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Early estimation of resource expenditures and program size

A substantial amount of software engineering research effort was focused on the development of software estimation models. A measure of lines of code was derived based on the origin of the delivered code, L sub dev = N + E + 0.2 (S + O) (where L sub dev = developed lines of code, N = newly implemented lines of code, E = extensively modified lines of code, S = slightly modified lines of code, and O = old unchanged lines of code) that is substituted in the following equation H sub s = aL sup b (where H sub s = staff-hours of effort, L = lines of code, a = a constant, and b = a constant). The limitations of this model are discussed and some alternative estimation models that can be used earlier in the development process are proposed.

Card, D.↗

Potential for Measurement of Trace Volatile Organic Compounds in Closed Environments Using Gas Chromatograph/Differential Mobility Spectrometer

For nearly 3.5 years, the Volatile Organic Analyzer (VOA) has routinely analyzed the International Space Station (ISS) atmosphere for a target list of approximately 20 volatile organic compounds (VOCs). Additionally, an early prototype of the VOA collected data aboard submarines in two separate trials. Comparison of the data collected on ISS and submarines showed a surprising similarity in the atmospheres of the two environments. Furthermore, in both cases it was demonstrated that the VOA data can detect hardware issues unrelated to crew health. Finally, it was also clear in both operations that the VOA s size and resource consumption were major disadvantages that would restrict its use in the future. The VOA showed the value of measuring VOCs in closed environments, but it had to be shrunk if it was to be considered for future operations in these environments that are characterized by cramped spaces and limited resources. The Sionex Microanalyzer is a fraction of the VOA s size and this instrument seems capable of maintaining or improving upon the analytical performance of the VOA. The two design improvements that led to a smaller, less complex instrument are the Microanalyzer s use of recirculated air as the gas chromatograph s carrier gas and a micromachined detector. Although the VOA s ion mobility spectrometer and the Microanalyzer s differential mobility spectrometer (DMS) are related detector technologies, the DMS was more amenable to micromachining. This paper will present data from the initial assessment of the Microanalyzer. The instrument was challenged with mixtures that simulated the VOCs typically detected in closed-environment atmospheres.

Limero, Thomas↗

SPARC-X: Quantum simulations at extreme scale - reactive dynamics from first principles

We have developed the massively parallel electronic structure code SPARC-X: a computational framework for performing Kohn-Sham Density Functional Theory (DFT) calculations that can scale linearly with the number of atoms in the system, while being able to leverage petascale and emerging exascale parallel computers to study chemical phenomena at unprecedented length and time scales. SPARC-X exploits a recent breakthrough in electronic structure methodologies: systematically improvable, strictly local, orthonormal, discontinuous real-space bases that efficiently and systematically capture the local chemistry of the system. With further adaptation using new machine-learning techniques and the use of the massively parallel Spectral Quadrature (SQ) electronic structure method, the algorithmic complexity and prefactor associated with DFT calculations involving semilocal as well as hybrid functionals are dramatically reduced. Using petascale computational resources, SPARC-X enables quantum mechanical simulations at length and time scales previously accessible only by empirical approaches, e.g., 1,000,000 atoms for a few picoseconds using semilocal functionals or 1,000 atoms for a few picoseconds using hybrid functionals. Using exascale resources, the sizes and times targeted are two orders of magnitude larger. Such a capability has applications in a wide variety of chemical sciences, including reactive interfaces where large length- and/or long time-scales are needed and traditional force fields fail. This is particularly important in dynamic catalysis, where bond breaking and formation must be understood in detail. We developed, tested, and employed the SPARC-X framework to understand the photocatalytic properties of TiO 2 nanoparticles, revealing finite size effects that cannot be captured with standard model systems or functionals. This integrated development and application strategy ensures that SPARC-X remains a robust, efficient, and scalable software package for quantum simulations on current petascale and emerging exascale computing resources.

