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At least 289 records · Page 16

PPPL Laboratory Directed Research and Development (Project Final Reports, FY2018 - FY2020)

The U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL) is a collaborative national center for fusion energy science, basic sciences, and advanced technology. The Laboratory has three major missions: (1) to develop the scientific knowledge and advanced engineering to enable fusion to power the U.S. and the world; (2) to advance the science of nanoscale fabrication for technologies of tomorrow; and (3) to further the development of the scientific understanding of the plasma universe from laboratory to astrophysical scales. PPPL’s Laboratory Directed Research and Development (LDRD) program supports and encourages creativity and innovation and contributes to its long-term viability. New scientific and technical research areas emerge and are nurtured through the program. Furthermore, new capabilities are developed to enable the Laboratory to meet its and DOE’s missions. The program is used to systematically diversify the Laboratory’s programs and mission. In the last few years, the program has started projects in nanomaterial synthesis, microelectronics, advanced x-ray spectroscopy, high-energy-density physics, superconducting magnet technology, machine learning and artificial intelligence, 3D magnetic fields to optimize fusion plasmas, integration of permanent magnets with simple high-field magnets to reduce the cost of producing complex 3D magnetic fields, advanced computational methods for predictive understanding and control of fusion plasma, development of quantum computing algorithms for plasma physics, liquid metal plasma-facing components for fusion reactors, virtual engineering, and plasma-based space propulsion. The program is also the vehicle to recruit and train talented scientists and engineers with the new skills needed to perform the Laboratory’s mission. Many of the new hires through the program go on to become world-class scientists and engineers in their fields. This report provides descriptions and accomplishments of those LDRD projects that were completed during fiscal years 2018 through 2020.

36 MATERIALS SCIENCE↗

HPE ultralit project (ARPA-E open program 2018) final report 15

The goal of the program was to build a fully integrated optical transceiver with >1 Tb/s and <1.5 pJ/bit operating at 50 ◦ C. Optical transceivers are critical components in high-performance-computers (HPC) and data centers, and the details of their implementation has a big impact on the total power consumption (energy efficiency) of an HPC system. Our proposed transceiver used three key enabling technologies. Firstly, SiGe avalanche photodetectors have record-low sensitivities, meaning that they can reach low bit error rates with very little light input. As a result, we can drive our lasers at a lower drive current, thus saving electrical power. Secondly, we use MOS-based capacitive tuning in our deinterleaver, modulator, and demultiplexer. Capacitive tuning allows for the tuning of photonic elements with zero static power consumption. Thirdly, we use quantum dots as the gain material in our light source. This allows us to efficiently use our light source at temperatures that are typically encountered in an HPCsystem. Our proposed optical transceiver consisted of a quantum dot comb laser as a light source, a booster SOA, MOS-based deinterleavers, MOS based ring modulators, MOS-based ring demultiplexers, and SiGe APDs.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

MILK : a Python scripting interface to MAUD for automation of Rietveld analysis

Modern diffraction experiments ( e.g. in situ parametric studies) present scientists with many diffraction patterns to analyze. Interactive analyses via graphical user interfaces tend to slow down obtaining quantitative results such as lattice parameters and phase fractions. Furthermore, Rietveld refinement strategies ( i.e. the parameter turn-on-off sequences) tend to be instrument specific or even specific to a given dataset, such that selection of strategies can become a bottleneck for efficient data analysis. Managing multi-histogram datasets such as from multi-bank neutron diffractometers or caked 2D synchrotron data presents additional challenges due to the large number of histogram-specific parameters. To overcome these challenges in the Rietveld software Material Analysis Using Diffraction ( MAUD ), the MAUD Interface Language Kit ( MILK ) is developed along with an updated text batch interface for MAUD . The open-source software MILK is computer-platform independent and is packaged as a Python library that interfaces with MAUD . Using MILK , model selection ( e.g. various texture or peak-broadening models), Rietveld parameter manipulation and distributed parallel batch computing can be performed through a high-level Python interface. A high-level interface enables analysis workflows to be easily programmed, shared and applied to large datasets, and external tools to be integrated with MAUD . Through modification to the MAUD batch interface, plot and data exports have been improved. The resulting hierarchical folders from Rietveld refinements with MILK are compatible with Cinema: Debye–Scherrer , a tool for visualizing and inspecting the results of multi-parameter analyses of large quantities of diffraction data. In this manuscript, the combined Python scripting and visualization capability of MILK is demonstrated with a quantitative texture and phase analysis of data collected at the HIPPO neutron diffractometer.

