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At least 1,333 records · Page 74

PaRSEC: Scalability, flexibility, and hybrid architecture support for task-based applications in ECP

This paper highlights the most significant enhancements made to PaRSEC, a scalable task-based runtime system designed for hybrid machines, during the Exascale Computing Project (ECP). The enhancements focus on expanding the capabilities of PaRSEC to address the evolving landscape of parallel computing. Notable achievements include the integration of support for three major types of accelerators (NVIDIA, AMD, and Intel GPUs), the refinement and increased flexibility of the communication subsystem, and the introduction of new programming interfaces tailored for irregular applications. Additionally, the project resulted in the development of powerful debugging and performance analysis tools aimed at assisting users in understanding and optimizing their applications. We present a comprehensive demonstration of these advancements through a series of benchmarks and applications within ECP and beyond, thereby showcasing the enhanced capabilities of PaRSEC across the diverse architectures within the ECP, providing valuable insights into the runtime system’s adaptability and performance across varied computing environments.

Bouteiller, Aurelien↗

Structural and Acoustic Numerical Modeling of a Curved Composite Honeycomb Panel

The finite and boundary element modeling of the curved section of a composite honeycomb aircraft fuselage sidewall was validated for both structural response and acoustic radiation. The curved panel was modeled in the pre-processor MSC/PATRAN. Geometry models of the curved panel were constructed based on the physical dimensions of the test article. Material properties were obtained from the panel manufacturer. Finite element models were developed to predict the modal parameters for free and supported panel boundary conditions up to a frequency of 600 Hz. Free boundary conditions were simulated by providing soft foam support under the four comers of the panel or by suspending the panel from elastic bands. Supported boundary conditions were obtained by clamping the panel between plastic tubing seated in grooves along the perimeter of a stiff and heavy frame. The frame was installed in the transmission loss window of the Structural Acoustic Loads and Transmission (SALT) facility at NASA Langley Research Center. The structural response of the curved panel due to point force excitation was predicted using MSC/NASTRAN and the radiated sound was computed with COMET/Acoustics. The predictions were compared with the results from experimental modal surveys and forced response tests on the fuselage panel. The finite element models were refined and updated to provide optimum comparison with the measured modal data. Excellent agreement was obtained between the numerical and experimental modal data for the free as well as for the supported boundary conditions. Frequency response functions (FRF) were computed relating the input force excitation at one panel location to the surface acceleration response at five panel locations. Frequency response functions were measured at the same locations on the test specimen and were compared with the calculated FRF values. Good agreement was obtained for the real and imaginary parts of the transfer functions when modal participation was allowed up to 3000 Hz. The validated finite element model was used to predict the surface velocities due to the point force excitation. Good agreement was obtained between the spatial characteristics of the predicted and measured surface velocities. The measured velocity data were input into the acoustic boundary element code to compute the sound radiated by the panel. The predicted sound pressure levels in the far-field of the panel agreed well with the sound pressure levels measured at the same location.

Grosveld, Ferdinand W.↗

Comparing Cumulative Flight Thermal Fatigue to Ground Test Results for Memory Components on the Mars Curiosity Rover

This paper explores the methods used to examine Mars Curiosity Rover’s flight temperature data to the Package Qualification and Verification (PQV) accelerated thermal cycle life test data in response to flight anomalies. The redundant Rover Compute Element (RCE-A, B) has experienced an inability to mount the flash memory several times. The leading cause of these anomalies is likely the loss of electrical connectivity, which is theorized to be due to cracks on the memory component solder joints by thermal cycle fatigue. To investigate this theory, the number of thermal cycles accumulated in flight was compared to PQV accelerated thermal cycle life test data. The goal of this study was to inform mission operations of the risk associated with thermal cycling damage on the RCE. However, since the RCE-B does not have continuous temperature data from the Platinum Resistance Thermometer (PRT) closest to the flash memory, a model was made to correlate continuous data from two other nearby sensors on the RCE-B to the noncontiguous sensor. Using the Rainflow Counting Algorithm, the reconstituted data was converted into the number of equivalent thermal cycles. The Coffin-Manson Equation was used to compare flight thermal cycles to the PQV test. The accelerated life test showed cracking on the memory component solder joints after 500 cycles of 80°C temperature excursions. This study found that the RCE-A and RCE-B have undergone an equivalent of 144 and 430 cycles of 80°C temperature excursions during flight, respectively.

