Search NASA⌕ Search

SEARCH · Search NASA

Results for “Parallelization Strategy”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Dynamic Modeling, Trajectory Optimization, and Linear Control of Cable-Driven Parallel Robots for Automated Panelized Building Retrofits

The construction industry faces a growing need for automation to reduce costs, improve accuracy and productivity, and address labor shortages. One area that stands to benefit significantly from automation is panelized prefabricated building envelope retrofits, which can improve a building’s energy efficiency in heating and cooling interior spaces. In this paper, we propose using cable-driven parallel robots (CDPRs), which can effectively lift and handle large objects, to install these panels. However, implementing CDPRs presents significant challenges because of their nonlinear dynamics, complex trajectory planning, and precise control requirements. To tackle these challenges, this work focuses on a new application of established control and trajectory optimization theories in a CDPR simulation of a building envelope retrofit under real-world conditions. We first model the dynamics of CDPRs, highlighting the critical role of damping in system behavior. Building on this dynamic model, we formulate a trajectory optimization problem to generate feasible and efficient motion plans for the robot under operational and environmental constraints. Given the high precision required in the construction industry, accurately tracking the optimized trajectory is essential. However, challenges such as partial observability and external vibrations complicate this task. To address these issues, a Linear Quadratic Gaussian control framework is applied, enabling the robot to track the optimized trajectories with precision. Simulation results show that the proposed controller enables precise end effector positioning with errors under 4 mm, even in the presence of external wind disturbances. Through comprehensive simulations, our approach allows for an in-depth exploration of the system’s nonlinear dynamics, trajectory optimization, and control strategies under controlled yet highly realistic conditions. The results demonstrate the feasibility of CDPRs for automating panel installation and provide insights into their practical deployment.

CDPR↗
DOE OSTI2011

β1 integrin mediates an alternative survival pathway in breast cancer cells resistant to lapatinib

The overexpression of human epidermal growth factor receptor (HER)-2 in 20% of human breast cancers and its association with aggressive growth has led to widespread use of HER2-targeted therapies, such as trastuzumab (T) and lapatinib (L). Despite the success of these drugs, their efficacy is limited in patients whose tumors demonstrate de novo or acquired resistance to treatment. The b1 integrin resides on the membrane of the breast cancer cell, activating several elements of breast tumor progression including proliferation and survival. We developed a panel of HER2-overexpressing cell lines resistant to L, T, and the potent LT combination through long-term exposure and validated these models in 3D culture. Parental and L/T/LT-resistant cells were subject to HER2 and b1 integrin inhibitors in 3D and monitored for 12 days, followed by quantification of colony number. Parallel experiments were conducted where cells were either stained for Ki-67 and Terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) or harvested for protein and analyzed by immunoblot. Results were subjected to statistical testing using analysis of variance and linear contrasts, followed by adjustment with the Sidak method. Using multiple cell lines including BT474 and HCC1954, we reveal that in L and LT resistance, where phosphorylation of EGFR/HER1, HER2, and HER3 are strongly inhibited, kinases downstream of b1 integrin– including focal adhesion kinase (FAK) and Src–are up-regulated. Blockade of b1 by the antibody AIIB2 abrogates this up-regulation and functionally achieves significant growth inhibition of L and LT resistant cells in 3D, without dramatically affecting the parental cells. SiRNA against b1 as well as pharmacologic inhibition of FAK achieve the same growth inhibitory effect. In contrast, trastuzumab-resistant cells, which retain high levels of phosphorylated EGFR/HER1, HER2, and HER3, are only modestly growth-inhibited by AIIB2. Our data suggest that HER2 activity, which is suppressed in resistance involving L but not T alone, dictates whether b1 mediates an alternative pathway driving resistance. Our findings justify clinical studies investigating the inhibition of b1 or its downstream signaling moieties as strategies to overcome acquired L and LT resistance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Direct health-care cost of head and neck cancers: a population-based study in north-eastern Italy