97 MATHEMATICS AND COMPUTING↗

Optimality and Noise Resilience of Critical Quantum Sensing

We compare critical quantum sensing to passive quantum strategies to perform frequency estimation, in the case of single-mode quadratic Hamiltonians. We show that, while in the unitary case both strategies achieve precision scaling quadratic with the number of photons, in the presence of dissipation this is true only for critical strategies. We also establish that working at the exceptional point or beyond threshold provides suboptimal performance. This critical enhancement is due to the emergence of a transient regime in the open critical dynamics, and is invariant to temperature changes. When considering both time and system size as resources, for both strategies the precision scales linearly with the product of the total time and the number of photons, in accordance with fundamental bounds. However, we show that critical protocols outperform optimal passive strategies if preparation and measurement times are not negligible. Our results are applicable to a broad variety of critical sensors whose phenomenology can be reduced to that of a single-mode quadratic Hamiltonian, including systems described by finite-component and fully connected models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Developing And Scaling an OpenFOAM Model to Study Turbulent Flow in a HFIR Coolant Channel

Improving the understanding of how computational fluid dynamics (CFD) direct numerical simulations (DNS) of flows in the High Flux Isotope Reactor (HFIR) perform when run in parallel using the high performance computing (HPC) platform Summit at the Oak Ridge Leadership Computing Facility (OLCF) is of particular importance to boost the computational tools used to support HFIR conversion to low enriched fuel (LEU). Evaluation of scaling performance was driven by the increasing importance of graphics processing unit (GPU) usage in HPC, which is becoming the standard for modern supercomputers such as Summit. The desired results are to obtain a strong positive correlation between the computational resources dedicated to a problem and the relative speed-up of the simulation in comparison to a benchmark. This capability will allow substantially improvement in HFIR flow analytical capabilities, specifically when predicting turbulence properties at high Reynolds numbers. The study leverages previous simulation results performed with code PHASTA (finite element) on HPC platforms Cori (NERSC) and Theta (ALCF) [1] with computing options provided in the computing platform OpenFOAM (finite volume) at OLCF. Transitioning from PHASTA to OpenFOAM will (1) eliminate dependence on third-party software for mesh generation and manipulation, (2) reduce resource needs by employing modern architectures, and (3) build expertise for future modeling of HFIR-specific problems like heat transfer in involute geometry, entrance effects, flow structure in channel corners, and so on—all important issues when defining the available thermal margins in the transition to LEU. CPUs and GPUs differ significantly in their architecture and utilization, as discussed in the literature [2]. The most important differences are in the approach to computations and their memory. A single GPU contains a large quantity of cores, enabling it to perform with a much higher throughput than a CPU, but execution requires a different approach. GPU codes execute instructions using the Single-Instruction Multiple-Thread (SIMT) approach in which a single instruction is used for groups of threads called warps. A warp typically consists of 32 threads which must execute the same set of instructions, although on separate threads. Alternately, a CPU has far fewer cores that are much more flexible in their operation, excelling at quickly performing more complex serial computations. This is why GPUs have greater throughput when properly utilized. The second important difference is seen when comparing their memory spaces. Limited memory allocations and CPU–GPU communications cause a significant bottleneck in GPU-accelerated programs. Further study was required to properly take advantage of GPU resources. A comprehensive analysis of code performance and the model-specific features of turbulence constitutes the core of this work. In this study, a DNS simulation of HFIR channel turbulence was performed with the finite volume CFD code OpenFOAM v2112 and CUDA v11.0 on Red Hat Enterprise Linux v8.2. The OpenFOAM installation had AMGx integrated to enable GPU acceleration and utilizes the PETSc4FOAM library. The computational resources and the problem size were scaled on CPU and CPU + GPU architectures to gain a better understanding of the performance of a DNS problem on modern computing hardware. The study aimed to analyze the scaling of the code exclusively on CPUs and then to examine the scaling of the codes with GPU acceleration enabled. Scaling studies included CPU and GPU acceleration on a mesh of varying resolution to analyze the impact of problem size relative to computational resources. In the course of preparing the GPU configuration on Summit, mainly using the AMGX solvers, difficulties were encountered stemming from constant changes resulting from extensive ongoing development activities and the changing environment. This resulted in the inability to complete the GPU portion of the work. The code was compiled and tested, but production runs to assess acceleration were not performed because the used discretional compute time allocation expired as year-end approached. The Summit HPC platform is scheduled for decommissioning in 2024, making it unattractive for future use with Nvidia-based GPUs. Therefore, the work will be moved onto NERSC machines in FY24. An application was prepared and submitted, and sufficient node-hours were awarded to continue the research in the next calendar year. This report summarizes work performed thus far, which mostly focused on CPU OpenFOAM computing.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Miniature GC-Minicell Ion Mobility Spectrometer (IMS) for In Situ Measurements in Astrobiology Planetary Missions

