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At least 181 records · Page 10

Efficient Parallelization of a Dynamic Unstructured Application on the Tera MTA

The success of parallel computing in solving real-life computationally-intensive problems relies on their efficient mapping and execution on large-scale multiprocessor architectures. Many important applications are both unstructured and dynamic in nature, making their efficient parallel implementation a daunting task. This paper presents the parallelization of a dynamic unstructured mesh adaptation algorithm using three popular programming paradigms on three leading supercomputers. We examine an MPI message-passing implementation on the Cray T3E and the SGI Origin2OOO, a shared-memory implementation using cache coherent nonuniform memory access (CC-NUMA) of the Origin2OOO, and a multi-threaded version on the newly-released Tera Multi-threaded Architecture (MTA). We compare several critical factors of this parallel code development, including runtime, scalability, programmability, and memory overhead. Our overall results demonstrate that multi-threaded systems offer tremendous potential for quickly and efficiently solving some of the most challenging real-life problems on parallel computers.

Oliker, Leonid

Implications of Responsive Space on the Flight Software Architecture

The Responsive Space initiative has several implications for flight software that need to be addressed not only within the run-time element, but the development infrastructure and software life-cycle process elements as well. The runtime element must at a minimum support Plug & Play, while the development and process elements need to incorporate methods to quickly generate the needed documentation, code, tests, and all of the artifacts required of flight quality software. Very rapid response times go even further, and imply little or no new software development, requiring instead, using only predeveloped and certified software modules that can be integrated and tested through automated methods. These elements have typically been addressed individually with significant benefits, but it is when they are combined that they can have the greatest impact to Responsive Space. The Flight Software Branch at NASA's Goddard Space Flight Center has been developing the runtime, infrastructure and process elements needed for rapid integration with the Core Flight software System (CFS) architecture. The CFS architecture consists of three main components; the core Flight Executive (cFE), the component catalog, and the Integrated Development Environment (DE). This paper will discuss the design of the components, how they facilitate rapid integration, and lessons learned as the architecture is utilized for an upcoming spacecraft.

Wilmot, Jonathan

Visual Object Recognition and Tracking of Tools

A method has been created to automatically build an algorithm off-line, using computer-aided design (CAD) models, and to apply this at runtime. The object type is discriminated, and the position and orientation are identified. This system can work with a single image and can provide improved performance using multiple images provided from videos. The spatial processing unit uses three stages: (1) segmentation; (2) initial type, pose, and geometry (ITPG) estimation; and (3) refined type, pose, and geometry (RTPG) calculation. The image segmentation module files all the tools in an image and isolates them from the background. For this, the system uses edge-detection and thresholding to find the pixels that are part of a tool. After the pixels are identified, nearby pixels are grouped into blobs. These blobs represent the potential tools in the image and are the product of the segmentation algorithm. The second module uses matched filtering (or template matching). This approach is used for condensing synthetic images using an image subspace that captures key information. Three degrees of orientation, three degrees of position, and any number of degrees of freedom in geometry change are included. To do this, a template-matching framework is applied. This framework uses an off-line system for calculating template images, measurement images, and the measurements of the template images. These results are used online to match segmented tools against the templates. The final module is the RTPG processor. Its role is to find the exact states of the tools given initial conditions provided by the ITPG module. The requirement that the initial conditions exist allows this module to make use of a local search (whereas the ITPG module had global scope). To perform the local search, 3D model matching is used, where a synthetic image of the object is created and compared to the sensed data. The availability of low-cost PC graphics hardware allows rapid creation of synthetic images. In this approach, a function of orientation, distance, and articulation is defined as a metric on the difference between the captured image and a synthetic image with an object in the given orientation, distance, and articulation. The synthetic image is created using a model that is looked up in an object-model database. A composable software architecture is used for implementation. Video is first preprocessed to remove sensor anomalies (like dead pixels), and then is processed sequentially by a prioritized list of tracker-identifiers.

