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DOE OSTI2014

Parallel processing of filtered queries in attributed semantic graphs

Execution of complex analytic queries on massive semantic graphs is a challenging problem in big-data analytics that requires high-performance parallel computing. In a semantic graph, vertices and edges carry attributes of various types and the analytic queries typically depend on the values of these attributes. Thus, the computation must view the graph through a filter that passes only those individual vertices and edges of interest. Previous investigations have developed Knowledge Discovery Toolbox (KDT), a sophisticated Python library for parallel graph computations. In KDT, the user can write custom graph algorithms by specifying operations between edges and vertices ( semiring operations ). The user can also customize existing graph algorithms by writing filters. While the high-level language for this customization enables domain scientists to productively express their graph analytics requirements, the customized queries perform poorly due to the overhead of having to call into the Python virtual machine for each vertex and edge. In this work, we use the Selective Embedded Just-In-Time Specialization (SEJITS) approach to automatically translate semiring operations and filters defined by programmers into a lower-level efficiency language, bypassing the upcall into Python. We evaluate our approach by comparing it with the high-performance Combinatorial BLAS engine and show that our approach combines the benefits of programming in a high-level language with executing in a low-level parallel environment. We increase the system's flexibility by developing techniques that provide users with the ability to define new vertex and edge types from Python. We also present a new Roofline model for graph traversals and show that we achieve performance that is significantly closer to the bounds suggested by the Roofline. Finally, to further understand the complex interaction with the underlying architecture, we present an analysis using performance counters that quantifies the improvement in hardware behavior in the context our SEJITS methodology. Comprehensively, we demonstrate the first known solution to the problem of obtaining high performance from a productivity language when applying graph algorithms selectively on semantic graphs with hundreds of millions of edges and scaling to thousands of processors for graphs.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Towards a Verifiable Domain-Specific Language for Hardware-Accelerated Stencils

Defining a domain-specific language (DSL) that supports vector-calculus abstractions eases the porting of partial differential equation (PDE) solvers to specialized architectures. Sufficiently high-level abstractions empower users to express universal laws with sufficient generality that the laws must always hold true within their domain of validity. A broad class of PDE solvers employs stencil-based algorithms, the target domain of Berkeley Lab's stencil accelerator chip co-design project. First released as open-source in January 2026, the Formal software framework lays a foundation for defining an embedded DSL based on composable operators that implement mimetic numerical methods -- stencil algorithms that guarantee satisfaction of discrete versions of important vector calculus theorems. The Formal DSL will be the frontend to a new class of stencil-PDE accelerators developed jointly by LBNL, UHCL, and UC Berkeley through the DOE Competitive Portfolios for Computer Science Project. This offers the potential of an order of magnitude acceleration for this important category of computational methods to serve the DOE mission. Future work on the Formal DSL will facilitate software verification via type-safe templates that enable problem-specific correctness proofs relying upon generic function theory and carefully crafted unit tests.

Rouson, Damian↗

DOE OSTI2023

A Scalable Quantum Cryptography Network for Protected Automation Communication (Final Report)

This is the final report for a CEDS-funded project aimed at developing a new quantum technology for securing utility communication networks used to control and monitor electrical grid equipment. Securing these control networks represents a unique challenge as the performance of the security solution has a direct impact on the stability and reliability of the electrical grid. Traditional, software-based solutions - developed for information networks - are not suitable for utility control networks because they introduce latency, require burdensome maintenance and upgrades, are often incompatible with legacy equipment, and introduce operational complexity that reduces grid reliability. Consequently, many U.S. utilities do not use existing solutions and, instead, protect their critical control networks through the careful isolation and obscuration of their networked equipment. With more utilities embracing grid automation, the attack surface that utilities must defend from hackers has grown to an unmanageable size. To address this situation, Qubitekk and its partners proposed and developed a hardware-based solution that can secure critical control networks without negatively impacting grid performance. This new solution is based on quantum key distribution (QKD) techniques that guarantee secure key generation and distribution across a utility control network. Through deployment and field testing of a prototype QKD system, we have shown that this solution delivers long-term network security, is technically feasible to implement and maintain on a utility’s distribution substation network and does not negatively impact grid operations. In addition, the project has identified and solved key challenges associated with generating, transmitting, and measuring coherent photonic quantum states on a real-world fiber optic network. These additional findings are playing a critical role in advancing quantum networks for quantum computing applications. An overview of the QKD prototype development effort, field testing activities and results, and additional findings relevant to emerging quantum networks are presented in this report.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Resilience Design Patterns: A Structured Approach to Resilience at Extreme Scale