Astrobiology flight experiments require highly sensitive instrumentation for in situ analysis of volatile chemical species and minerals present in the atmospheres and surfaces of planets, moons, and asteroids. The complex mixtures encountered place a heavy burden on the analytical instrumentation to detect and identify all species present. The use of land rovers and balloon aero-rovers place additional emphasis on miniaturization of the analytical instrumentation. In addition, smaller instruments, using tiny amounts of consumables, allow the use of more instrumentation and/or ionger mission life for stationary landers/laboratories. The miniCometary Ice and Dust Experiment (miniCIDEX), which combined Gas Chromatography (GC) with helium Ion Mobility Spectrometry (IMS), was capable of providing the wide range of analytical information required for Astrobiology missions. The IMS used here was based on the PCP model 111 IMS. A similar system, the Titan Ice and Dust Experiment (TIDE), was proposed as part of the Titan Orbiter Aerorover Mission (TOAM). Newer GC systems employing Micro Electro- Mechanical System (MEMS) based technology have greatly reduced both the size and resource requirements for space GCs. These smaller GCs, as well as the continuing miniaturization of Astrobiology analytical instruments in general, has highlighted the need for smaller, dry helium IMS systems. We describe here the development of a miniature, MEMS GC-IMS system (MEMS GC developed by Thorleaf Research Inc.), employing the MiniCell Ion Mobility Spectrometer (IMS), from Ion Applications Inc., developed through NASA's Astrobiology Science and Technology Instrument Development (ASTID) Program and NASA s Small Business Innovative Research (SBIR) Program.

Kojiro, Daniel R.↗

Economic dispatch of offshore renewable energy resources for islanded communities with optimal storage sizing

Coastal or isolated microgrids depend on diesel generators and could benefit from renewable energy resources, especially offshore wind and wave energy. Integrating these resources into microgrids is complicated by their high intermittency, which requires optimal economic dispatch to effectively evaluate. This study considers three coastal or islanded sites, and uses mid-fidelity models of wind and wave energy technologies, and local demand data to solve the optimal economic dispatch problem. An optimal storage sizing method is developed that finds the smallest capacity of energy storage required to meet the microgrid load during each season. The storage capacity decreases by a factor of two at most when adding wave energy converters to a system. Adding wave energy converters to a farm decreases cost by about 30%. Furthermore, the required storage size varies by two to three times from summer to winter. Compared with the state-of-the-art approaches that often overlook realistic offshore renewable energy technology in microgrid economic dispatch and optimal storage sizing, the proposed solution introduced in this study allows for better site selection, microgrid design, converter selection, and storage sizing considerations for isolated microgrids.

16 TIDAL AND WAVE POWER↗

SAD5 Stereo Correlation Line-Striping in an FPGA

High precision SAD5 stereo computations can be performed in an FPGA (field-programmable gate array) at much higher speeds than possible in a conventional CPU (central processing unit), but this uses large amounts of FPGA resources that scale with image size. Of the two key resources in an FPGA, Slices and BRAM (block RAM), Slices scale linearly in the new algorithm with image size, and BRAM scales quadratically with image size. An approach was developed to trade latency for BRAM by sub-windowing the image vertically into overlapping strips and stitching the outputs together to create a single continuous disparity output. In stereo, the general rule of thumb is that the disparity search range must be 1/10 the image size. In the new algorithm, BRAM usage scales linearly with disparity search range and scales again linearly with line width. So a doubling of image size, say from 640 to 1,280, would in the previous design be an effective 4 of BRAM usage: 2 for line width, 2 again for disparity search range. The minimum strip size is twice the search range, and will produce an output strip width equal to the disparity search range. So assuming a disparity search range of 1/10 image width, 10 sequential runs of the minimum strip size would produce a full output image. This approach allowed the innovators to fit 1280 960 wide SAD5 stereo disparity in less than 80 BRAM, 52k Slices on a Virtex 5LX330T, 25% and 24% of resources, respectively. Using a 100-MHz clock, this build would perform stereo at 39 Hz. Of particular interest to JPL is that there is a flight qualified version of the Virtex 5: this could produce stereo results even for very large image sizes at 3 orders of magnitude faster than could be computed on the PowerPC 750 flight computer. The work covered in the report allows the stereo algorithm to run on much larger images than before, and using much less BRAM. This opens up choices for a smaller flight FPGA (which saves power and space), or for other algorithms in addition to SAD5 to be run on the same FPGA.