97 MATHEMATICS AND COMPUTING↗

Exploring the Use of Novel Spatial Accelerators in Scientific Applications

Driven by the need to find alternative accelerators which can viably replace GPUs in next-generation Supercomputing systems, this paper proposes a methodology to enable agile application/hardware co-design. The application-first methodology provides the ability to come up with design of accelerators while working with real-world workloads, available accelerators, and system software. The iterative design process targets a set of kernels in a workload for performance estimates that can prune the design space for later phases of detailed architectural evaluations. To this effect, in this paper, a novel data-parallel device model is introduced that simulates the latency of performance-sensitive operations in an accelerator including data transfers and kernel computation using multi-core CPUs. The use of off-the-shelf simulators, such as pre-RTL simulator Aladdin or multiple tools available for exploring the design of deep neural network accelerators (e.g., Timeloop) is demonstrated for evaluation of various accelerator designs using applications with realistic inputs. Examples of multiple device configurations that are instantiable in a system are explored to evaluate the performance benefit of deploying novel accelerators. The proposed device is integrated with a programming model and system software to potentially explore the impacts of high-level programming languages/compilers and low-level effects such as task scheduling on multiple accelerators. We analyze our methodology for a set of applications that represent high-performance computing (HPC) and graph analytics. The applications include a computational chemistry kernel realized using tensor contractions, triangle counting, GraphSAGE and Breadth-first Search. These applications include kernels such as dense matrix-dense matrix multiplication, sparse matrix-spare matrix multiplication, and sparse matrix-dense vector multiplication. Our results indicate potential performance benefits and insights for system design by including accelerators that realize these kernels along-side general purpose accelerators.

AI, codesign, Accelerated Computing, Modeling and ↗

Enabling Scalable VQE Simulation on Leading HPC Systems

Large-scale simulations of quantum circuits pose significant challenges, especially in the context of quantum chemistry, due to the number of qubits, circuit depth, and the number of circuits needed per problem. High-performance computing (HPC) systems offer massive computational capabilities that could help overcome these obstacles. We developed a high-performance quantum circuit simulator, called NWQ-Sim, and demonstrate its capability to simulate large quantum chemistry problems on NERSC's Perlmutter supercomputer. Integrating NWQ-Sim with XACC, we have executed QPE and VQE algorithms for downfolded quantum chemistry systems at unprecedented scales. Our work demonstrates the potential of leveraging HPC resources to advance quantum chemistry and other applications of near-term quantum devices.

Wang, Meng↗

Integrating Sudo-Kaminaga Correlation to the Safety Analysis Code PARET-ANL

The accuracy and reliability of the reactor safety analysis code are critical because the specifications of the safety systems will depend on the analytical results for initiating events that could occur to the reactor. In safety analyses for power reactors, there exist many proficient and applicable computer codes such as RELAP5, CATHARE, RETRAN, or CATHENA. For non-power research reactors, an issue arises, however, due to lacking of such specialized codes. As a result, computer codes developed for the transient analysis of power reactors need to be applied carefully after proving their applicability to a specified research reactor. The safety analysis discussed in this paper concerns the prevention of fuel damage in hypothetical accidental scenarios for the new research reactor design at National Institute of Standards and Technology (NIST). One fuel integrity criterion is analyzed by investigating the Minimum Critical Heat Flux Ratio (MCHFR) in the core during the accidental transients. Some previous studies develop a relationship that correlates the nominal value of the minimum CHFR with the probability of CHF occurring and causing fuel damage. Using a statistical approach, the nominal value of the MCHFR for the low-enriched uranium (LEU) reactor needs to remain above the recommended limiting value to better ensure the safety of the research reactor. The probability of no fuel failure increases as the MCHFR increases. More importantly, as long as the MCHFR remains above the recommended limiting value of 1.301, the reactor will have a 90% probability that CHF is not reached. The safety analysis program PARET, developed by Argonne National Laboratory (ANL), is employed to obtain the CHFR information in this study. PARET/ANL is a digital computer programming code intended primarily for the analysis of test and research reactors that use plate-type (flat) fuel elements. This program has its own set of correlations that are used to calculate the CHFR. One of them is the Mirshak correlation, which was believed to provide the best estimation of the critical heat flux under the operating conditions of the new reactor at the time. Following the critical heat flux (CHF) experiments for vertical rectangular channels in the JRR-3 (Japan Research Reactor unit 3), the CHF calculations now use the Sudo- Kaminaga correlation. This correlation is of our interest because this method has an enhanced geometric similarity and an increased range of applicability that are more representative of the actual operating conditions of our current design, and has a more mechanistic approach [9]. Since the source code of PARET/ANL is inaccessible, a MATLAB-based utility has been written to integrate the Sudo-Kaminaga correlation as a substitute for the Mirshak correlation in the code. As a result, both the Mirshak and the Sudo-Kaminaga correlations are used to analyze the standard output from the PARET program to calculate the CHFR.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Development of massively parallel quantum chemistry program SMASH