Improvements in prognosis of head-and-neck squamous cell carcinoma (HNSCC) have paralleled with an increase in health-care costs, so that an economic evaluation is of growing importance. Presently, most of the evidence is from insurance-based studies in the USA. Between 2007 and 2010, 879 HNSCC patients were identified through the population-based cancer registry of the Friuli Venezia Giulia region, including 266 oral, 187 oropharyngeal, 136 hypopharyngeal, and 290 laryngeal cancers. Health-care costs from diagnosis to treatment initiation and in the following 2 years were retrieved through a record linkage with the regional health data warehouse. This database collected comprehensive health information on all resident citizens. Generalized linear models with a gamma distribution and log-link function were applied to model costs. The average health-care cost from diagnosis up to 2 years after treatment initiation was €20,184 (95% confidence interval: €19,634 − 20,733). Heterogeneity emerged according to cancer site, elective treatment, and retreatment for cancer persistence/recurrence (no: €13,896; yes: €24,599; p < 0.001). An advanced stage was associated with increased costs stage (I: €12,969; II: €18,276; III: €26,229; IV: €25,574; p < 0.001) as the result of treatment complexity and elevated frequency of patients retreatment due to recurrence. These findings further support strategies to diagnose patients at an earlier cancer stage and the accurate definition of diagnostic and treatment pathways, to start treating patients when radical unimodal approach is still feasible. Besides the advantage in prognosis due to timely curative treatments, this would reduce the economic burden of cancer treatment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Monofluorination of Naphthyls Promotes the Cofacial π–π Stacking and Increases the Electron Mobility of Non-Planar Zinc(II) Complexes of Di(naphthylethynyl)azadipyrromethene

The homoleptic zinc(II) complex of [2,8-di(1-naphthylethynyl) 3,7-diphenyl 1,9-(4-hexylphenyl)azadipyrromethene (ZnL2) 2 ] is a promising non-planar non-fullerene acceptor for organic photovoltaic applications, but it has a relatively low electron mobility that may limit its performance. Here, we explored the fluorination of peripheral aryl groups to increase intermolecular cofacial π–π stacking interactions, which are desirable for electron transport. Here complexes with fluorine on the distal phenyls [Zn(1F-L2) 2 ], on the naphthyls [Zn(2F-L2) 2 ], and on both [Zn(3F-L2) 2 ] were synthesized and characterized. All three complexes had similar optical and electrochemical properties. The crystal packing structure of Zn(2F-L2) 2 and Zn(3F-L2) 2 revealed cofacial parallel-displaced π–π stacking between the fluorinated 1-naphthylethynyl groups. Such a cofacial orientation was not observed in Zn(L2) 2 crystals, suggesting that fluorination of the naphthyl groups promotes the cofacial π–π stacking orientation. The hole mobility increased from 1.0 × 10 –4 cm 2 V –1 s –1 for Zn(L2) 2 to 0.8–1.0 × 10 –3 cm 2 V –1 s –1 for the fluorinated complexes. Fluorination on the naphthyl groups increased the electron mobility from 4.2 × 10 –5 cm 2 V –1 s –1 for Zn(L2) 2 and Zn(1F-L2) 2 to 2.0 × 10 –4 cm 2 V –1 s –1 for Zn(2F-L2) 2 and Zn(3F-L2) 2 , consistent with cofacial π–π stacking being favorable for electron transport. The three complexes were tested in OPVs using regioregular poly(3-hexylthiophene) (P3HT) as the p-type material, and the best power conversion efficiencies were 5.2, 5.4, and 5.8% for Zn(2F-L2) 2 , Zn(1F-L2) 2 , and Zn(3F-L2) 2 , respectively, compared to 5.5% for Zn(L2) 2 . The fluorination combination found in Zn(3F-L2) 2 resulted in the best device performance. This study points to a viable strategy to increase the electron mobility and performance of non-planar zinc(II) complexes of azadipyrromethene.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Multi-core and many-core shared-memory parallel raycasting volume rendering optimization and tuning