Berger, Lindsey N↗

Comparing Cumulative Flight Thermal Fatigue to Ground Test Results for Memory Components on the Mars Curiosity Rover

This paper explores the methods used to examine Mars Curiosity Rover’s flight temperature data in relation to the Package Qualification and Verification (PQV) accelerated thermal cycle life test data in response to flight anomalies. The redundant Rover Compute Element (RCE-A, B) has experienced an inability to mount the flash memory several times. The leading cause of these anomalies is likely the loss of electrical connectivity, which is theorized to be due to cracks on the memory component solder joints by thermal cycle fatigue. To investigate this theory, the number of thermal cycles accumulated in flight was compared to PQV accelerated thermal cycle life test data. The goal of this study was to inform mission operations of the risk associated with thermal cycling damage on the RCE. However, since the RCE-B does not have continuous temperature data from the Platinum Resistance Thermometer (PRT) closest to the flash memory, a model was made to correlate continuous data from two other nearby sensors on the RCE-B to the noncontiguous sensor. Using the Rainflow Counting Algorithm, the reconstituted data was converted into the number of equivalent thermal cycles. The Coffin-Manson Equation was used to compare flight thermal cycles to the PQV test. The accelerated life test showed cracking on the memory component solder joints after 500 cycles of 80°C temperature excursions. This study found that the RCE-A and RCE-B have undergone an equivalent of 144 and 430 cycles of 80°C temperature excursions during flight, respectively.

Bell, Charles↗

Quantum Computing for Neutrino-Nucleus Scattering

Neutrino-nucleus cross section uncertainties are expected to be a dominant systematic in future accelerator neutrino experiments. The cross sections are determined by the linear response of the nucleus to the weak interactions of the neutrino, and are dominated by energy and distance scales of the order of the separation between nucleons in the nucleus. These response functions are potentially an important early physics application of quantum computers. Here we present an analysis of the resources required and their expected scaling for scattering cross section calculations. The current estimates of Trotter steps needed to achieve an energy resolution of 10 MeV and the number of CNOT gates for analyzing Ar40 highlights the need for significant improvements in algorithms. We also examine simple small-scale neutrino-nucleus models on modern quantum hardware. In this paper, we use variational methods to obtain the ground state of a three nucleon system (the triton) and then implement the relevant time evolution. To tame the errors in present-day NISQ devices, we explore the use of different error-mitigation techniques to increase the fidelity of the calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Free-floating experiments in orbiter and space station

Manned spacecraft will never be free of acceleration perturbations due to necessary motions of crewmembers. However, in most cases, the perturbations can be minimized or even isolated from sensitive experiments when required. The principal disturbances and methods of isolation are described. As the crew moves about the spacecraft, no external forces are applied and the average acceleration remains near zero. External force will be exerted when jets are fired for spacecraft attitude control or translation, and these must be transferred to the microgravity experiments. Transitory acceleration and vibration are produced by crew and equipment. The most significant on Orbiter have been wall push-offs used for body translation within the spacecraft, the exercise conducted on a treadmill within the middeck area, closing doors of stowage compartments and the vibration of some machinery, such as a sample centrifuge. For short periods of perhaps a few minutes, crew and equipment motion can be largely inhibited, but not for much longer intervals. It may be necessary to mount especially sensitive experiments on an isolation table, which can greatly reduce the acceleration transferred to the experiment. Either weak mechanical springs or, even better, a computer-controlled electromagnetic suspension can be used to effectively insulate the table from vibration at frequencies above about 0.01 Hz. Another option is to free-float an experiment table within the spacecraft. All of the above-mentioned perturbations can be eliminated for some minutes if the entire experiment package is allowed to free-float within the spacecraft until a wall contact is made. Package acceleration levels should be maintainable below 10(exp -8) g sub o in this way.

Garriott, Owen K.↗

Accelerating Lossy and Lossless Compression on Emerging BlueField DPU Architectures

Data compression has become a crucial technique in addressing performance bottlenecks caused by increasing data volumes in High-Performance Computing (HPC), Big Data, and Deep Learning (DL). Despite its potential to boost system performance, recent studies have identified significant challenges with existing compression methods, mainly due to their high computational demands amidst continuously growing data sizes. Concurrently, the advent of Data Processing Units (DPUs), equipped with programmable System-on-Chip (SoC) and specialized compression accelerators, offers a promising opportunity to alter the landscape of data compression. This paper explores the complexities and potential of leveraging NVIDIA BlueField DPUs to accelerate lossy and lossless compression. Towards this, we introduce PEDAL, an innovative library that leverages the hardware capabilities of DPUs to unify and optimize data compression designs. Moreover, we seamlessly co-design PEDAL with the popular MPICH MPI library, demonstrating up to 101x speedup in compression time and 88x decrease in communication latency. Drawing on these achievements, we share our experience with various research communities about accelerating data compression on DPUs in communication-oriented HPC scenarios.