Reliability is a serious concern for future extreme-scale high-performance computing (HPC) systems. Projections based on the current generation of HPC systems and technology roadmaps suggest the prevalence of very high fault rates in future systems. While the HPC community has developed various resilience solutions, application-level techniques as well as system-based solutions, the solution space remains fragmented. There are no formal methods and metrics to integrate the various HPC resilience techniques into composite solutions, nor are there methods to holistically evaluate the adequacy and efficacy of such solutions in terms of their protection coverage, and their performance \& power efficiency characteristics. Additionally, few of the current approaches are portable to newer architectures and software environments that will be deployed on future systems. In this paper, we develop a structured approach to the design, evaluation and optimization of HPC resilience using the concept of design patterns. A design pattern is a general repeatable solution to a commonly occurring problem. We identify the problems caused by various types of faults, errors and failures in HPC systems and the techniques used to deal with these events. Each well-known solution that addresses a specific HPC resilience challenge is described in the form of a pattern. We develop a complete catalog of such resilience design patterns, which may be used by system architects, system software and tools developers, application programmers, as well as users and operators as essential building blocks when designing and deploying resilience solutions. We also develop a design framework that enhances a designer's understanding the opportunities for integrating multiple patterns across layers of the system stack and the important constraints during implementation of the individual patterns. It is also useful for defining mechanisms and interfaces to coordinate flexible fault management across hardware and software components. The resilience patterns and the design framework also enable exploration and evaluation of design alternatives and support optimization of the cost-benefit trade-offs among performance, protection coverage, and power consumption of resilience solutions. Here, the overall goal of this work is to establish a systematic methodology for the design and evaluation of resilience technologies in extreme-scale HPC systems that keep scientific applications running to a correct solution in a timely and cost-efficient manner despite frequent faults, errors, and failures of various types.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

A Statistical Testing Approach for Quantifying Software Reliability; Application to an Example System

The U.S. Nuclear Regulatory Commission (NRC) encourages the use of probabilistic risk assessment (PRA) technology in all regulatory matters, to the extent supported by the state-of-the-art in PRA methods and data. Although much has been accomplished in the area of risk-informed regulation, risk assessment for digital systems has not been fully developed. The NRC established a plan for research on digital systems to identify and develop methods, analytical tools, and regulatory guidance for (1) including models of digital systems in the PRAs of nuclear power plants (NPPs), and (2) incorporating digital systems in the NRC's risk-informed licensing and oversight activities. Under NRC's sponsorship, Brookhaven National Laboratory (BNL) explored approaches for addressing the failures of digital instrumentation and control (I and C) systems in the current NPP PRA framework. Specific areas investigated included PRA modeling digital hardware, development of a philosophical basis for defining software failure, and identification of desirable attributes of quantitative software reliability methods. Based on the earlier research, statistical testing is considered a promising method for quantifying software reliability. This paper describes a statistical software testing approach for quantifying software reliability and applies it to the loop-operating control system (LOCS) of an experimental loop of the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Using MLIR Framework for Codesign of ML Architectures Algorithms and Simulation Tools

MLIR (Multi-Level Intermediate Representation), is an extensible compiler framework that supports high-level data structures and operation constructs. These higher-level code representations are particularly applicable to the artificial intelligence and machine learning (AI/ML) domain, allowing developers to more easily support upcoming heterogeneous AI/ML accelerators and develop flexible domain specific compilers/frameworks with higher-level intermediate representations (IRs) and advanced compiler optimizations. The result of using MLIR within the LLVM compiler framework is expected to yield significant improvement in the quality of generated machine code, which in turn will result in improved performance and hardware efficiency

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1984

A search for Earth-crossing asteroids, supplement

The ground based electro-optical deep space surveillance program involves a network of computer controlled 40 inch 1m telescopes equipped with large format, low light level, television cameras of the intensified silicon diode array type which is to replace the Baker-Nunn photographic camera system for artificial satellite tracking. A prototype observatory was constructed where distant artificial satellites are discriminated from stars in real time on the basis of the satellites' proper motion. Hardware was modified and the technique was used to observe and search for minor planets. Asteroids are now routinely observed and searched. The complete observing cycle, including the 2"-3" measurement of position, requires about four minutes at present. The commonality of asteroids and artificial satellite observing, searching, data reduction, and orbital analysis is stressed. Improvements to the hardware and software as well as operational techniques are considered.

