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At least 343 records · Page 19

miniGAN: a proxy application for generative adversarial networks

miniGAN is a python-based machine learning proxy application for generative adversarial networks, developed through the Exascale Computing Project's (ECP) ExaLearn project. It will be included in the main ECP proxy application and the machine learning proxy application suite. It is a proxy for ECP cosmological(CosmoFlow, ExaGAN) and wind energy(ExaWind) applications. miniGAN will be distributed to ECP hardware vendors as part of hardware codesign. miniGAN uses the Numpy/PyTorch/TensorFlow/Keras/Horovod frameworks and libraries. It also relies on the Kokkos and Kokkos-Kernels packages developed here at Sandia Labs. SAND2020-2038 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Ellis, John↗

Inventory Management Improvement Project

The Lawrence Livermore National Laboratory (LLNL) conducts research and development for the National Nuclear Security Agency (NNSA) and its affiliates. The Polymer AM team at LLNL conducts research and development in 3D printing, specifically direct-ink-write, in accordance with LLNL and NNSA missions. The team is composed of machine operators, chemists, testing engineers, and project engineers across multiple lab spaces with one shared storage area at LLNL. The operations use a variety of different consumables and hardware to conduct research applications for LLNL and NNSA. These items are critical to performing operation tasks; if an item is out of stock, operations associated with the respective item could be suspended for weeks. As such, the Polymer AM team manages an inventory of spare consumables and hardware to ensure these items are always available. However, the current management system, an excel sheet managed by the project engineer group, is not intuitive in providing inventory information despite the high labor utilization needed to maintain the system. As such, the team is looking to improve their inventory management that can send notifications regarding inventory needs, accessible to other team members, provide all relevant information to a specific item, and store historical information for budget and operation planning. The proposed solution is a Computer Maintenance Management System (CMMS): a web-based management software that stores inventory information and provides automated notifications. The system will store information on each item including quantity in stock, technical information, supplier information, costs, lead times, and expiration date. The system has a notifications function that can send notifications to the respective team member’s when an item needs to be counted, item inventory is low, or an item is approaching their expiration date. Information for each item can be tracked over time creating data to be used for budget planning and process improvement purposes. Due to its web-based source, the system can be accessed by the respective team member viewing technical information, quantity, and purchasing information.

42 ENGINEERING↗

Simulating lossy Gaussian boson sampling with matrix-product operators

Gaussian boson sampling, a computational model that is widely believed to admit quantum supremacy, has already been experimentally demonstrated and is claimed to surpass the classical simulation capabilities of even the most powerful supercomputers today. However, whether the current approach limited by photon loss and noise in such experiments prescribes a scalable path to quantum advantage is an open question. Here, to understand the effect of photon loss on the scalability of Gaussian boson sampling, we analytically derive the asymptotic operator entanglement entropy scaling, which relates to the simulation complexity. As a result, we observe that efficient tensor network simulations are likely possible under the N out ∝ √N scaling of the number of surviving photons N out in the number of input photons N. We numerically verify this result using a tensor network algorithm with U⁡(1) symmetry, and we overcome previous challenges due to the large local Hilbert-space dimensions in Gaussian boson sampling with hardware acceleration. Additionally, we observe that increasing the photon number through larger squeezing does not increase the entanglement entropy significantly. Finally, we numerically find the bond dimension necessary for fixed accuracy simulations, providing more direct evidence for the complexity of tensor networks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Autonomy Loops for Monitoring, Operational Data Analytics, Feedback, and Response in HPC Operations

Many High Performance Computing (HPC) facilities have developed and deployed frameworks in support of continuous monitoring and operational data analytics (MODA) to help improve efficiency and throughput. Because of the complexity and scale of systems and workflows and the need for low-latency response to address dynamic circumstances, automated feedback and response have the potential to be more effective than current human-in-the-loop approaches which are laborious and error prone. Progress has been limited, however, by factors such as the lack of infrastructure and feedback hooks, and successful deployment is often site- and case-specific. In this position paper we report on the outcomes and plans from a recent Dagstuhl Seminar, seeking to carve a path for community progress in the development of autonomous feedback loops for MODA, based on the established formalism of similar (MAPE-K) loops in autonomous computing and self-adaptive systems. By defining and developing such loops for significant cases experienced across HPC sites, we seek to extract commonalities and develop conventions that will facilitate interoperability and interchangeability with system hardware, software, and applications across different sites, and will motivate vendors and others to provide telemetry interfaces and feedback hooks to enable community development and pervasive deployment of MODA autonomy loops.