Li, Yuke↗

On the Efficient Evaluation of the Exchange Correlation Potential on Graphics Processing Unit Clusters

The predominance of Kohn–Sham density functional theory (KS-DFT) for the theoretical treatment of large experimentally relevant systems in molecular chemistry and materials science relies primarily on the existence of efficient software implementations which are capable of leveraging the latest advances in modern high-performance computing (HPC). With recent trends in HPC leading toward increasing reliance on heterogeneous accelerator-based architectures such as graphics processing units (GPU), existing code bases must embrace these architectural advances to maintain the high levels of performance that have come to be expected for these methods. In this work, we purpose a three-level parallelism scheme for the distributed numerical integration of the exchange-correlation (XC) potential in the Gaussian basis set discretization of the Kohn–Sham equations on large computing clusters consisting of multiple GPUs per compute node. In addition, we purpose and demonstrate the efficacy of the use of batched kernels, including batched level-3 BLAS operations, in achieving high levels of performance on the GPU. We demonstrate the performance and scalability of the implementation of the purposed method in the NWChemEx software package by comparing to the existing scalable CPU XC integration in NWChem.

97 MATHEMATICS AND COMPUTING↗

Modern Monte Carlo methods for efficient uncertainty quantification and propagation: A survey

Uncertainty quantification (UQ) includes the characterization, integration, and propagation of uncertainties that result from stochastic variations and a lack of knowledge or data in the natural world. Monte Carlo (MC) method is a sampling-based approach that has widely used for quantification and propagation of uncertainties. However, the standard MC method is often time-consuming if the simulation-based model is computationally intensive. This article gives an overview of modern MC methods to address the existing challenges of the standard MC in the context of UQ. Specifically, multilevel Monte Carlo (MLMC) extending the concept of control variates achieves a significant reduction of the computational cost by performing most evaluations with low accuracy and corresponding low cost, and relatively few evaluations at high accuracy and corresponding high cost. Multifidelity Monte Carlo (MFMC) accelerates the convergence of standard Monte Carlo by generalizing the control variates with different models having varying fidelities and varying computational costs. Multimodel Monte Carlo method (MMMC), having a different setting of MLMC and MFMC, aims to address the issue of UQ and propagation when data for characterizing probability distributions are limited. Multimodel inference combined with importance sampling is proposed for quantifying and efficiently propagating the uncertainties resulting from small data sets. All of these three modern MC methods achieve a significant improvement of computational efficiency for probabilistic UQ, particularly uncertainty propagation. Finally, an algorithm summary and the corresponding code implementation are provided for each of the modern MC methods. The extension and application of these methods are discussed in detail.

97 MATHEMATICS AND COMPUTING↗

Bringing OpenCL to Commodity RISC-V CPUs

The importance of open-source hardware has been increasing in recent years with the introduction of the RISC-V Open ISA. This has also accelerated the push for support of the open-source software stack from compiler tools to full-blown operating systems. Parallel computing with today’s Application Programming Interfaces such as OpenCL has proven to be effective at leveraging the parallelism in commodity multi-core processors and programmable parallel accelerators. However, to the best of our knowledge, there is currently no publicly available implementation of OpenCL targeting commodity RISC-V processors that is accessible to the open-source community. Besides opening RISC-V to the existing rich variety of scientific parallel applications, OpenCL also provides access to a unique genre of benchmarks useful in computer architecture research. In this work, we extended an Open-source implementation of OpenCL to target RISC-V CPUs. Our work not only cover commodity multi-core RISC-V processors, but also plethora of low- profile embedded RISC-V CPUs that often do not support atomic instructions or multi-threading.