Given the computing industry trend of increasing processing capacity by adding more cores to a chip, the focus of this work is tuning the performance of a staple visualization algorithm, raycasting volume rendering, for shared-memory parallelism on multi-core CPUs and many-core GPUs. Our approach is to vary tunable algorithmic settings, along with known algorithmic optimizations and two different memory layouts, and measure performance in terms of absolute runtime and L2 memory cache misses. Our results indicate there is a wide variation in runtime performance on all platforms, as much as 254% for the tunable parameters we test on multi-core CPUs and 265% on many-core GPUs, and the optimal configurations vary across platforms, often in a non-obvious way. For example, our results indicate the optimal configurations on the GPU occur at a crossover point between those that maintain good cache utilization and those that saturate computational throughput. This result is likely to be extremely difficult to predict with an empirical performance model for this particular algorithm because it has an unstructured memory access pattern that varies locally for individual rays and globally for the selected viewpoint. Our results also show that optimal parameters on modern architectures are markedly different from those in previous studies run on older architectures. In addition, given the dramatic performance variation across platforms for both optimal algorithm settings and performance results, there is a clear benefit for production visualization and analysis codes to adopt a strategy for performance optimization through auto-tuning. These benefits will likely become more pronounced in the future as the number of cores per chip and the cost of moving data through the memory hierarchy both increase.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Creating orbiting vorticity vectors in magnetic particle suspensions through field symmetry transitions–a route to multi-axis mixing

It has recently been reported that two types of triaxial electric or magnetic fields can drive vorticity in dielectric or magnetic particle suspensions, respectively. The first type-symmetry -- breaking rational fields -- consists of three mutually orthogonal fields, two alternating and one dc, and the second type -- rational triads -- consists of three mutually orthogonal alternating fields. In each case it can be shown through experiment and theory that the fluid vorticity vector is parallel to one of the three field components. For any given set of field frequencies this axis is invariant, but the sign and magnitude of the vorticity (at constant field strength) can be controlled by the phase angles of the alternating components and, at least for some symmetry-breaking rational fields, the direction of the dc field. In short, the locus of possible vorticity vectors is a 1-d set that is symmetric about zero and is along a field direction. In this paper we show that continuous, 3-d control of the vorticity vector is possible by progressively transitioning the field symmetry by applying a dc bias along one of the principal axes. Such biased rational triads are a combination of symmetry-breaking rational fields and rational triads. A surprising aspect of these transitions is that the locus of possible vorticity vectors for any given field bias is extremely complex, encompassing all three spatial dimensions. As a result, the evolution of a vorticity vector as the dc bias is increased is complex, with large components occurring along unexpected directions. More remarkable are the elaborate vorticity vector orbits that occur when one or more of the field frequencies are detuned. As a result, these orbits provide the basis for highly effective mixing strategies wherein the vorticity axis periodically explores a range of orientations and magnitudes.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Energy-Screened Many-Body Expansion for Protein–Ligand Interactions: Examining Convergence for Metalloenzymes Through Seven–Body Interactions

Fragment-based quantum chemistry is a powerful strategy for calculating protein−ligand interaction energies using quantum chemistry methods. Rigorous convergence often requires hundreds of atoms in the protein binding-site model, especially if that model is constructed using distance-based criteria to select amino acid residues, while three- and four-body calculations exhibit instability related to combinatorial proliferation in the number of subsystem calculations. Here, we report an energy-based screening protocol for the many-body expansion applied to protein−ligand interactions, implemented in the open-source FRAGME∩T code. Using a combination of aggressive screening based on semiempirical quantum chemistry, with an improved graph-theoretical algorithm to eliminate unimportant subsystems, we are able to perform n-body calculations up to n = 7 using density functional theory in triple-ζ basis sets. Distance cutoffs further reduce the cost without compromising accuracy. Rapid and stable convergence of the many-body expansion is obtained by n = 4, for a pair of metalloenzymes in which a divalent ion coordinates directly to the ligand. As compared to previous results that relied solely on distance cutoffs, oscillations in the n-body corrections are reduced or eliminated, although residual errors remain in one case. This work demonstrates that benchmark-quality protein−ligand interaction energies can be systematically converged using a method with excellent parallel efficiency and scalability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Enabling machine learning-ready HPC ensembles with Merlin