Villalpando, Carlos Y.↗

Inferred Lunar Boulder Distributions at Decimeter Scales

Block size distributions of impact deposits on the Moon are diagnostic of the impact process and environmental effects, such as target lithology and weathering. Block size distributions are also important factors in trafficability, habitability, and possibly the identification of indigenous resources. Lunar block sizes have been investigated for many years for many purposes [e.g., 1-3]. An unresolved issue is the extent to which lunar block size distributions can be extrapolated to scales smaller than limits of resolution of direct measurement. This would seem to be a straightforward statistical application, but it is complicated by two issues. First, the cumulative size frequency distribution of observable boulders rolls over due to resolution limitations at the small end. Second, statistical regression provides the best fit only around the centroid of the data [4]. Confidence and prediction limits splay away from the best fit at the endpoints resulting in inferences in the boulder density at the CPR scale that can differ by many orders of magnitude [4]. These issues were originally investigated by Cintala and McBride [2] using Surveyor data. The objective of this study was to determine whether the measured block size distributions from Lunar Reconnaissance Orbiter Camera - Narrow Angle Camera (LROC-NAC) images (m-scale resolution) can be used to infer the block size distribution at length scales comparable to Mini-RF Circular Polarization Ratio (CPR) scales, nominally taken as 10 cm. This would set the stage for assessing correlations of inferred block size distributions with CPR returns [6].

Baloga, S. M.↗

Microreactor System Design for a NASA In Situ Propellant Production Plant on Mars

The NASA In Situ Resource Utilization (ISRU) program is planning near-term missions to Mars that will include chemical processes for converting the carbon dioxide (CO2) and possibly water from the Martian environment to propellants, oxygen, and other useful chemicals. The use of indigenous resources reduces the size and weight of the payloads from Earth significantly, representing enormous cost savings that make human exploration of Mars affordable. Extraterrestrial chemical processing plants will need to be compact, lightweight, highly efficient under reduced gravity, and extraordinarily reliable for long periods. Microchemical and thermal systems represent capability for dramatic reduction in size and weight, while offering high reliability through massive parallelization. In situ propellant production (ISPP), one aspect of the ISRU program, involves collecting and pressurizing atmospheric CO2, conversion reactions, chemical separations, heat exchangers, and cryogenic storage. A preliminary system design of an ISPP plant based on microtechnology has demonstrated significant size, weight, and energy efficiency gains over the current NASA baseline. Energy management is a strong driver for Mars-based processes, not only because energy is a scarce resource, but because heat rejection is problematic; the low pressure environment makes convective heat transfer ineffective. Energy efficiency gains are largely achieved in the microchemical plant through extensive heat recuperation and energy cascading, which has a small size and weight penalty because the added micro heat exchangers are small. This leads to additional size and weight gains by reducing the required area of waste heat radiators. The microtechnology-based ISPP plant is described in detail, including aspects of pinch analysis for optimizing the heat exchanger network. Three options for thermochemical compression Of CO2 from the Martian atmosphere, adsorption, absorption, and cryogenic freezing, are presented, as well as three options for water decomposition, low temperature electrolysis, high temperature electrolysis, and thermochemical decomposition. Other elements of the plant include Sabatier and reverse water gas shift reactors, water recovery, chemical separations, and cryogenic storage. Data are presented supporting preliminary sizing of components, and results of the system design are compared to the existing NASA baseline that is based on conventional technologies.