Taff, L. G.↗

DOE OSTI2025

A Real-Time Implementation and Validation of Federated Learning for Grid Services

Grid-edge devices are becoming increasingly important in the energy transition. Preserving privacy was not previously considered an important aspect for power grid operations, but with the increased proliferation of customer-owned assets, it is now an essential consideration. Several mechanisms have been proposed to provide privacy for non-utility owned assets in the power grid. Federated learning (FL) is one method gaining prominence in this area. Although FL has been used for other applications, such as auto-complete in phones, there has not been much investigation into whether these approaches are feasible for grid applications. In this work, we use a research platform with real-time simulators and hardware-in-the-loop capabilities to investigate how FL can be applied to grid-edge devices, and we present the potential grid services that can be derived for these devices. We discuss the computational challenges with deploying complex FL approaches, and we explore several grid services, including participation in retail electricity markets, voltage control, and resilience-driven reconfiguration.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2017

Volumetric Additive Manufacturing of Polymer Structures by Holographically Projected Light Fields

As additive manufacturing technologies proliferate and mature, overcoming some of their process limitations becomes increasingly important for the continued expansion of practical applications. Two such limitations that arise from layer-based fabrication are slow speed and geometric constraints (which include poor surface quality and challenges fabricating span, cantilever, and overhang elements). Moving beyond point-by-point and layer-by-layer approaches, the ability to generate a complex 3D volume as a unit operation has the potential to overcome these limitations. Since holography has been extensively studied as a means for storage and retrieval of 3D geometrical information, this dissertation explores the use of holographically-shaped light fields for producing three-dimensional structures in a “volume at once” approach. Leveraging advances in spatial light modulator (SLM) technology, phase-controlled light fields are projected into photopolymer resin to cure a desired geometry. By overlapping multiple sub-regions of a single light field within the target volume, the successful fabrication of non-periodic complex 3D geometries is demonstrated by single exposures on timescales of seconds. This dissertation presents a complete prototype platform that makes this approach possible, comprising a suitable hardware configuration along with the computational algorithms necessary to calculate and optimize the required optical fields. A study of the photopolymerization kinetics is also carried out, to determine the boundaries of usable process parameters such as resin absorbance and available light intensity. The results indicate that low-absorbing resins containing ~0.1% photoinitiator, illuminated at modest powers (~10-100 mW) may be used to produce full 3D structures from 1-10 second exposures, with volume build rates exceeding 100 cm3/hr, without layering and with no need for a substrate or support material.

36 MATERIALS SCIENCE↗

NASA NTRS1989

A telerobotic system for automated assembly of large space structures

Future space missions such as polar platforms and antennas are anticipated to require large truss structures as their primary support system. During the past several years considerable research has been conducted to develop hardware and construction techniques suitable for astronaut assembly of truss structures in space. A research program has recently been initiated to develop the technology and to demonstrate the potential for automated in-space assembly of large erectable structures. The initial effort will be focussed on automated assembly of a tetrahedral truss composed of 2-meter members. The facility is designed as a ground based system to permit evaluation of assembly concepts and was not designed for space qualification. The system is intended to be used as a tool from which more sophisticated procedures and operations can be developed. The facility description includes a truss structure, motionbases and a robot arm equipped with an end effector. Other considerations and requirements of the structural assembly describe computer control systems to monitor and control the operations of the assembly facility.

Rhodes, Marvin D.↗

NASA NTRS1990

A telerobotic system for automated assembly of large space structures

Future space missions such as polar platforms and antennas are anticipated to require large truss structures as their primary support system. During the past several years considerable research has been conducted to develop hardware and construction techniques suitable for astronaut assembly of truss structures in space. A research program has recently been initiated to develop the technology and to demonstrate the potential for automated in-space assembly of large erectable structures. The initial effort will be focused on automated assembly of a tetrahedral truss composed of 2-meter members. The facility is designed as a ground based system to permit evaluation of assembly concepts and was not designed for space qualification. The system is intended to be used as a tool from which more sophisticated procedures and operations can be developed. The facility description includes a truss structure, motionbases and a robot arm equipped with an end effector. Other considerations and requirements of the structural assembly describe computer control systems to monitor and control the operations of the assembly facility.