A massively parallel program for quantum chemistry calculations SMASH was released under the Apache License 2.0 in September 2014. The SMASH program is written in the Fortran90/95 language with MPI and OpenMP standards for parallelization. Frequently used routines, such as one- and two-electron integral calculations, are modularized to make program developments simple. The speed-up of the B3LYP energy calculation for (C{sub 150}H{sub 30}){sub 2} with the cc-pVDZ basis set (4500 basis functions) was 50,499 on 98,304 cores of the K computer.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Lattice Quantum Chromodynamics: SPI, mapping, site ordering, and QPX in Lattice QCD code on Mira (ALCF-2 Early Science Program Technical Report)

Lattice QCD is a numerical method to simulate QCD (Quantum Chromodynamics) including non-perturbative effects. Among other methods, lattice QCD is the only successful non-perturbative method that can be systematically improved from first principles. Lattice QCD plays an important role in High Energy Particle Physics (flavor physics, spectroscopy, and beyond the Standard Model physics) and Nuclear Physics (nucleon/nuclear spectrum & structure, quark-gluon plasma, and the QCD equation of state). Moreover, recently there are active developments in applying lattice gauge theory to quantum field theory in general, for example the theoretical description of graphene or cold atom systems. We define the QCD action on a finite and discrete ‘lattice’ like grid, so that we can compute the path integral (partition function) on a computer. A current lattice size is 96 3 ×192, and the corresponding number of degrees of freedom for the path integral is about 6×10 8 . Thus, it requires enormous computing resources. In this report, we describe our overall efforts to improve lattice QCD software on Mira, which include a new communication library using the Message Unit (MU) SPI (System Programming Interface), better node mapping strategy, lattice site reordering, and using the quad floating point (QPX) intrinsics.

Na, Heechang↗

PINE: Photonic Integrated Networked Energy efficient datacenters

We review the motivation, goals, and achievements of the Photonic Integrated Networked Energy efficient datacenter (PINE) project, which is part of the Advanced Research Projects Agency–Energy (ARPA-E) ENergy-efficient Light-wave Integrated Technology Enabling Networks that Enhance Dataprocessing (ENLITENED) program. Here, the PINE program leverages the unique features of photonic technologies to enable alternative mega-datacenters and high-performance computing (HPC) system architectures that deliver more substantial energy efficiency improvements than can be achieved through link energy efficiency alone. In phase 1 of the program, the PINE system architecture demonstrated an average factor of 2.2× improvement in transactions/joule across a diverse set of HPC and datacenter applications. In phase 2, PINE will demonstrate an aggressive 1.0 pJ/bit total link budget with high-bandwidth-density dense wavelength-division multiplexing (DWDM) links to enable additional 2.5× or more efficiency gains through deep resource disaggregation.