TeGrotenhuis, W. E.↗

Factors influencing pregnancy, litter size, and reproductive parameters of invasive wild pigs

Abstract Reproduction is the most energetically expensive life stage with the demands of productivity representing a balance between physiological requirements and environmental conditions. Wild pigs ( Sus scrofa ) throughout most of North America are genetic hybrids of feral domestic pigs and wild boar and have the highest reproductive potential of any wild ungulate. The phenology of reproduction, extent of multiple reproductive events per year, how individual and extrinsic factors contribute to variability in productivity, and impact of genetic lineage on these parameters is not well understood in wild pigs. We quantified reproductive parameters in wild pigs relative to a suite of individual and environmental attributes across seasons and multiple years in South Carolina, USA, from March 2017 and May 2020. We hypothesized that individual attributes (mass, age class, number of teats, rump fat, relative genetic association to wild boar vs. domestic pigs) and extrinsic factors (mast availability) would influence probability of pregnancy and fetal litter size. Wild pigs produced offspring throughout all months with peaks in conception corresponding to a seasonal pulse in food availability. The likelihood of pregnancy was influenced by female mass and nutritional condition and was greatest during years with abundant resources. Similarly, litter size increased with female mass and age, implying larger and older females represent the most important group for population recruitment. In evaluating the relationship between reproductive output and ancestral associations to domestic pigs versus wild boar, the proportion of wild boar ancestry was not an important influence on productivity in our population. We determined juveniles reach a physiological threshold of sexual maturity at approximately 30 kg. Average litter size was comparable to other populations, and wild pigs maintain an average fetal litter size of 5.43 offspring despite 13.6% embryonic mortality. A thorough understanding of biotic and extrinsic factors influencing reproduction are important for realistic population models, which are necessary for identifying areas to focus management needs and implementation.

59 BASIC BIOLOGICAL SCIENCES↗

Addressing the dynamic nature of reference data: a new nucleotide database for robust metagenomic classification

Accurate metagenomic classification relies on comprehensive, up-to-date, and validated reference databases. While the NCBI BLAST Nucleotide (nt) database, encompassing a vast collection of sequences from all domains of life, represents an invaluable resource, its massive size—currently exceeding 10 12 nucleotides—and exponential growth pose significant challenges for researchers seeking to maintain current nt-based indices for metagenomic classification. Recognizing that no current nt-based indices exist for the widely used Centrifuge classifier, and the last public version currently available was released in 2018, we addressed this critical gap by leveraging advanced high-performance computing resources. We present new Centrifuge-compatible nt databases, meticulously constructed using a novel pipeline incorporating different quality control measures, including reference decontamination and filtering. These measures demonstrably reduce spurious classifications, as shown through our reanalysis of published metagenomic data where Plasmodium annotations were dramatically reduced using our decontaminated database, highlighting how database quality can significantly impact research conclusions. Through temporal comparisons, we also reveal how our approach minimizes inconsistencies in taxonomic assignments stemming from asynchronous updates between public sequence and taxonomy databases. These discrepancies are particularly evident in taxa such as Listeria monocytogenes and Naegleria fowleri, where classification accuracy varied significantly across database versions. These new databases, made available as pre-built Centrifuge indexes, respond to the need for an open, robust, nt-based pipeline for taxonomic classification in metagenomics. Applications such as environmental metagenomics, forensics, and clinical metagenomics, which require comprehensive taxonomic coverage, will benefit from this resource. Our work highlights the importance of treating reference databases as dynamic entities, subject to ongoing quality control and validation akin to software development best practices. This approach is crucial for ensuring accuracy and reliability of metagenomic analysis, especially as databases continue to expand in size and complexity.

59 BASIC BIOLOGICAL SCIENCES↗

Advancing quantum simulations of the nuclear shell model with Gray-code–based resource-efficient protocols

Background: Some of the computational limitations in solving the nuclear many-body problem could be overcome by utilizing quantum computers. The nuclear shell-model calculations providing deeper insights into the properties of atomic nuclei are one such case with high demand for resources, as the size of the Hilbert space grows exponentially with the number of particles involved. Quantum algorithms are being developed to overcome these challenges and advance such calculations. Purpose: To develop quantum circuits for the nuclear shell-model, leveraging the capabilities of noisy intermediate-scale quantum (NISQ) devices. Here, we aim to minimize resource requirements (specifically in terms of qubits and gates) and strive to reduce the impact of noise by employing relevant mitigation techniques. Methods: We achieve noise resilience by designing an optimized Ansatz for the variational quantum eigensolver (VQE) based on Givens rotations and incorporating qubit-ADAPT-VQE in combination with variational quantum deflation (VQD) to compute ground and excited states, incorporating the zero-noise extrapolation mitigation technique. Furthermore, the qubit requirements are significantly reduced by mapping the basis states to qubits using Gray-code encoding and generalizing transformations of fermionic operators to efficiently represent many-body states. Results: By employing the resource-efficient protocols, we achieve the ground and excited state energy levels of 38 Ar and 6 Li with better accuracy. These energy levels are presented for noiseless simulations, noisy conditions, and after applying noise mitigation techniques. Results are compared for Jordan-Wigner and Gray-code encoding using VQE, qubit-ADAPT-VQE, and VQD. Conclusions: Our work highlights the potential of resource-efficient protocols to leverage the full potential of NISQ devices in scaling the nuclear shell model calculations, offering a pathway toward more complex quantum simulations in nuclear physics. This approach establishes a framework for studying other nuclear systems with improved quantum resource efficiency, marking a significant advancement in applying quantum computing to realistic nuclear physics applications.