English, James

First Order Temporal Logic Monitoring with BDDs

Runtime verification is aimed at analyzing execution traces stemming from a running program or system. The traditional purpose is to detect the lack of conformance with respect to a formal specification. Numerous efforts in the field have focused on monitoring so-called parametric specifications, where events carry data, and formulas can refer to such. Since a monitor for such specifications has to store observed data, the challenge is to have an efficient representation and manipulation of Boolean operators, quantification, and lookup of data. The fundamental problem is that the actual values of the data are not necessarily bounded or provided in advance. In this work we explore the use of Binary Decision Diagrams (BDDs) for representing observed data. Our experiments show a substantial improvement in performance compared to related work.

Ulus, Dogan

An interactive parallel programming environment applied in atmospheric science

This article introduces an interactive parallel programming environment (IPPE) that simplifies the generation and execution of parallel programs. One of the tasks of the environment is to generate message-passing parallel programs for homogeneous and heterogeneous computing platforms. The parallel programs are represented by using visual objects. This is accomplished with the help of a graphical programming editor that is implemented in Java and enables portability to a wide variety of computer platforms. In contrast to other graphical programming systems, reusable parts of the programs can be stored in a program library to support rapid prototyping. In addition, runtime performance data on different computing platforms is collected in a database. A selection process determines dynamically the software and the hardware platform to be used to solve the problem in minimal wall-clock time. The environment is currently being tested on a Grand Challenge problem, the NASA four-dimensional data assimilation system.

Interactive Display Devices

Adaptive Distributed Environment for Procedure Training (ADEPT)

ADEPT (Adaptive Distributed Environment for Procedure Training) is designed to provide more effective, flexible, and portable training for NASA systems controllers. When creating a training scenario, an exercise author can specify a representative rationale structure using the graphical user interface, annotating the results with instructional texts where needed. The author's structure may distinguish between essential and optional parts of the rationale, and may also include "red herrings" - hypotheses that are essential to consider, until evidence and reasoning allow them to be ruled out. The system is built from pre-existing components, including Stottler Henke's SimVentive instructional simulation authoring tool and runtime. To that, a capability was added to author and exploit explicit control decision rationale representations. ADEPT uses SimVentive's Scalable Vector Graphics (SVG)- based interactive graphic display capability as the basis of the tool for quickly noting aspects of decision rationale in graph form. The ADEPT prototype is built in Java, and will run on any computer using Windows, MacOS, or Linux. No special peripheral equipment is required. The software enables a style of student/ tutor interaction focused on the reasoning behind systems control behavior that better mimics proven Socratic human tutoring behaviors for highly cognitive skills. It supports fast, easy, and convenient authoring of such tutoring behaviors, allowing specification of detailed scenario-specific, but content-sensitive, high-quality tutor hints and feedback. The system places relatively light data-entry demands on the student to enable its rationale-centered discussions, and provides a support mechanism for fostering coherence in the student/ tutor dialog by including focusing, sequencing, and utterance tuning mechanisms intended to better fit tutor hints and feedback into the ongoing context.

Domeshek, Eric

Refining the Safety - Liveness Classification of Temporal Properties According to Monitorability

Runtime verification is the topic of analyzing execution traces using formal techniques. It includes monitoring the execution of a system against temporal properties, commonly to detect violations. Not every temporal property is fully monitorable however: in some cases, the correctness of the execution does not depend on any finite prefix. We study the connection between monitorability and Lamport’s classification of properties to safety and liveness and their dual classes.We refine the definition of monitorability and provide algorithms to check which verdicts can be expected, a priori and during runtime verification.

Peled, Doron

Characterizing the Impact of GPU Power Management on an Exascale System

As GPU-accelerated high-performance computing (HPC) systems approach exascale performance, controlling energy consumption without compromising throughput is essential. Architectures such as the AMD MI250X-based Frontier supercomputer provide runtime mechanisms like frequency and power capping, enabling energy tuning without modifying application code. Although both target energy reduction, they operate via distinct hardware control paths and influence workloads differently. We present a comprehensive evaluation of these strategies on a leadership-class system using diverse HPC proxy applications representative of production workloads. Our study analyzes performance–energy trade-offs across multiple capping levels, node counts (1 and 32), and application profiles. Results show that frequency capping generally achieves higher energy efficiency and scalability, with gains of up to 13.2% without performance loss, while power capping is more effective for single-node runs or bursty GPU utilization. We also provide practical guidelines to help system administrators and users balance energy efficiency and performance in large-scale scientific workloads.

