportunities to exploit parallelism on shared memory that would translate into improved computational performance. We will recall the critical steps and modifications that occurred during code development and optimization. Furthermore, we will compare the performances of triad census algorithm versions on three specific systems: Cray XMT, HP Superdome, and AMD multi-core NUMA machine. These three systems have shared memory architectures but with markedly different hardware capabilities to manage parallelism.

Triadic analysis, triads, triad census, large-scal↗
DOE OSTI2022

Bridging Python to Silicon: The SODA Toolchain

Systems performing scientific computing, data analysis, and machine learning tasks have a growing demand for application-specific accelerators that can provide high computational performance while meeting strict size and power requirements. However, the algorithms and applications that need to be accelerated are evolving at a rate that is incompatible with manual design processes based on hardware description languages. Agile hardware design tools based on compiler techniques can help by quickly producing an application-specific integrated circuit (ASIC) accelerator starting from a high-level algorithmic description. Here, we present the software-defined accelerator (SODA) synthesizer, a modular and open-source hardware compiler that provides automated end-to-end synthesis from high-level software frameworks to ASIC implementation, relying on multilevel representations to progressively lower and optimize the input code. Our approach does not require the application developer to write any register-transfer level code, and it is able to reach up to 364 giga floating point operations per second (GFLOPS)/W efficiency (32-bit precision) on typical convolutional neural network operators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

On relaxations of the max k -cut problem formulations

Here, a tight continuous relaxation is a crucial factor in solving mixed integer formulations of many NP-hard combinatorial optimization problems. The (weighted) max k-cut problem is a fundamental combinatorial optimization problem with multiple notorious mixed integer optimization formulations. In this paper, we explore four existing mixed integer optimization formulations of the max k-cut problem. Specifically, we show that the continuous relaxation of a binary quadratic optimization formulation of the problem is: (i) stronger than the continuous relaxation of two mixed integer linear optimization formulations and (ii) at least as strong as the continuous relaxation of a mixed integer semidefinite optimization formulation. We also conduct a set of experiments on multiple sets of instances of the max k-cut problem using state-of-the-art solvers that empirically confirm the theoretical results in item (i). Furthermore, these numerical results illustrate the advances in the efficiency of global non-convex quadratic optimization solvers and more general mixed integer nonlinear optimization solvers. As a result, these solvers provide a promising option to solve combinatorial optimization problems. Our codes and data are available on GitHub.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Innovations in optimization and control of accelerators using methods of differential geometry and genetic algorithms (Final Report)

Online tuning of particle accelerators is necessary in order to achieve optimal machine performance. However, it is also a major challenge due to the large parameter space which must be searched and the fact that many of the desir- able objectives compete with one another, and so will not reach their optimal values simultaneously. In order to mitigate these issues, we have explored using dimension-reduction techniques to reduce the size of the parameter space which must be searched and multi-objective genetic algorithms to obtain the sets of tuning parameters which provide pareto-optimal values for the objectives. These methods have enabled us to obtain improved values of the vertical emittance at the Cornell Electron Storage Ring (CESR), and to do so with greater control of orbit errors. Algorithmic tuning is a multidisciplinary endeavour, requiring expertise in beam dynamics, diagnostics, control systems and computer science, and thus a key practical problem is to formulate a common language in which experts with different specialties can communicate. We developed a solution to this problem in the form of a generic accelerator software interface that allows for rapid prototyping of optimization and control algorithms. Our interface is built on the Experimental Physics and Industrial Control Systems (EPICS) and makes possible testing control code in simulation before deployment on real accelerators, as well as deployment of third-party optimization code.

43 PARTICLE ACCELERATORS↗