Rhodes, Marvin D.↗

NASA NTRS2009

Creating a Lunar EVA Work Envelope

A work envelope has been defined for weightless Extravehicular Activity (EVA) based on the Space Shuttle Extravehicular Mobility Unit (EMU), but there is no equivalent for planetary operations. The weightless work envelope is essential for planning all EVA tasks because it determines the location of removable parts, making sure they are within reach and visibility of the suited crew member. In addition, using the envelope positions the structural hard points for foot restraints that allow placing both hands on the job and provides a load path for reacting forces. EVA operations are always constrained by time. Tasks are carefully planned to ensure the crew has enough breathing oxygen, cooling water, and battery power. Planning first involves computers using a virtual work envelope to model tasks, next suited crew members in a simulated environment refine the tasks. For weightless operations, this process is well developed, but planetary EVA is different and no work envelope has been defined. The primary difference between weightless and planetary work envelopes is gravity. It influences anthropometry, horizontal and vertical mobility, and reaction load paths and introduces effort into doing "overhead" work. Additionally, the use of spacesuits other than the EMU, and their impacts on range of motion, must be taken into account. This paper presents the analysis leading to a concept for a planetary EVA work envelope with emphasis on lunar operations. There is some urgency in creating this concept because NASA has begun building and testing development hardware for the lunar surface, including rovers, habitats and cargo off-loading equipment. Just as with microgravity operations, a lunar EVA work envelope is needed to guide designers in the formative stages of the program with the objective of avoiding difficult and costly rework.

Griffin, Brand N.↗

NASA NTRS2024

Runtime Thread-Block Optimization for Custom Multistream CUDA Kernels for the Glenn Research Center Communication Analysis Suite

In preparation of the return of humans to the Moon with the coming Artemis missions, NASA scientists must evaluate proposed landing site locations for terrain and communications viability. The Glenn Research Center Communication Analysis Suite (GCAS) combines sophisticated communication network models with accurate lunar terrain to access sites across the Moon’s south pole. Given the importance of proper site selection to crew safety and mission success, many locations need to be analyzed resulting in a large computational load needing to be performed. To meet the growing project demands, development has begun to improve the runtime efficiency of GCAS with GPU parallelization by way of multi-stream CUDA kernels. One of the most prominent factors in kernel optimization is the proper selection of thread-block dimensions in order to maximize the concurrent operation on the device. Typically, thread-block dimensions are optimized by hand requiring many stages of benchmarking and iteration. Additionally, given the main conditions to optimization are the physical GPU architecture and problem size, these optimal dimensions are non-portable and fragile in their scope. As such, a novel optimization routine was developed to generate the optimal thread-block dimensions during runtime with considerations to hardware specifications and problem size resolving the issues of portability and enabling the function of more dynamic routines.

Aden Bergstresser↗

DOE OSTI2025

A Novel Protection Scheme for Unbalanced Faults in Inverter Dominated Networks: A Computationally Efficient Algorithm for Entry-Level Relays

Microgrids are now a common practice in distribution systems to increase resilience and reliability. However, microgrid protection remains a critical challenge, considering its requirement to operate in both grid connected and islanded, and the variability in fault characteristics under each mode of operation. This paper presents unbalanced power (S unb ) based fault detection algorithm, which considers local voltage and current unbalances to determine faults in the system. S unb is a computationally efficient fault detection algorithm that is suitable for implementation in the programmable logic of entry level protective relays. In addition, the difference in current and voltage unbalance (D n ) is used to determine the fault type. The proposed method demonstrates high sensitivity and selectivity for line-to-ground (LG), line-to-line (LL), and double line-to-ground (LLG) faults, representing the most common faults in distribution systems. It also allows relay coordination with upstream and downstream protection devices in both island and grid connected operation, while preserving grading margins. The same pickup and time multiplier settings of a particular relay for both modes of operation eliminates the need for adaptive settings, which rely on communication networks. Validation was performed with a hardware-in-the-loop (HIL) setup using Typhoon HIL real time simulator interfaced with three entry-level, SEL 751 relays. Results confirmed the algorithm’s ability to discriminate fault conditions, and determine the fault type under both operating modes, maintain fast detection times, and ensure proper protection coordination.