Costa, Mariana [Universidade Federal do Rio Grande

Investigation into the Performance Benefits of Exposing Network Backpressure in UPC++ and GASNet-EX

This document is a brief summary of the research, and supporting development efforts, conducted by the project "Investigation into Improving Dynamic Adaptivity to System-Level Asynchrony in UPC++". We tested the hypothesis "The UPC++ and GASNet-EX runtimes can expose information from the network stack that enables applications to dynamically adapt to congestion, improving total throughput". We present experimental results from both a microbenchmark and an application benchmark that support this hypothesis.

97 MATHEMATICS AND COMPUTING

Ground and excited state gradients with end-to-end differentiable semiempirical quantum chemistry

Accurate and efficient gradients of molecular energy with respect to nuclear degrees of freedom are essential for geometry optimization and molecular dynamics, including simulations that go beyond the Born–Oppenheimer regime. A common approach involves deriving analytical formulas for new electronic structure methods, which is often conceptually difficult and requires tedious coding. Here, we implement analytical, semi-numerical, and automatic differentiation (AD)-based gradient pathways for semiempirical Hamiltonian models in the PYSEQM software package, leveraging both graphics processing unit (GPU) and central processing unit (CPU) architectures. We further extend these capabilities to excited states calculated using the configuration interaction singles and time-dependent Hartree–Fock ansätze. We benchmark wall time, peak memory usage, and accuracy across three molecular families of varying chemical complexity, including systems of up to a thousand atoms. For ground-state simulations, analytical and AD gradients achieve near-identical GPU runtimes, while semi-numerical gradients are slower on GPU but remain competitive on CPU. For excited states, both analytical and custom AD approaches using implicit differentiation show similar performance and low memory requirements, whereas gradients with full AD are memory-limited. AD gradients match analytical ones in accuracy across all tested systems, aided by a quaternion-based diatomic frame rotation for two-center quantities that ensures smooth energy surfaces. Overall, automatic differentiation emerges as a practical alternative to analytical gradients in semiempirical quantum chemistry, offering high accuracy while allowing seamless integration in AI-driven workflows and popular packages, such as PyTorch and JAX. Our results provide actionable guidance for selecting optimal gradient strategies in large-scale ground- and excited-state molecular dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Adaptive Fault Tolerance for Many-Core Based Space-Borne Computing

This paper describes an approach to providing software fault tolerance for future deep-space robotic NASA missions, which will require a high degree of autonomy supported by an enhanced on-board computational capability. Such systems have become possible as a result of the emerging many-core technology, which is expected to offer 1024-core chips by 2015. We discuss the challenges and opportunities of this new technology, focusing on introspection-based adaptive fault tolerance that takes into account the specific requirements of applications, guided by a fault model. Introspection supports runtime monitoring of the program execution with the goal of identifying, locating, and analyzing errors. Fault tolerance assertions for the introspection system can be provided by the user, domain-specific knowledge, or via the results of static or dynamic program analysis. This work is part of an on-going project at the Jet Propulsion Laboratory in Pasadena, California.

fault tolerance

Impact of refrigerant undercharge faults on building indoor conditions and HVAC system operation in residential Buildings: A simulation study