Physics - Nuclear physics and radiation physics↗

Content and Representation of Information Needed to Support Time-Constrained Problem Solving

NASA’s current mission-operations paradigm originated with Project Mercury and endured with minimum evolution through the Apollo Program, Space Shuttle Program, and ISS missions. At its foundation is a near-complete real-time dependence on a ground team to manage the combined state of the mission, vehicle, and crew. Utilizing many engineers and operators with broad and deep expertise; large, distributed datasets including extensive telemetry; and expansive analytical and computing power, this ground team has served as the safety net for crewed spaceflight missions over the past 60 years. This approach must change to address challenges associated with missions beyond low Earth orbit (BLEO), including infrequent resupply, reduced ability to evacuate, and delayed communications that prohibit real-time operational support. We anticipate that a necessary part of this change will be increased independence for the crew, as roles and responsibilities traditionally performed by ground teams move on board the vehicle. While many risks are associated with Earth-independent operations, one particular concern is ensuring that the crew will have adequate onboard support to perform urgent problem solving when communication with the ground is delayed or intermittent. A key resource that enables the ground team to respond to anomalies quickly and effectively is the extraordinary expertise and experience it possesses. It is comprised of 80+ experts on at any given time, with a combined 600+ years of system-specific experience across 22 unique console disciplines. A small crew will face the unprecedented challenge of independently responding to anomalies that have historically been handled by a team 20 times their size. Another important resource upon which the ground heavily relies to support procedure execution and anomaly response is data. The amount of telemetry data that each flight controller monitors is extensive. In addition, as the ground team works to further assess impacts, trouble shoot, identify workarounds, and oversee procedure execution, it accesses and synthesizes engineering and procedure information, as well as system build, test, and configuration documentation. It is not feasible nor useful to put all these data onboard as crews become more Earth independent. Each member of a small Mars mission small crew will have multiple roles beyond monitoring telemetry and data gathering, and multiple roles within anomaly resolution processes, thereby limiting their capacity for copious amounts of information. Moreover, while access is necessary, it alone is insufficient. Information will need to be compiled, refined, and represented appropriately to support the crew’s reduced attention and expertise. This work seeks to understand the content and representation of information needed to support time-constrained problem solving and decision making by the crew without real-time ground support. To build this understanding, we first surveyed the literature, focusing on how expert problem solvers construct and manipulate their mental models. Next, we interviewed expert problem solvers in spaceflight and analogous domains and surveyed industry solutions for data presentation. Finally, we analyzed current spaceflight operations by investigating flight controller anomaly resolution processes during ISS training simulations and real operational events. These methods led to creating a problem-solving framework that details common themes and features of attending to, assessing, analyzing, and acting on problems in complex, time-constrained domains. Using this framework and the results of our analysis, we identified conceptual data representations needed for crew-led problem-solving. Preliminary onboard user interface concepts to meet identified needs will be presented.