With the growing complexity of computational and experimental facilities, many scientific researchers are turning to machine learning (ML) techniques to analyze large scale ensemble data. With complexities such as multi-component workflows, heterogeneous machine architectures, parallel file systems, and batch scheduling, care must be taken to facilitate this analysis in a high performance computing (HPC) environment. Here, we present Merlin, a workflow framework to enable large ML-friendly ensembles of scientific HPC simulations. By augmenting traditional HPC with distributed compute technologies, Merlin aims to lower the barrier for scientific subject matter experts to incorporate ML into their analysis. As a producer–consumer workflow model, Merlin enables multi-machine, cross-batch job, dynamically allocated yet persistent workflows capable of utilizing surge-compute resources. Key features of Merlin are a flexible HPC-centric interface, low per-task overhead, multi-tiered fault recovery, and a hierarchical sampling algorithm that allows for $\mathscr{O}$(N) task execution and $\mathscr{O}$(N ln N) task queuing to ensembles of millions of tasks. In addition to Merlin’s design, we test the algorithm’s performance in an HPC center and demonstrate the ability to enqueue 40 million simulations in 100 s, with a 30 millisecond per-task overhead that is independent of ensemble size. Finally, we describe some example applications that Merlin has enabled on leadership-class HPC resources, such as the ML-augmented optimization of nuclear fusion experiments and the calibration of infectious disease models to study the progression of and possible mitigation strategies for COVID-19.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

A Multi-TeV Linear Collider Based on CLIC Technology : CLIC Conceptual Design Report

This report describes the accelerator studies for a future multi-TeV e + e - collider based on the Compact Linear Collider (CLIC) technology. The CLIC concept as described in the report is based on high gradient normal-conducting accelerating structures where the RF power for the acceleration of the colliding beams is extracted from a high-current Drive Beam that runs parallel with the main linac. The focus of CLIC R&D over the last years has been on addressing a set of key feasibility issues that are essential for proving the fundamental validity of the CLIC concept. The status of these feasibility studies are described and summarized. The report also includes a technical description of the accelerator components and R&D to develop the most important parts and methods, as well as a description of the civil engineering and technical services associated with the installation. Several larger system tests have been performed to validate the two-beam scheme, and of particular importance are the results from the CLIC test facility at CERN (CTF3). Both the machine and detector/physics studies for CLIC have primarily focused on the 3 TeV implementation of CLIC as a benchmark for the CLIC feasibility. This report also includes specific studies for an initial 500 GeV machine, and some discussion of possible intermediate energy stages. The performance and operation issues related to operation at reduced energy compared to the nominal, and considerations of a staged construction program are included in the final part of the report. The CLIC accelerator study is organized as an international collaboration with 43 partners in 22 countries. An associated report describes the physics potential and experiments at CLIC and a shorter report in preparation will focus on the CLIC implementation strategy, together with a plan for the CLIC R&D studies 2012–2016. Critical and important implementation issues such as cost, power and schedule will be addressed there.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

A round bobbin critical current measurement and thermal runaway simulation of REBCO coated conductors

A round bobbin test has been widely used to measure critical current Ic of practical superconductors including Nb–Ti, Nb3Sn, and Bi-2212 round strands at 4.2 K and in high magnetic fields but rarely used for rare earth-barium-copper-oxide (REBCO) coated conductor tapes. Here, we applies this method to REBCO tapes and test their Ic at 77 K, self-field, and 4.2 K with a magnetic field of 14 T applied parallel to the tape. The sample carries very high current densities; it is 1.3 m long and has a dense array of voltage taps that allows probing localized thermal runaways and correlation with Ic variations along the length. At 77 K, the Ic values of all sections were measured and found to be rather uniform. However, at 4.2 K, we found that a 3 cm section has 90% of the overall voltage drop and it went into thermal runaways upon further increasing current. Thus, at 4.2 K, we were prevented by localized thermal runaways and unable to determine Ic of most of the REBCO conductor sections; this behavior is different from Bi-2212 and Bi-2223 for which Ic of all turns of a round barrel sample can be determined. We simulate REBCO tapes during current ramping to a thermal runaway and analyze impacts of various factors including cooling, conductor n-values, and thickness of stabilizer on the thermal runaway current Iq. The combined experiments and simulations identify n-value as a crucial factor that leads to the observed differences between Bi-2212 and REBCO. Together with cooling and the standard deviation of Ic variations along the length, the n-value determines whether Iq is above or below the average Ic of a long piece of conductor and their ratio Iq/Ic,ave, greatly affecting quench detection and thermal runaway prevention strategies of Bi-2212 and REBCO magnets.