This study investigates the impact of refrigerant undercharge on indoor temperature and HVAC system performance in residential buildings. Simulation models for typical residential buildings in Orlando, FL and Indianapolis, IN were developed using the ResStock database. A refrigerant undercharge fault model was then applied to the simulations with varying levels of fault intensity. The paper offers an extensive analysis, revealing that variations in supply air temperature, equipment runtime, and cooling energy consumption due to the level of refrigerant undercharge faults are notably significant on a summer representative day. Similarly, on a winter representative day, changes in supply air temperature and runtime are significant as well as changes in supplemental heat energy consumption. We find that occupants may remain oblivious to these faults during the cooling season, particularly when the HVAC system is oversized; in that case, supply air temperature data could help detect a fault. Another challenge is that during the heating season, when the supplemental heater operates, it is difficult to identify a refrigerant undercharge fault using only indoor and supply air temperature data. Finally, this study finds that supply air temperature, equipment runtime, and supplemental heater energy consumption data can help in detecting refrigerant undercharge faults.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Fault-Tolerant, Real-Time, Multi-Core Computer System

A document discusses a fault-tolerant, self-aware, low-power, multi-core computer for space missions with thousands of simple cores, achieving speed through concurrency. The proposed machine decides how to achieve concurrency in real time, rather than depending on programmers. The driving features of the system are simple hardware that is modular in the extreme, with no shared memory, and software with significant runtime reorganizing capability. The document describes a mechanism for moving ongoing computations and data that is based on a functional model of execution. Because there is no shared memory, the processor connects to its neighbors through a high-speed data link. Messages are sent to a neighbor switch, which in turn forwards that message on to its neighbor until reaching the intended destination. Except for the neighbor connections, processors are isolated and independent of each other. The processors on the periphery also connect chip-to-chip, thus building up a large processor net. There is no particular topology to the larger net, as a function at each processor allows it to forward a message in the correct direction. Some chip-to-chip connections are not necessarily nearest neighbors, providing short cuts for some of the longer physical distances. The peripheral processors also provide the connections to sensors, actuators, radios, science instruments, and other devices with which the computer system interacts.

Gostelow, Kim P.

Characterization and thermometry of dissipatively stabilized steady states

In this work we study the properties of dissipatively stabilized steady states of noisy quantum algorithms, exploring the extent to which they can be well approximated as thermal distributions, and proposing methods to extract the effective temperature T. We study an algorithm called the relaxational quantum eigensolver (RQE), which is one of a family of algorithms that attempt to find ground states and balance error in noisy quantum devices. In RQE, we weakly couple a second register of auxiliary ‘shadow’ qubits to the primary system in Trotterized evolution, thus engineering an approximate zero-temperature bath by periodically resetting the auxiliary qubits during the algorithm’s runtime. Balancing the infinite temperature bath of random gate error, RQE returns states with an average energy equal to a constant fraction of the ground state. We probe the steady states of this algorithm for a range of base error rates, using several methods for estimating both T and deviations from thermal behavior. In particular, we both confirm that the steady states of these systems are often well-approximated by thermal distributions, and show that the same resources used for cooling can be adopted for thermometry, yielding a fairly reliable measure of the temperature. These methods could be readily implemented in near-term quantum hardware, and for stabilizing and probing Hamiltonians where simulating approximate thermal states is hard for classical computers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC

Three Years of on Orbit ISS Oxygen Generation System Operation 2007-2010

The International Space Station (ISS) United States Orbital Segment (USOS) Oxygen Generation System (OGS) has accumulated 240 days of continuous operation at varied oxygen production rates within the US Laboratory Module (LAB) since it was first activated in July 2007. OGS relocated from the ISS LAB to Node 3 during 20A Flight (February 2010). The OGS rack delivery was accelerated for on-orbit checkout in the LAB, and it was launched to ISS in July of 2006. During the on-orbit checkout interval within the LAB from July 2007 to October 2008, OGS operational times were limited by the quantity of feedwater in a Payload Water Reservoir (PWR) bag. Longer runtimes are now achievable due to the continuous feedwater availability after ULF2 delivery and activation of the USOS Water Recovery System (WRS) racks. OGS is considered a critical function to maintaining six crew capability. There have been a number of failures which interrupted or threatened to interrupt oxygen production. Filters in the recirculation loop have clogged and have been replaced, Hydrogen sensors have fallen out of specifications, a pump delta pressure sensor failed, a pump failed to start, and the voltage on the cell stack increased out of tolerance. This paper will discuss the operating experience and characteristics of the OGS, as well as operational issues and their resolution.