autonomy loops↗

New hardware and software platform for experiments on a HUBER-5042 X-ray diffractometer with a DISPLEX DE-202 helium cryostat in the temperature range of 20–300 K

Huber-5042 diffractometer with a closed-cycle Displex DE-202 helium cryostat is a unique scientific instrument for carrying out X-ray diffraction experiments when studying the single crystal structure in the temperature range of 20–300 K. To make the service life longer and develop new experimental techniques, the diffractometer control is transferred to a new hardware and software platform. To this end, a modern computer; a new detector reader unit; and new control interfaces for stepper motors, temperature controller, and cryostat vacuum pumping system are used. The system for cooling the X-ray tube, the high-voltage generator, and the helium compressor and pump for maintaining the desired vacuum in the cryostat are replaced. The system for controlling the primary beam shutter is upgraded. A biological shielding is installed. The new program tools, which use the Linux Ubuntu operating system and SPEC constructor, include a set of drivers for control units through the aforementioned interfaces. A program for searching reflections from a sample using fast continuous scanning and a priori information about crystal is written. Thus, the software package for carrying out the complete cycle of precise diffraction experiment (from determining the crystal unit cell to calculating the integral reflection intensities) is upgraded. High quality of the experimental data obtained on this equipment is confirmed in a number of studies in the temperature range from 20 to 300 K.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

GPU-accelerated Tersoff potentials for massively parallel Molecular Dynamics simulations

The Tersoff potential is one of the empirical many-body potentials that has been widely used in simulation studies at atomic scales. Unlike pair-wise potentials, the Tersoff potential involves three-body terms, which require much more arithmetic operations and data dependency. In this contribution, we have implemented the GPU-accelerated version of several variants of the Tersoff potential for LAMMPS, an open-source massively parallel Molecular Dynamics code. Compared to the existing MPI implementation in LAMMPS, the GPU implementation exhibits a better scalability and offers a speedup of 2.2X when run on 1000 compute nodes on the Titan supercomputer. On a single node, the speedup ranges from 2.0 to 8.0 times, depending on the number of atoms per GPU and hardware configurations. The most notable features of our GPU-accelerated version include its design for MPI/accelerator heterogeneous parallelism, its compatibility with other functionalities in LAMMPS, its ability to give deterministic results and to support both NVIDIA CUDA- and OpenCL-enabled accelerators. Our implementation is now part of the GPU package in LAMMPS and accessible for public use.

Computer Science↗

VISION: a modular AI assistant for natural human-instrument interaction at scientific user facilities

Scientific user facilities, such as synchrotron beamlines, are equipped with a wide array of hardware and software tools that require a codebase for human-computer-interaction. This often necessitates developers to be involved to establish connection between users/researchers and the complex instrumentation. The advent of generative AI presents an opportunity to bridge this knowledge gap, enabling seamless communication and efficient experimental workflows. Here we present a modular architecture for the Virtual Scientific Companion by assembling multiple AI-enabled cognitive blocks that each scaffolds large language models (LLMs) for a specialized task. With VISION, we performed LLM-based operation on the beamline workstation with low latency and demonstrated the first voice-controlled experiment at an x-ray scattering beamline. The modular and scalable architecture allows for easy adaptation to new instruments and capabilities. Development on natural language-based scientific experimentation is a building block for an impending future where a science exocortex—a synthetic extension to the cognition of scientists—may radically transform scientific practice and discovery.

36 MATERIALS SCIENCE↗

Emulating the Android Boot Process

Critical vulnerabilities continue to be discovered in the boot process of Android smartphones used around the world. The entire device's security is compromised if boot security is compromised, so any weakness presents undue risk to users. Vulnerabilities persist, in part, because independent security analysts lack access and appropriate tools. In response to this gap, we implemented a procedure for emulating the early phase of the Android boot process. This work demonstrated feasibility and utility of emulation in this space. By using HALucinator, we derived execution context and data flow, as well as incorporated peripheral hardware behavior. While smartphones with shared processors have substantial code overlap regardless of vendor, generational changes can have a significant impact. By applying our approach to older and modern devices, we learned interesting characteristics about the system. Such capabilities introduce new levels of introspection and operation understanding not previously available to mobile researchers.