fault classification↗

DOE OSTI2022

Virtual Neuron: A Neuromorphic Approach for Encoding Numbers

Neuromorphic computers perform computations by emulating the human brain and are expected to be indispensable for energy-efficient computing in the future. They are primarily used in spiking neural network-based machine learning applications. However, neuromorphic computers are unable to preprocess data for these applications. Currently, data is preprocessed on a CPU or a GPU-this incurs a significant cost of transferring data from the CPU/GPU to the neuromorphic processor and vice versa. This cost can be avoided if preprocessing is done on the neuromorphic processor. To efficiently preprocess data on a neuromorphic processor, we first need an efficient mechanism for encoding data that can lend itself to all general-purpose preprocessing operations. Current encoding approaches have limited applicability and may not be suitable for all preprocessing operations. In this paper, we present the virtual neuron as a mechanism for encoding integers and rational numbers on neuromorphic processors. We evaluate the performance of the virtual neuron on physical and simulated neuromorphic hardware and show that it can perform an addition operation using 23 nJ of energy on average using a mixed-signal, memristor-based neuromorphic processor. The virtual neuron encoding approach is the first step in preprocessing data on a neuromorphic processor.

Date, Prasanna↗

NASA NTRS1992

Learning a trajectory using adjoint functions and teacher forcing

A new methodology for faster supervised temporal learning in nonlinear neural networks is presented which builds upon the concept of adjoint operators to allow fast computation of the gradients of an error functional with respect to all parameters of the neural architecture, and exploits the concept of teacher forcing to incorporate information on the desired output into the activation dynamics. The importance of the initial or final time conditions for the adjoint equations is discussed. A new algorithm is presented in which the adjoint equations are solved simultaneously (i.e., forward in time) with the activation dynamics of the neural network. We also indicate how teacher forcing can be modulated in time as learning proceeds. The results obtained show that the learning time is reduced by one to two orders of magnitude with respect to previously published results, while trajectory tracking is significantly improved. The proposed methodology makes hardware implementation of temporal learning attractive for real-time applications.

Toomarian, Nikzad B.↗

NASA NTRS2007

Optimizations of a Hardware Decoder for Deep-Space Optical Communications

The National Aeronautics and Space Administration has developed a capacity approaching modulation and coding scheme that comprises a serial concatenation of an inner accumulate pulse-position modulation (PPM) and an outer convolutional code [or serially concatenated PPM (SCPPM)] for deep-space optical communications. Decoding of this code uses the turbo principle. However, due to the nonbinary property of SCPPM, a straightforward application of classical turbo decoding is very inefficient. Here, we present various optimizations applicable in hardware implementation of the SCPPM decoder. More specifically, we feature a Super Gamma computation to efficiently handle parallel trellis edges, a pipeline-friendly 'maxstar top-2' circuit that reduces the max-only approximation penalty, a low-latency cyclic redundancy check circuit for window-based decoders, and a high-speed algorithmic polynomial interleaver that leads to memory savings. Using the featured optimizations, we implement a 6.72 megabits-per-second (Mbps) SCPPM decoder on a single field-programmable gate array (FPGA). Compared to the current data rate of 256 kilobits per second from Mars, the SCPPM coded scheme represents a throughput increase of more than twenty-six fold. Extension to a 50-Mbps decoder on a board with multiple FPGAs follows naturally. We show through hardware simulations that the SCPPM coded system can operate within 1 dB of the Shannon capacity at nominal operating conditions.

quadratic polynomial interleaver↗

NASA NTRSDate not supplied

A Simplified Model of VIPER Thermal Management System. Part I: Loop Heat Pipe

NASA’s Volatiles Investigating Polar Exploration Rover (VIPER) uses a combination of loop heat pipes (LHPs) and heaters as the primary hardware to modulate the temperature of the electronic boxes and payloads instruments. LHPs have been designed and instrumented to be capable of passive and active shutdown. The goal of the passive shutdown, using a thermal control valve (TCV) to limit the flow of the working fluid, is to preserve thermal energy and avoid unnecessary heat leaks during lunar night. The goal of the active shutdown on the other hand, is to forcefully increase the vehicle internal temperature to bakeout the payload instruments. Several numerical modeling tools are available to analyze LHP performance under the complex set of operational requirements and environments levied on the VIPER Thermal Management System (TMS). Yet, while those numerical modeling tools are capable of detailed performance analysis, they tend to take large computational resources and long computational time. In this paper, a model of a single LHP developed based on control volume approach is presented. By using the control volume approach, the complex geometry of the LHP, and the components attached to it, are reduced to thermal lump capacitances, thus reducing the computation effort. This paper also describes the effort to correlate the proposed LHP model using thermal vacuum (TVAC) test data.

Loop Heat Pipe↗