Tine, Blaise↗

Characterization of ion accelerating systems on NASA LeRC's ion thrusters

An investigation is conducted regarding ion-accelerating systems for two NASA thrusters to study the limits of ion-extraction capability or perveance. A total of nine two-grid ion-accelerating systems are tested with the 30- and 50-cm-diam ring-cusp inert-gas ion thrusters emphasizing the extension of ion-extraction. The vacuum-tank testing is described using xenon, krypton, and argon propellants, and thruster performance is computed with attention given to theoretical design considerations. Reductions in perveance are noted with decreasing accelerator-hole-to-screen-hole diameter ratios. Perveance values vary indirectly with the ratio of discharge voltage to total accelerating voltage, and screen/accelerator electrode hole-pair alignment is also found to contribute to perveance values.

Rawlin, Vincent K.↗

Non-thermal processes in large solar flares

The paper examines the significance of particle acceleration processes in large solar flares, and the importance of accelerated particles in the generation of other flare phenomena. Comprehensive observations of the August 1972 series of large flares were used to obtain quantitative estimates of the energetic particle populations, the electromagnetic emissions, and the mass ejections. The fluxes of energetic electrons and protons were derived from observed X-ray and gamma-ray emissions, respectively. The energy input into the solar atmosphere from the collisional losses of these energetic particles is computed as a function of overlying column density, under the assumption that particles are accelerated at a point high in the solar atmosphere and then precipitate down to denser layers. The flash phase radiation, soft X-ray flare plasma, and the interplanetary shock wave can be consistently and quantitatively explained as a result of the interaction of nonrelativistic electrons with the solar atmosphere.

Lin, R. P.↗

Linear stability analysis via simulated annealing and accelerated relaxation

Simulated annealing (SA) is a kind of relaxation method for finding equilibria of Hamiltonian systems. A set of evolution equations is solved with SA, which is derived from the original Hamiltonian system so that the energy of the system changes monotonically while preserving Casimir invariants inherent to noncanonical Hamiltonian systems. The energy extremum reached by SA is an equilibrium. Since SA searches for an energy extremum, it can also be used for stability analysis when initiated from a state where a perturbation is added to an equilibrium. The procedure of the stability analysis is explained, and some examples are shown. Because the time evolution is computationally time consuming, efficient relaxation is necessary for SA to be practically useful. An acceleration method is developed by introducing time dependence in the symmetric kernel used in the double bracket, which is part of the SA formulation described here. An explicit formulation for low-beta reduced magnetohydrodynamics (MHD) in cylindrical geometry is presented. In conclusion, since SA for low-beta reduced MHD has two advection fields that relax, it is important to balance the orders of magnitude of these advection fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Development of a colinear Second-Harmonic Orthogonal Polarization (SHOP) interferometer for electron areal density measurements in Magnetically Insulated Transmission Lines (MITLs)

Experimental measurements of low density plasmas forming in Magnetically Insulated Transmission Line (MITL) regions are desired to improve our understanding of current loss and power flow. Therefore, a new optical interferometer diagnostic was commissioned via this LDRD project. To measure the expected 10 13 - 10 17 cm -3 electron densities inside the 0.5 - 6 mm Anode-Cathode (A-K) gaps, a colinear SHOP interferometer diagnostic was constructed. The diagnostic was initially fielded on the University of New Mexico (UNM) Helicon-Cathode (HelCat) plasma device which provided a highly repeatable and well understood plasma source for which the colinear SHOP interferometer’s functionality could be verified and measured. Utilizing the highly repeatable plasma source and shot averaging, the interferometer was able to achieve an areal density sensitivity of 1×10 14 cm -2 . This work at UNM lead to a Review of Scientific Instruments (RSI) publication [20], DOI:10.1063/5.0101687. After the diagnostic’s capability was proven at UNM, the colinear SHOP interferometer was commissioned for use on the Sandia National Laboratories (SNL) Mykonos accelerator. Here, it provided the first temporal areal density measurements of plasma formation in a parallel plate MITL. The diagnostic was able to achieve a single shot (no multi-shot averaging like at UNM) areal density sensitivity of 1×10 15 cm -2 along a ~ 2mm probing path length, which provided adequate capability to conduct fundamental physics research of MITL plasma formation. CHICAGO and ALEGRA simulations support the diagnostics experimental findings. More experimental and computational work will continue, likely leading to another publication(s). The smaller scale Mykonos accelerator work has also provided justification that the colinear SHOP interferometer is a capable diagnostic for measuring plasma areal densities in the inner MITL and convolute regions of larger TW-class accelerators like SNL’s Z machine.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Advanced Research Directions on AI for Science, Energy, and Security: Report on Summer 2022 Workshops