Mosat, Marek↗
DOE OSTI2023

Generalizing mkFit and its Application to HL-LHC

mkFit is an implementation of the Kalman filter-based track reconstruction algorithm that exploits both thread- and data-level parallelism. In the past few years the project transitioned from the R&D phase to deployment in the Run-3 offline workflow of the CMS experiment. The CMS tracking performs a series of iterations, targeting reconstruction of tracks of increasing difficulty after removing hits associated to tracks found in previous iterations. mkFit has been adopted for several of the tracking iterations, which contribute to the majority of reconstructed tracks. When tested in the standard conditions for production jobs, speedups in track pattern recognition are on average of the order of 3.5x for the iterations where it is used (3-7x depending on the iteration). Multiple factors contribute to the observed speedups, including vectorization and a lightweight geometry description, as well as improved memory management and single precision. Efficient vectorization is achieved with both the icc and the gcc (default in CMSSW) compilers and relies on a dedicated library for small matrix operations, Matriplex, which has recently been released in a public repository. While the mkFit geometry description already featured levels of abstraction from the actual Phase-1 CMS tracker, several components of the implementations were still tied to that specific geometry. We have further generalized the geometry description and the configuration of the run-time parameters, in order to enable support for the Phase-2 upgraded tracker geometry for the HL-LHC and potentially other detector configurations. The implementation strategy and high-level code changes required for the HL-LHC geometry are presented. Speedups in track building from mkFit imply that track fitting becomes a comparably time consuming step of the tracking chain.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Distributed out-of-memory NMF on CPU/GPU architectures

We propose an efficient distributed out-of-memory implementation of the non-negative matrix factorization (NMF) algorithm for heterogeneous high-performance-computing systems. The proposed implementation is based on prior work on NMFk, which can perform automatic model selection and extract latent variables and patterns from data. In this work, we extend NMFk by adding support for dense and sparse matrix operation on multi-node, multi-GPU systems. The resulting algorithm is optimized for out-of-memory problems where the memory required to factorize a given matrix is greater than the available GPU memory. Memory complexity is reduced by batching/tiling strategies, and sparse and dense matrix operations are significantly accelerated with GPU cores (or tensor cores when available). Input/output latency associated with batch copies between host and device is hidden using CUDA streams to overlap data transfers and compute asynchronously, and latency associated with collective communications (both intra-node and inter-node) is reduced using optimized NVIDIA Collective Communication Library (NCCL) based communicators. Benchmark results show significant improvement, from 32X to 76x speedup, with the new implementation using GPUs over the CPU-based NMFk. Good weak scaling was demonstrated on up to 4096 multi-GPU cluster nodes with approximately 25,000 GPUs when decomposing a dense 340 Terabyte-size matrix and an 11 Exabyte-size sparse matrix of density 10 -6 .

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Chlorination of Side Chains: A Strategy for Achieving a High Open Circuit Voltage Over 1.0 V in Benzo[1,2-b:4,5-b']dithiophene-Based Non-Fullerene Solar Cells

Here, a benzo[1,2-b:4,5-b']dithiophene-based donor material with chlorine atoms substituted on its side chains, named PBClT, was designed and developed for application in non-fullerene solar cells to enhance the open-circuit voltage ( V oc ) without decreasing charge carrier transfer in the corresponding blend films. The results demonstrated that the chlorinated PBClT polymer was an efficient donor in non-fullerene polymer solar cells (PSCs) and exhibited a blue-shifted absorbance, resulting in more complementary light absorption with non-fullerene acceptors, such as ITIC. In addition, the chlorine substitution decreased the HOMO level of PBClT, and as a result, the V oc of the corresponding solar cell increased dramatically to 1.01 V, which is much higher than that of the non-chlorine analog, PTB7-Th, with a V oc of approximately 0.82 V. The 2D-GIWAX results illustrated that the PBClT/ITIC blend film exhibited a “face-on” orientation, which suggested that the chlorine substituents on the side chains favored π-π stacking in the direction perpendicular to the electron flow in photovoltaic devices. Furthermore, the PBClT/ITIC blend film showed a π-π stacking distance of 3.85 Å, which was very close to that of its non-chlorine analog blend film with a distance of approximately 3.74 Å. Based on this result, the introduction of multiple chlorine atoms on the conjugated side chains not only adjusted the energy level of the low-band-gap polymer through the electron withdrawing ability of the chlorine atoms but also subtly avoided obvious morphological changes that could result from strong steric hindrance in the main chain of the polymers. The PBClT/ITIC-based PSCs exhibited a maximum PCE of 8.46% with a V oc of 1.01 V, which is an increase in the PCE of approximately 22% compared to the PTB7-Th-based device based on our parallel experiments.