97 MATHEMATICS AND COMPUTING↗

Development of Microreactor Automated Control System (MACS): Surrogate Plant-level Modeling and Control Algorithms Integration

This report discusses progress on the modeling and integration task as part of the development of Microreactor Automated Control System (MACS). What follows is a discussion of the software tools used to develop a surrogate microreactor plant-level model, MACS module development, and a summary of the findings from integration with a hardware-in-the-loop (HIL) setup at Idaho National Laboratory (INL). Oak Ridge National Laboratory worked with INL to understand available hardware at INL (such as existing control platforms). With this information and using a preliminary framework for MACS with software interfaces defined, surrogate models and initial automated control algorithms were created for integration into the hardware to provide a HIL demonstration platform for MACS. Available reduced order reactor models that leverage existing microreactor neutronics and thermal hydraulics models have been integrated in the surrogate plant-level model. The surrogate model has been evaluated for sensitivity of all parameters and the MACS software modules (including the surrogate model) have been demonstrated to interact with the hardware. The integration, however, pointed to the need for further improvements to the framework—and specifically improvements to the interfaces to ensure that the HIL simulator is capable of longer-term stable operation with MACS in the loop. These improvements will be the focus of future research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Adaptive Cyber-Physical Resilience for Building Control Systems

The main goal of the project is to develop an AI-based process layer cybersecurity suite for detection, isolation and mitigation of cyber-attack effects on operation of building energy management systems (BEMS). The following constituent key technologies were developed under the program towards fulfilling the program objectives: (1) developed a high fidelity BEMS testbed for generation of training data and validation of developed technologies; (2) developed a physics informed ML based attack detection and localization module (ADL) capable of detecting high impact stealthy attacks (HISA - attacks causing 30% energy utilization but no immediate visible impact otherwise) with 98% accuracy; (3) developed a methodology to determine ’representative days’ to limit the data required for training; (4) developed a virtual sensing system that can reconstruct affected sensors with 10% error for the same HISA set; (5) developed a resilient model predictive control system that can continue operation of the BEMS without jeopardizing stability for the HISA set; and (6) integrated and deployed all the constituent modules and demonstrated the efficacy of the technology in real-time in a hardware in loop simulation.

42 ENGINEERING↗

Preliminary Study on Fine-Grained Power and Energy Measurements on Grace Hopper GH200 with Open-Source Performance Tools

The increasing adoption of tightly integrated, heterogeneous architectures, combined with the slowdown of Moore’s law, has made application power and energy-driven optimizations critical to efficiently use high-performance computing systems. This paper introduces a newly developed open-source toolkit that seamlessly integrates the Linux real-time hardware monitoring program hwmon with the Performance Application Programming Interface and the Score-P performance measurement system, thereby enabling fine-grained power and energy measurements for high-performance computing applications. Our primary target platform is the Wombat test bed, which is a system based on the NVIDIA GH200 superchip. The toolkit can capture transient power peaks with high temporal resolution (50 ms) and, thanks to Score-P integration, can map power metrics to specific code regions, thereby providing actionable information on power-intensive operations and inefficiencies. The toolkit also provides a holistic view of both the power and the energy consumption of the entire GH200 superchip by covering all major components: the Grace CPU, the Hopper GPU, and the I/O subsystem. Experiments that use Locally Self-consistent Multiple Scattering, which is an application for first-principles calculations of materials developed at Oak Ridge National Laboratory, have demonstrated the tool’s ability to identify transient power spikes and uncover opportunities for energy-aware optimizations. Additionally, we introduce a Python-based utility for converting Open Trace Format 2 traces to Parquet format, thus enabling advanced data analysis for numerical integration methods applied to power data for accurate energy profiling.

Hernandez Mendoza, Oscar [ORNL] (ORCID:00000002538↗

Impact of dynamics, entanglement and Markovian noise on the fidelity of few-qubit digital quantum simulation