anomaly response↗

ChatPORT: Fine-Tuned LLM for Easy Code {PORT}ing

Fine-tuning existing LLMs for specialized tasks has become a very attractive alternative due to its low cost and quick development cycle. With many pre-trained LLMs available, it is an increasingly complex task to choose the correct model as the starting point or base model. In this work we discuss ChatPORT - a specialized fine-tuned LLM geared towards providing correctly translated codes from one programming model to another. We evaluate a number of base models and compare and contrast their features and characteristics that make them a viable starting point. In this paper, we focus on the OpenMP offload porting capabilities of ChatPORT. We build our training data using kernels from the Heterogeneous Computing Benchmarks (HeCBench) [12] and the OpenMP Validation and Verification suite [5] to fine-tune the base models. We then test the model using unseen kernels extracted from the HeCBench benchmark suite. Our results show that: (1) not all open LLMs geared towards HPC are aware of programming models like OpenMP, (2) although all base models benefit from fine-tuning they learn differently and produce different correctness rates, (3) depending on the memory size and compute resource available, different base models can be used for fine-tuning without significantly affecting the quality of transpiled code they generate, (4) fine-tuning improved the correctness rate of the LLM by an average of 43.2%, and (5) feedback-based training data further increased the correctness rate by an average of 6% over the LLMs tested.

Pophale, Swaroop [ORNL] (ORCID:0000000185446367)↗

Probing Accuracy-Speedup Tradeoff in Machine Learning Surrogates for Molecular Dynamics Simulations

The performance promise of machine learning surrogates of molecular dynamics simulations of soft materials is significant but generally comes at the cost of acquiring large training datasets to learn the complex relationships between input soft material attributes and output properties. Under the constraint of limited high-performance computing resources, optimizing the size of the training datasets becomes paramount. Using an artificial neural network based surrogate for molecular dynamics simulations of confined electrolytes, we explore the tradeoff between surrogate accuracy and computational gains. Accuracy is assessed by computing the root-mean-square errors between the surrogate predictions and the ground truth results obtained via molecular dynamics simulations. The computational performance is judged by evaluating the speedup which incorporates the training dataset creation time. Improvement in accuracy occurs with a loss of speedup, which scales as the inverse of the training dataset size. Furthermore, the link between surrogate generalizability and the accuracy-speedup tradeoff is assessed by examining the errors incurred in surrogate predictions on unseen, interpolated input variables and developing a net speedup metric to capture the associated gains.

Anions↗

First principles calculations in support of Pu aging: calculating the effects of lattice imperfections on thermodynamics

Plutonium (Pu) has, in theory, well defined crystal structures: its atoms are arranged in regular spatial patterns. But Pu is radioactive, and as its nuclei decay those regular spatial patterns are interrupted. The interruptions are lattice imperfections, which are known to affect how materials respond to their environment. To adequately model Pu, we need to know which lattice imperfections are present, how they interact with each other, and how they affect the material’s response to its environment. The work presented here aims to use density functional theory (DFT) calculations to begin to answer the latter, in particular, how individual lattice imperfections affect measurable effects including thermal expansion (the change in volume in response to a change in temperature), heat capacity (the amount of thermal energy needed to change a material’s temperature), and elastic moduli (a material’s resistance to applied stresses). Pu poses many computational challenges. The $\textit{f}$ electrons require special attention. Of all the elements, Pu has the largest number of electrons that must be included in the calculations. Thermal effects require calculating the phonons (the lattice vibrations), which for systems containing lattice imperfections demand large, complex computational cells - but computational resources limit the size and complexity. With careful restructuring of how the calculations are performed, all these challenges have been met to enable calculations that provide insight into how lattice imperfections affect Pu’s response to its environment. Reported here are the computational challenges and the advances developed to meet them, along with the first results showing the strong effect that one prototype lattice imperfection (an interstitial Pu atom in a delta-phase Pu lattice) has on Pu’s response to its environment.

36 MATERIALS SCIENCE↗

Adaptive variational simulation for open quantum systems

Emerging quantum hardware provides new possibilities for quantum simulation. While much of the research has focused on simulating closed quantum systems, the real-world quantum systems are mostly open. Therefore, it is essential to develop quantum algorithms that can effectively simulate open quantum systems. Here we present an adaptive variational quantum algorithm for simulating open quantum system dynamics described by the Lindblad equation. The algorithm is designed to build resource-efficient ansatze through the dynamical addition of operators by maintaining the simulation accuracy. We validate the effectiveness of our algorithm on both noiseless simulators and IBM quantum processors and observe good quantitative and qualitative agreement with the exact solution. We also investigate the scaling of the required resources with system size and accuracy and find polynomial behavior. Our results demonstrate that near-future quantum processors are capable of simulating open quantum systems.

97 MATHEMATICS AND COMPUTING↗