14 SOLAR ENERGY↗
DOE OSTI2022

Designing for Zero Energy and Zero Carbon on a Multi-Building Scale Using URBANopt: Preprint

Groundbreaking efforts are necessary to mitigate contributors increasing impacts of climate change. In parallel to inventing pioneering clean energy technologies it is even more fundamental to rethink designing energy systems within a singular facility and collectively to function as a district. Facilities should not be continuously passive by just consuming; there is a need to shift to perform more dynamically. Designing for zero energy and zero carbon on a multi-building scale can uncover opportunities for building energy efficiency, decarbonization, demand flexibility, and resiliency that are not accessible at an individual building scale. This approach can be challenging without innovative tools to evaluate the multitude of possibilities. As an investigated result, we highlight the use of a campus-scale energy modeling platform - URBANopt™ - for the expansion of the National Renewable Energy Laboratory's (NREL's) South Table Mountain campus in Golden, Colorado. Programmatic growth included the design of three new all-electric, zero-energy, and zero-carbon, mixed used buildings (a combination of research laboratories and office space). This investigation is critical to NREL reaching net-zero emissions for its operational footprint, which will occur in phases over the next decade. Leveraging URBANopt's capabilities, we evaluate 1) high-performance building energy efficiency and decarbonization measures, 2) 4th generation district heating and cooling (4th GDHC) systems, 3) optimized onsite generation and energy storage assets that meet zero-energy and zero-carbon targets at minimum life-cycle costs, and 4) cost-optimal distributed energy technology mixes, dispatch strategies, and associated capacities that increase resiliency to grid outages. This work demonstrates the use and capabilities of URBANopt through a real-world case study on a multi-building scale.

community energy model↗
DOE OSTI2020

Conceptual Design Report -- eSPS

The design of a primary electron beam facility at CERN is described. It re-enables the SPS as an electron accelerator, and leverages the development invested in CLIC technology for its injector and as accelerator R&D infrastructure. The facility would be relevant for several of the key priorities in the 2020 update of the European Strategy for Particle Physics, such as an electron-positron(e-p) Higgs factory, accelerator R&D, dark sector physics, and neutrino physics. In addition, it could serve experiments in nuclear physics. The electron beam delivered by this facility would provide access to light dark matter production significantly beyond the targets predicted by a thermal dark matter origin, and for natures of dark matter particles that are not accessible by direct detection experiments. It would also enable electro-nuclear measurements crucial for precise modelling the energy dependence of neutrino-nucleus interactions, which is needed to precisely measure neutrino oscillations as a function of energy. The implementation of the facility is the natural next step in the development of X-band high-gradient acceleration technology, a key technology for compact and cost-effective electron/positron linacs. It would also become the only facility with multi-GeV drive bunches and truly independent electron witness bunches for plasma wakefield acceleration. The facility would be used for the development and studies of a large number of components and phenomena for a future e-p Higgs and electroweak factory as the first stage of a next circular collider at CERN, and its cavities in the SPS would be the same type as foreseen for such a future collider. The operation of the SPS with electrons would train a new generation of scientists. The facility could be made operational in about five years and would operate in parallel and without interference with Run 4 at the LHC.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Low-Temperature Plasma-Based Metrology of Lithium-Ion Battery Electrode Materials (CRADA Final Report)

As part of the Cyclotron Road program, SirenOpt Inc. evaluated its low-temperature plasma-based metrology sensor prototype for measuring multiple critical properties of lithium-ion battery electrode materials in parallel and in real-time. Cost-effective, minimal-waste manufacturing of high-performance battery electrode materials will be vital for achieving society’s net-zero carbon emission goals. Because existing electrode metrology sensors cannot operate within most sections of manufacturing lines, manufacturers often complete hundreds of processing steps before they can test their products and detect problems. When manufacturers perform these offline tests, they typically only test a small portion of the manufactured products. Current electrode manufacturing thus often yields many low-quality products, or off-spec products that must be thrown away all together. For example, at least 6% of the total lithium-ion battery manufacturing cost (i.e., over $250 million/year for the average gigafactory) is devoted to processing defective electrodes that are not scrapped until performance tests are failed during late-stage quality control checks. Electrode variability also leads manufacturers to build extra cells into battery packs to reduce the risk of poor performance. For example, many electric vehicle (EV) manufacturers include up to 10% more cells than needed, which substantially increases the cost and weight of the final EV product. The SirenOpt sensor can potentially enable early detection of poorly manufactured electrodes and allow them to be removed earlier from manufacturing lines, which can save battery manufacturers (hundreds of) millions of dollars per year. The sensor can further be used to improve product quality by accelerating R&D and process optimization, improving quality control, and enabling real-time process control. Overall, a real-time, in-situ metrology strategy can create unprecedented opportunities for implementation of smart manufacturing practices and advanced quality and process control solutions to realize higher battery electrode throughput and performance.