Quantum algorithms have been proposed to accelerate the simulation of the chaotic dynamical systems that are ubiquitous in the physics of plasmas. Quantum computers without error correction might even use noise to their advantage to calculate the Lyapunov exponent by measuring the Loschmidt echo fidelity decay rate. For the first time, digital Hamiltonian simulations of the quantum sawtooth map, performed on the IBM-Q quantum hardware platform, show that the fidelity decay rate of a digital quantum simulation increases during the transition from dynamical localization to chaotic diffusion in the map. The observed error per CNOT gate increases by $1.5{\times }$ as the dynamics varies from localized to diffusive, while only changing the phases of virtual RZ gates and keeping the overall gate count constant. A gate-based Lindblad noise model that captures the effective change in relaxation and dephasing errors during gate operation qualitatively explains the effect of dynamics on fidelity as being due to the localization and entanglement of the states created. Specifically, highly delocalized states that are entangled with random phases show an increased sensitivity to dephasing and, on average, a similar sensitivity to relaxation as localized states. In contrast, delocalized unentangled states show an increased sensitivity to dephasing but a lower sensitivity to relaxation. This gate-based Lindblad model is shown to be a useful benchmarking tool by estimating the effective Lindblad coherence times during CNOT gates and finding a consistent $2\unicode{x2013}3{\times }$ shorter $T_2$ time than reported for idle qubits. Thus, the interplay of the dynamics of a simulation with the noise processes that are active can strongly influence the overall fidelity decay rate.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Empowering a qudit-based quantum processor by traversing the dual bosonic ladder

Abstract High-dimensional quantum information processing has emerged as a promising avenue to transcend hardware limitations and advance the frontiers of quantum technologies. Harnessing the untapped potential of the so-called qudits necessitates the development of quantum protocols beyond the established qubit methodologies. Here, we present a robust, hardware-efficient, and scalable approach for operating multidimensional solid-state systems using Raman-assisted two-photon interactions. We then utilize them to construct extensible multi-qubit operations, realize highly entangled multidimensional states including atomic squeezed states and Schrödinger cat states, and implement programmable entanglement distribution along a qudit array. Our work illuminates the quantum electrodynamics of strongly driven multi-qudit systems and provides the experimental foundation for the future development of high-dimensional quantum applications such as quantum sensing and fault-tolerant quantum computing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

MO-AB-204-00: Interoperability in Radiation Oncology: IHE-RO Committee Update

You’ve experienced the frustration: vendor A’s device claims to work with vendor B’s device, but the practice doesn’t match the promise. Getting devices working together is the hidden art that Radiology and Radiation Oncology staff have to master. To assist with that difficult process, the Integrating the Healthcare Enterprise (IHE) effort was established in 1998, with the coordination of the Radiological Society of North America. Integrating the Healthcare Enterprise (IHE) is a consortium of healthcare professionals and industry partners focused on improving the way computer systems interconnect and exchange information. This is done by coordinating the use of published standards like DICOM and HL7. Several clinical and operational IHE domains exist in the healthcare arena, including Radiology and Radiation Oncology. The ASTRO-sponsored IHE Radiation Oncology (IHE-RO) domain focuses on radiation oncology specific information exchange. This session will explore the IHE Radiology and IHE RO process for; IHE solicitation process for new profiles. Improving the way computer systems interconnect and exchange information in the healthcare enterprise Supporting interconnectivity descriptions and proof of adherence by vendors Testing and assuring the vendor solutions to connectivity problems. Including IHE profiles in RFPs for future software and hardware purchases. Learning Objectives: Understand IHE role in improving interoperability in health care. Understand process of profile development and implantation. Understand how vendors prove adherence to IHE RO profiles. S. Hadley, ASTRO Supported Activity.

60 APPLIED LIFE SCIENCES↗

MO-AB-204-01: IHE RO Overview [Health Care]

You’ve experienced the frustration: vendor A’s device claims to work with vendor B’s device, but the practice doesn’t match the promise. Getting devices working together is the hidden art that Radiology and Radiation Oncology staff have to master. To assist with that difficult process, the Integrating the Healthcare Enterprise (IHE) effort was established in 1998, with the coordination of the Radiological Society of North America. Integrating the Healthcare Enterprise (IHE) is a consortium of healthcare professionals and industry partners focused on improving the way computer systems interconnect and exchange information. This is done by coordinating the use of published standards like DICOM and HL7. Several clinical and operational IHE domains exist in the healthcare arena, including Radiology and Radiation Oncology. The ASTRO-sponsored IHE Radiation Oncology (IHE-RO) domain focuses on radiation oncology specific information exchange. This session will explore the IHE Radiology and IHE RO process for; IHE solicitation process for new profiles. Improving the way computer systems interconnect and exchange information in the healthcare enterprise Supporting interconnectivity descriptions and proof of adherence by vendors Testing and assuring the vendor solutions to connectivity problems. Including IHE profiles in RFPs for future software and hardware purchases. Learning Objectives: Understand IHE role in improving interoperability in health care. Understand process of profile development and implantation. Understand how vendors prove adherence to IHE RO profiles. S. Hadley, ASTRO Supported Activity.