Over the past decade, fundamental changes in artificial intelligence (AI)—from foundational to applied—have delivered dramatic insights across a wide breadth of U.S. Department of Energy (DOE) mission space. AI is helping to augment and improve scientific and engineering workflows (e.g., for control, design, and dramatic performance gains through surrogate models) in national security, the Office of Science, and DOE’s applied energy programs. The progress and potential for AI in DOE science was captured in the 2020 “AI for Science” report from the DOE laboratory community in collaboration with academia and industry. Specific scientific areas ready to further leverage the power of AI ranged from the scale and performance of computational models to data analysis to creating new classes of observations using computer vision. Since that report, the scale and scope of scientific AI have accelerated, revealing new, emergent properties that yield insights that go beyond enabling opportunities to being potentially transformative in the way that scientific problems are posed and solved. Thus, under the guidance of both the Office of Science (SC) and the National Nuclear Security Administration (NNSA), the DOE national laboratories organized a series of workshops in 2022 to gather input on new and rapidly emerging opportunities and challenges of scientific AI. This 2023 report is a synthesis of those workshops. The scientific community believes AI can have a foundational impact on a broad range of DOE missions, including science, energy, and national security. Further, DOE has unique capabilities that enable the community to drive progress in scientific use of AI, building on long-standing DOE strengths and investments in computation, data, and communications infrastructure, spanning the Energy Sciences Network (ESnet), the Exascale Computing Project (ECP), and integrative programs such as the NNSA Office of Defense Programs Advanced Simulation and Computing (ASC) and the SC Scientific Discovery through Advanced Computing (SciDAC) programs.

97 MATHEMATICS AND COMPUTING↗

Portability: A Necessary Approach for Future Scientific Software

Today's world of scientific software for High Energy Physics (HEP) is powered by x86 code, while the future will be much more reliant on accelerators like GPUs and FPGAs. The portable parallelization strategies (PPS) project of the High Energy Physics Center for Computational Excellence (HEP/CCE) is investigating solutions for portability techniques that will allow the coding of an algorithm once, and the ability to execute it on a variety of hardware products from many vendors, especially including accelerators. We think without these solutions, the scientific success of our experiments and endeavors is in danger, as software development could be expert driven and costly to be able to run on available hardware infrastructure. We think the best solution for the community would be an extension to the C++ standard with a very low entry bar for users, supporting all hardware forms and vendors. We are very far from that ideal though. We argue that in the future, as a community, we need to request and work on portability solutions and strive to reach this ideal.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Accelerating Hydraulic Fracture Imaging by Deep Transfer Learning

Deep transfer learning has a great success story in computer vision (CV), natural language processing, and many other fields. In this communication, we are going to push forward the deep transfer learning to the hydraulic fracture imaging problem by proposing a two-step approach: 1) train a convolutional neural network (CNN) to reconstruct target geometries by a relatively large amount of approximated field patterns generated from a simplified model and 2) fine-tune the top layers of transferred CNN by a small amount of true field patterns generated through a full model. The advantages include the rapid generation of large amount of data through the simplified model and the high reconstruction accuracy through a careful design of the deep transfer learning. Here, the CNN trained through the deep transfer learning can accurately reconstruct the lateral extent and direction of fractures with unseen conductivity and white Gaussian noise, showing a notable acceleration/accuracy enhancement over the previous CNN trained by mixing a small number of true data into the approximated data as data augmentation.

02 PETROLEUM↗

Object Proxy Patterns for Accelerating Distributed Applications

Workflow and serverless frameworks have empowered new approaches to distributed application design by abstracting compute resources. However, their typically limited or one-size-fits-all support for advanced data flow patterns leaves optimization to the application programmer—optimization that becomes more difficult as data become larger. The transparent object proxy, which provides wide-area references that can resolve to data regardless of location, has been demonstrated as an effective low-level building block in such situations. Here we propose three high-level proxy-based programming patterns—distributed futures, streaming, and ownership—that make the power of the proxy pattern usable for more complex and dynamic distributed program structures. We motivate these patterns via careful review of application requirements and describe implementations of each pattern. As a result, we evaluate our implementations through a suite of benchmarks and by applying them in three meaningful scientific applications, in which we demonstrate substantial improvements in runtime, throughput, and memory usage.

Distributed Computing↗