25 ENERGY STORAGE↗
DOE OSTI2020

A massively parallel and scalable multi-CPU material point method

Harnessing the power of modern multi-GPU architectures, we present a massively parallel simulation system based on the Material Point Method (MPM) for simulating physical behaviors of materials undergoing complex topological changes, self-collision, and large deformations. Our system makes three critical contributions. First, we introduce a new particle data structure that promotes coalesced memory access patterns on the GPU and eliminates the need for complex atomic operations on the memory hierarchy when writing particle data to the grid. Second, we propose a kernel fusion approach using a new Grid-to-Particles-to-Grid (G2P2G) scheme, which efficiently reduces GPU kernel launches, improves latency, and significantly reduces the amount of global memory needed to store particle data. Finally, we introduce optimized algorithmic designs that allow for efficient sparse grids in a shared memory context, enabling us to best utilize modern multi-GPU computational platforms for hybrid Lagrangian-Eulerian computational patterns. We demonstrate the effectiveness of our method with extensive benchmarks, evaluations, and dynamic simulations with elastoplasticity, granular media, and fluid dynamics. In comparisons against an open-source and heavily optimized CPU-based MPM codebase [Fang et al. 2019] on an elastic sphere colliding scene with particle counts ranging from 5 to 40 million, our GPU MPM achieves over 100x per-time-step speedup on a workstation with an Intel 8086K CPU and a single Quadro P6000 GPU, exposing exciting possibilities for future MPM simulations in computer graphics and computational science. Moreover, compared to the state-of-the-art GPU MPM method [Hu et al. 2019a], we not only achieve 2x acceleration on a single GPU but our kernel fusion strategy and Array-of-Structs-of-Array (AoSoA) data structure design also generalizes to multi-GPU systems. Our multi-GPU MPM exhibits near-perfect weak and strong scaling with 4 GPUs, enabling performant and large-scale simulations on a 10243 grid with close to 100 million particles with less than 4 minutes per frame on a single 4-GPU workstation and 134 million particles with less than 1 minute per frame on an 8-GPU workstation.

Wang, Xinlei↗
DOE OSTI2022

Avoiding excess computation in asynchronous evolutionary algorithms

Abstract Asynchronous evolutionary algorithms are becoming increasingly popular as a means of making full use of many processors while solving computationally expensive search and optimization problems. These algorithms excel at keeping large clusters fully utilized, but may sometimes inefficiently sample an excess of fast‐evaluating solutions at the expense of higher‐quality, slow‐evaluating ones. We have previously introduced a steady‐state parent selection strategy, SWEET (“Selection whilE EvaluaTing”), that sometimes selects individuals that are still being evaluated and allows them to reproduce early. We perform a takeover‐time analysis that confirms that this strategy gives slow‐evaluating individuals that have higher fitnesses an increased ability to multiply in the population. We also find that SWEET appears effective at improving optimization performance on problems in which solution quality is positively correlated with evaluation time. We evaluate our approach on six simulated real‐valued optimization problems and three real‐world applications: an autonomous vehicle controller problem that involves tuning a spiking neural network and two adversarial EA problems. We further evaluate SWEET versus a basic asynchronous process in a simulated setting. We present evidence that SWEET outperforms basic asynchronous processes in a use‐case in which performance is positively correlated with evaluation time, and performs comparably (and often better) than basic asynchronous processes in several use‐cases where performance is negatively correlated with evaluation time. That said, in the cases where performance and evaluation time are negatively correlated the variance of outcomes for SWEET is notably high.

97 MATHEMATICS AND COMPUTING↗