42 ENGINEERING↗

The Role of the Digital Thread for Security, Resilience, and Adaptability in Manufacturing

The manufacturing sector is dramatically evolving with recent technical and digital advances. Among these, the digital thread is revolutionizing manufacturing operations well beyond the historic downloading of programs to computer numerically controlled (CNC) machine tools and the uploading of edited programs from CNC controllers. The digital thread is “the communication framework that enables a connected data flow and integrated view of the asset’s data throughout its lifecycle across traditionally siloed functional perspectives” (Leiva 2016). It is pervasive around the world and has changed the way society operates; for example, map apps are used to provide time-optimal directions to destinations using real-time traffic feedback. The digital thread makes it possible to digitally verify products, ensure that the latest technologies are deployed across the entire manufacturing ecosystem, and strengthen the workforce by making each individual more efficient and effective. These three foundational advanced manufacturing concepts will ensure a next-generation secure, resilient, and adaptable manufacturing ecosystem and sustainably support current and future needs of society (Lynn et al. 2020).

99 GENERAL AND MISCELLANEOUS↗

Coordinated Fault Tolerance for High-Performance Computing

Our work to meet our goal of end-to-end fault tolerance has focused on two areas: (1) improving fault tolerance in various software currently available and widely used throughout the HEC domain and (2) using fault information exchange and coordination to achieve holistic, systemwide fault tolerance and understanding how to design and implement interfaces for integrating fault tolerance features for multiple layers of the software stack—from the application, math libraries, and programming language runtime to other common system software such as jobs schedulers, resource managers, and monitoring tools.

97 MATHEMATICS AND COMPUTING↗

Advanced Photovoltaic Inverter Control Development and Validation in a Controller-Hardware-in-the-Loop Test Bed

Penetration of solar photovoltaic (PV) installations into the grid has increased in recent years. In the past, photovoltaic installations have not included grid-support functionality. Grid support functions including Volt-VAR (VVAR), Frequency-Watt (FW), Volt-Watt (VW), frequency/voltage-ride through, as well as other inverter functions such as anti-islanding are recommended by standards such as IEEE 1547 to allow PV inverters to contribute to acceptable operation and stability of distribution systems with high penetrations of PV and to ensure predictable response of the PV inverters. First, low-level and high-level grid support inverter control functions were developed and tested in simulation. The developed controller is able to integrate advanced controller functions in a coordinated approach, avoiding any conflict between the different control objectives. The algorithms were then programmed on an off-the-shelf embedded controller that included a dual-core CPU and FPGA. The details of the high-level grid support function and the lower level switching control will be presented. Second, this programmed controller is tested using a controller-hardware-in-the-loop (CHIL) test bed setup using an FPGA-based real-time simulator. The CHIL setup has the capability to run at a 500 nano-second time-step to accommodate the 20 kHz switching frequency of the developed controller. The advanced control function and CHIL test bed details provided here will aide future researchers to design, implement, and test advanced inverter functions for PV inverters.

14 SOLAR ENERGY↗

An Uncertainty Quantification Framework for Studying the Effect of Spatial Heterogeneity in Reservoir Permeability on CO2 Sequestration

In this paper, we introduce an uncertainty quantification (UQ) software framework for carbon sequestration, focused on the effect of spatial heterogeneity of reservoir properties on CO2 migration. We use a sequential Gaussian method (SGSIM) to generate realizations of permeability fields with various spatial statistical attributes. To deal with the computational difficulties, we integrate the following ideas/approaches. First, we use three different sampling approaches (probabilistic collocation, quasi-Monte Carlo, and adaptive sampling) to reduce the number of forward calculations while trying to explore the parameter space and quantify the input uncertainty. Second, we use eSTOMP as the forward modeling simulator. eSTOMP is implemented with the Global Arrays toolkit that is based on one-sided inter-processor communication and supports a shared memory programming style on distributed memory platforms, providing a highly-scalable performance. Third, we built an adaptive system infrastructure to select the best possible data transfer mechanisms, to optimally allocate system resources to improve performance and to integrate software packages and data for composing carbon sequestration simulation, computation, analysis, estimation and visualization. We demonstrate the framework with a given CO2 injection scenario in heterogeneous sandstone reservoirs.