60 APPLIED LIFE SCIENCES↗

MO-AB-204-02: IHE RAD [Health care]

You’ve experienced the frustration: vendor A’s device claims to work with vendor B’s device, but the practice doesn’t match the promise. Getting devices working together is the hidden art that Radiology and Radiation Oncology staff have to master. To assist with that difficult process, the Integrating the Healthcare Enterprise (IHE) effort was established in 1998, with the coordination of the Radiological Society of North America. Integrating the Healthcare Enterprise (IHE) is a consortium of healthcare professionals and industry partners focused on improving the way computer systems interconnect and exchange information. This is done by coordinating the use of published standards like DICOM and HL7. Several clinical and operational IHE domains exist in the healthcare arena, including Radiology and Radiation Oncology. The ASTRO-sponsored IHE Radiation Oncology (IHE-RO) domain focuses on radiation oncology specific information exchange. This session will explore the IHE Radiology and IHE RO process for; IHE solicitation process for new profiles. Improving the way computer systems interconnect and exchange information in the healthcare enterprise Supporting interconnectivity descriptions and proof of adherence by vendors Testing and assuring the vendor solutions to connectivity problems. Including IHE profiles in RFPs for future software and hardware purchases. Learning Objectives: Understand IHE role in improving interoperability in health care. Understand process of profile development and implantation. Understand how vendors prove adherence to IHE RO profiles. S. Hadley, ASTRO Supported Activity.

60 APPLIED LIFE SCIENCES↗

MO-AB-204-03: Profile Development and IHE Process

You’ve experienced the frustration: vendor A’s device claims to work with vendor B’s device, but the practice doesn’t match the promise. Getting devices working together is the hidden art that Radiology and Radiation Oncology staff have to master. To assist with that difficult process, the Integrating the Healthcare Enterprise (IHE) effort was established in 1998, with the coordination of the Radiological Society of North America. Integrating the Healthcare Enterprise (IHE) is a consortium of healthcare professionals and industry partners focused on improving the way computer systems interconnect and exchange information. This is done by coordinating the use of published standards like DICOM and HL7. Several clinical and operational IHE domains exist in the healthcare arena, including Radiology and Radiation Oncology. The ASTRO-sponsored IHE Radiation Oncology (IHE-RO) domain focuses on radiation oncology specific information exchange. This session will explore the IHE Radiology and IHE RO process for; IHE solicitation process for new profiles. Improving the way computer systems interconnect and exchange information in the healthcare enterprise Supporting interconnectivity descriptions and proof of adherence by vendors Testing and assuring the vendor solutions to connectivity problems. Including IHE profiles in RFPs for future software and hardware purchases. Learning Objectives: Understand IHE role in improving interoperability in health care. Understand process of profile development and implantation. Understand how vendors prove adherence to IHE RO profiles. S. Hadley, ASTRO Supported Activity.

60 APPLIED LIFE SCIENCES↗

MO-AB-204-04: Connectathons and Testing

You’ve experienced the frustration: vendor A’s device claims to work with vendor B’s device, but the practice doesn’t match the promise. Getting devices working together is the hidden art that Radiology and Radiation Oncology staff have to master. To assist with that difficult process, the Integrating the Healthcare Enterprise (IHE) effort was established in 1998, with the coordination of the Radiological Society of North America. Integrating the Healthcare Enterprise (IHE) is a consortium of healthcare professionals and industry partners focused on improving the way computer systems interconnect and exchange information. This is done by coordinating the use of published standards like DICOM and HL7. Several clinical and operational IHE domains exist in the healthcare arena, including Radiology and Radiation Oncology. The ASTRO-sponsored IHE Radiation Oncology (IHE-RO) domain focuses on radiation oncology specific information exchange. This session will explore the IHE Radiology and IHE RO process for; IHE solicitation process for new profiles. Improving the way computer systems interconnect and exchange information in the healthcare enterprise Supporting interconnectivity descriptions and proof of adherence by vendors Testing and assuring the vendor solutions to connectivity problems. Including IHE profiles in RFPs for future software and hardware purchases. Learning Objectives: Understand IHE role in improving interoperability in health care. Understand process of profile development and implantation. Understand how vendors prove adherence to IHE RO profiles. S. Hadley, ASTRO Supported Activity.

61 RADIATION PROTECTION AND DOSIMETRY↗