Diderich, Greg S.

DIMPLES: Distributed Influence Maximization for Pandemic pLanning on Exascale Systems

We study exascale parallel algorithms for the selection of intervention or monitoring strategies in massive realistic socio-technical networks through scalable Influence Maximization (InfMax) algorithms. We employ novel techniques to enable efficient scaling on up to 8k nodes of OLCF Frontier, with 65k AMD GPUs and 458k AMD CPU cores. Current state-of-the-art InfMax tools are limited to networks with only a few million actors (vertices) and a few hundred million interactions (edges). By overcoming these limitations, we show that our approach is capable of processing a realistic social contact network of the United States with 285 million nodes and about 8 billion edges. This two orders-of-magnitude improvement over the previous state-of-the-art is obtained by leveraging algorithmic advancements for the InfMax problem and designing several problem-specific approaches to overlap communication with computation, improve GPU efficiency, and lower the application’s memory requirements. We evaluate strong scaling for computing 10k most influential seeds using up to 8k nodes of an exascale system, and weak scaling from 128 to 8k system nodes for seed sets ranging from 625 to 40k seeds. We achieve the fastest-known runtime of 25 minutes while performing 48 million diffusion simulations totaling 2.31 petabytes to identify 40k influential seeds using 8k nodes, and take 5.75 minutes to identify 10k seeds while using 4k nodes.

Minutoli, Marco [Pacific Northwest National Labora

STEReO

STEReO brings together several technologies in Unmanned Aircraft Systems (UAS) Traffic Management (UTM), Autonomy, Communications, Human Factors, and Domain Expertise & Tools, aimed at providing scalability and flexibility, as well as operational resiliency to dynamic changes during a disaster event. Some of the concepts STEReO explores are: collaborative tools to ingest remote sensing information and distribute a common mission operating picture, apply ad-hoc communication networks to facilitate timely information sharing and communication of changes, vehicle-to-vehicle and onboard autonomy technologies ensure the safety and resiliency of operations, and apply NASA’s UAS traffic management system (UTM) as a public safety UAS Service Supplier (USS) to access and coordinate use of the airspace by both manned and unmanned operations. The potential benefits of STEReO include: standardized, cross-platform communication means increased interoperability and ease of cooperation/collaboration, increased situation awareness and common operating picture allow for earlier detection and decision making, and scalable to size and complexity of environment, operations, and mission objectives. This presentation gives an informational overview of the STEReO project to attendees of the Helicopter Association International (HAI) Aerial Firefighting Safety Conference. Note: Presentation slide 7 video is included in record as additional attachment, requires download of mp4 file, runtime 1 min 54 secs.

emergency response operations

Discrete versus continuous: Enhancing battery optimization in capacity expansion models

This study compares two battery modeling approaches for capacity expansion models: discrete-duration and continuous-duration formulations. In the discrete approach, battery duration is fixed, and power capacity is optimized. In the continuous approach, both power and energy capacities are decision variables, allowing storage duration to be optimized endogenously. Although both discrete-duration and continuous-duration battery formulations are used in long-term power system planning models, the literature has provided limited direct, systematic comparisons of their implications within a common modeling framework. To address this gap, this study implements both approaches in the Regional Energy Deployment System (ReEDS TM ) capacity expansion model using two resource adequacy methods, across a range of future system conditions, and with varying battery cost projections. Results show continuous-duration and high-resolution discrete approaches produce similar capacity expansion outcomes. The continuous formulation achieves faster runtimes compared to discrete-duration runs with many discrete-duration options. However, the discrete-duration approach allows users to choose to have limited fidelity for storage duration options, which in some cases can outperform the continuous formulation. The continuous formulation has the lowest overall system costs, indicating its ability to fine-tune storage duration to better meet specific system needs. This study's findings provide a side-by-side evaluation of discrete and continuous battery modeling approaches and offer guidance for improving the representation of real-world systems, flexibility, and computational efficiency for representing energy storage in long-term power system planning models.

25 ENERGY STORAGE