Carbon sequestration, uncertainty quantification, ↗

Tightly integrated single- and multi-crystal data collection strategy calculation and parallelized data processing in JBluIce beamline control system

The calculation of single- and multi-crystal data collection strategies and a data processing pipeline have been tightly integrated into the macromolecular crystallographic data acquisition and beamline control software JBluIce . Both tasks employ wrapper scripts around existing crystallographic software. JBluIce executes scripts through a distributed resource management system to make efficient use of all available computing resources through parallel processing. The JBluIce single-crystal data collection strategy feature uses a choice of strategy programs to help users rank sample crystals and collect data. The strategy results can be conveniently exported to a data collection run. The JBluIce multi-crystal strategy feature calculates a collection strategy to optimize coverage of reciprocal space in cases where incomplete data are available from previous samples. The JBluIce data processing runs simultaneously with data collection using a choice of data reduction wrappers for integration and scaling of newly collected data, with an option for merging with pre-existing data. Data are processed separately if collected from multiple sites on a crystal or from multiple crystals, then scaled and merged. Results from all strategy and processing calculations are displayed in relevant tabs of JBluIce .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

CCAMP: An Integrated Translation and Optimization Framework for OpenACC and OpenMP

Heterogeneous computing and exploration into specialized accelerators are inevitable in current and future supercomputers. Although this diversity of devices is promising for performance, the array of architectures presents programming challenges. High-level programming strategies have emerged to face these challenges, such as the OpenMP offloading model and OpenACC. The varying levels of support for these standards, however, within vendor-specific and open-source tools, as well as the lack of performance portability across devices, have prevented the standards from achieving their goals. To address these shortcomings, we present CCAMP, an OpenMP and OpenACC interoperable framework. CCAMP provides two primary facilities: language translation between the two standards and device-specific directive optimization within each standard. We show that by using the CCAMP framework, programmers can easily transplant non-portable code into new ecosystems for new architectures. Additionally, by using CCAMP device-specific directive optimizations, users can achieve optimized performance across architectures using a single source code.

Lambert, Jacob↗

High Performance Computing Operations Review Report

The High Performance Computing Operations Review (HPCOR) meeting—requested by the ASC and ASCR program headquarters at DOE—was held November 5 and 6, 2013, at the Marriott Hotel in San Francisco, CA. The purpose of the review was to discuss the processes and practices for HPC integration and its related software and facilities. Experiences and lessons learned from the most recent systems deployed were covered in order to benefit the deployment of new systems.

97 MATHEMATICS AND COMPUTING↗

A GPU-based 2D shallow water quality model

In this paper, a 2D shallow water flow solver integrated with a water quality model is presented. The interaction between the main water quality constituents included is based on the Water Quality Analysis Simulation Program. Efficiency is achieved by computing with a combination of a Central Processing Unit (CPU) and a Graphics Processing Unit (GPU) device. This technique is intended to provide robust and accurate simulations with high computation speedups with respect to a single-core CPU in real events. The proposed numerical model is evaluated in cases that include the transport and reaction of water quality components over irregular bed topography and dry–wet fronts, verifying that the numerical solution in these situations conserves the required properties (C-property and positivity). The model can operate in any steady or unsteady form allowing an efficient assessment of the environmental impact of water flows. The field data from an unsteady river reach test case are used to show that the model is capable of predicting the measured temporal distribution of dissolved oxygen and water temperature, proving the robustness and computational efficiency of the model, even in the presence of noisy signals such as wind speed.

54 ENVIRONMENTAL SCIENCES↗

Cybersecurity Standards, Certification, and Best Practices for DERs

Distributed energy resources (DERs) are becoming increasingly important to the electric grid, including solar energy systems. However, DERs also introduce new cybersecurity risks, including those posed by cloud computing. Standards harmonization is essential for ensuring that DERs are secure and can be safely integrated into the grid. This panel will discuss cyber standards harmonization for solar security. The panel will feature experts from the S2G Program, National Labs and Industry who will discuss the following topics: the cybersecurity risks and future benefits posed by ubiquitous solar energy systems, the development and implementation of cloud-based security solutions for DERs, including solar energy systems, the challenges and opportunities for harmonizing DER cybersecurity standards, and Cyber Informed Engineering and the solar security implementations The panel will also discuss the following specific initiatives: the S2G Program's DER Cybersecurity Framework, UL's DER Cybersecurity Certification Program, and IEEE 1547 Updates. The panel will conclude with a discussion of the future of standards harmonization for DER cybersecurity.

14 SOLAR ENERGY↗